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A Spatial analysis of property tax revenue and fire vulnerability in Oakland, California

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A Spatial analysis of property tax revenue and fire vulnerability in Oakland, California
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Albornoz, Alejandra Uribe
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Denver, Colo.
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University of Colorado Denver
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Master's ( Master of Science)
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University of Colorado Denver
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Department of Geography and Environmental Sciences, CU Denver
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Environmental science

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Full Text
A SPATIAL ANALYSIS OF PROPERTY TAX REVENUE AND FIRE VULNERABILITY
IN OAKLAND, CALIFORNIA
by
ALEJANDRA URIBE ALBORNOZ
B.A. Arizona State University, 2007
A thesis submitted to the Faculty of the Graduate School of the University of Colorado Denver in partial fulfillment of the requirements for the degree of Master of Science Environmental Science
2016


2016
ALEJANDRA URIBE ALBORNOZ
ALL RIGHT RESERVED


This thesis for the Master of Science degree by
Alejandra Uribe Albornoz has been approved for the Environmental Science Program by
Gregory Simon, Chair Deborah Thomas Rafael Moreno
December 17, 2016


Uribe Albomoz, Alejandra (M.S., Environmental Science)
The Geography of Inequality and the Fear of Fire Thesis directed by Associate Professor Gregory Simon
ABSTRACT
In 1991 the Oakland Hills firestorm burned the hillsides of northern Oakland and south-east Berkeley, in northern California. To this day, this fire remains the most damaging wildfire in California's history and the second deadliest in the state. Fires like the Oakland firestorm are a result of the urbanization processes guided by economic and social factors into fire vulnerable areas (like the Very High Fire Hazard Severity Zone VHFHSZ). This thesis is an spatial analysis of property tax revenue and fire vulnerability, in particular examines how the urban development in Alameda County resulting for the cities desire to increase property taxes potentially contributed to the production of vulnerability to fire within the area. In particular, how the VHFHSZ and Non-VHFHSZ differ, in terms of property tax revenue generated, across the various incorporated cities in Alameda County, in particular Oakland and the impact of Proposition 13 on Oakland's capacity to collect money from property taxes in the VHFHSZ and Non-VHFHSZ. The data set used for this research is the Assessor Secured Roll Financial Year 2012/2013 from the Alameda County Assessors Office. This data set contains information about the location and price (among other things) of about half a million parcels in Alameda County.
The research combines two element for the theoretical framework to discuss the research questions and the result. First, the political ecology ecology perspective is used to un-
IV


derstand how vulnerability to hazards could have been produced by the pursuit of cities to increased tax revenue. Second, the concept of the production of vulnerability is used to describe areas more exposed to wildfires, based on economic, social and environmental factors. Furthermore, the continuous production of fire vulnerability in Oakland results from the joint influence of both decision-making and city planning. The research concludes with the policy implications and recommendations based on the results generated.
The form and content of this abstract are approved I recommend its publication
Approved: Gregory Simon
v


DEDICATION
I would like to dedicate this thesis to my husband Julien Riel-Salvatore for all of his unconditional love and support, I would have not been able to follow this dream without him. I will also like to thank my parents for passing on to me their love for nature and academia. I finally want to mention my two sons Mateo and Sebastian who make me want to be the best person I can be.
vi


ACKNOWLEDGEMENTS
I would like to thank my advisor Gregory Simon for all his guidance and patience, and for providing me the opportunity work with him during a research assistant at Stanford..
I also want to thank Deborah Thomas for all of her knowledge and pushing me to be the best I can be. Thank you also to Rafael Moreno for all of his classes and continuous long-distance support while working on completing my masters and thesis from abroad. Finally, I want to thank to the people at The Center for Spatial and Textual Analysis (CESTA) at Stanford for giving me the opportunity to work with you and learn many new things.
Vll


TABLE OF CONTENTS
CHAPTER
I. INTRODUCTION................................................................... 1
Background of the Problem.................................................. 1
History of Fires in the Area........................................ 1
California.................................................... 3
Alameda County and Fire Vulnerability......................... 3
Oakland' History of Development..................................... 4
The Geography of Alameda County and Oakland......................... 5
The Fire Hazard Severity Zones...................................... 9
Economic Responsibility for for Fire Management.................... 10
Fire Mitigation Activities......................................... 13
Statement of the Problem.................................................. 14
Research Question......................................................... 15
Format of the Study....................................................... 16
Significance of the Study................................................. 16
Definitions of Terms...................................................... 17
Proposition 13 .................................................... 17
Risk............................................................... 18
Very High Fire Hazard Severity Zone................................ 18
Vulnerability...................................................... 18
Wildland-Urban Interface........................................... 19
viii


II. THEORY AND LITERATURE REVIEW.............................................. 20
Framework I: Political Ecology......................................... 20
Introduction..................................................... 20
The Political Ecology of Hazards................................. 21
The Elements that Shape Hazards.................................. 22
Proposition 13 .................................................. 23
Urban Sprawl..................................................... 24
Oakland Property Values and Taxes...................................... 25
Framework II: The Concept of Vulnerability and its Production.......... 27
Summary................................................................ 29
III. METHODS.................................................................. 31
Introduction........................................................... 31
Research Design........................................................ 31
Data.................................................................
Data Processing and Analysis........................................... 35
Question 1 ...................................................... 35
Question 2....................................................... 39
Property Values........................................... 39
Year of the Property Reassessment......................... 40
IV RESULTS................................................................... 42
IX


Question 1
42
Part 1: Alameda County................................... 43
Part 2: The \ I II I ISZ and the WUI in Alameda....... 46
Part 3: The \ I II I ISZ and the Non-VHFHSZ........... 50
Question 2..................................................... 52
Part 1: Property Value................................... 53
Part 2. Year of the Property Reassessment Value.......... 56
V. DISCUSSION
Introduction.......................................................... 61
Key Findings.......................................................... 61
Policy Implications................................................... 64
Vulnerability, a Dynamic Concept............................... 64
The Limit that Guides Urban Sprawl............................. 66
Effective Tax System........................................... 67
Future Research....................................................... 68
Limitations of the Study.............................................. 69
REFERENCES.................................................................. 70
APPENDIX.................................................................... 73
x


LIST OF TABLES
TABLE
1.1 Oaklands breakdown of revenues by fund for the Fire Service Agency for
I-Â¥2012-2013...................................................................... 12
3.1 List of GIS layers used.................................................. 34
3.2 List of layers created including a description of each................... 38
4.1: Total property taxes collected 2013 in each of the incorporated cities of
Alameda County.................................................................... 44
4.2: Total property taxes collected 2013 within the VHFHSZ in each of the
incorporated cities of Alameda County............................................. 51
4.3 Distribution of property last date of purchase or reassessed value based
on year and location (VHFHSZ and Non-VHFHSZ).................................. 57
4.4 Descriptive statistics for the VHFHSZ and Non-VHFHSZ based on the
date of purchase / reassessed in value............................................ 59
xi


LIST OF FIGURES
FIGURE
1.1 Representation of the history of wildfires in California by year................ 2
1.2 Location and distribution of fires in Alameda County based on the decade
it happened............................................................................. 4
1.3 Map of Alameda county's incorporated cities.................................... 6
1.4 Map of Oakland tract median home value............................................. 8
1.5 Illustration of the division between county- and city-level budgets............ 12
4.1. The city wide level scatter plot of Single Family Residential Parcels by
the total tax.......................................................................... 45
4.2 Map of the distribution of the Very High Fire Hazard Severity Zone
(VHFHSZ) in Alameda County............................................................. 47
4. 3 Map of the distribution of the Wildland -Urban Interface (WUI) in
Alameda county, California............................................................. 48
4.4. The WUI level scatter plot of Single Family Residential Parcels by the
total taxes............................................................................ 49
4.5 The VHFHSZ level scatter plot of Single Family Residential Parcels by
the total tax.......................................................................... 49
4.6 Box-and-whiskers plot of the distribution of the property taxes for the Single
Family Residential Parcels in Oakland based on location of the property............. 52
4.7 Map of distribution of Oaklands single family units based on the Assessed
xii


value of the home..................................................................... 54
4.8 Map of the distribution of the comparison between values for the Oaklands
single family units................................................................... 56
4.9 Box-and-whiskers plot of the distribution of Single Family Residential Parcels Residential Parcels property taxes in Oakland, CA based on the year
the property was purchased............................................................ 58
xiii


LIST OF ABBREVIATIONS
CALFIRE California Department of Forest and Fire Protection
FY Financial Year
HZSZ Fire Hazard Severity Zone
SRA State Responsible Area
VHFHSZ Very High Fire Hazard Severity Zone
WUI Wildland Urban Interface


CHAPTERI
INTRODUCTION
In 1991 the Oakland Hills firestorm (aka, the Tunnel Fire) burned the hillsides of northern Oakland and south-east Berkeley, in northern California. To this day, this fire remains the most damaging wildfire in California's history and the second deadliest in the state: it burned 1600 acres, destroyed 2900 structures, killed 25 people and seriously injured another 150 people. The Oakland Hills firestorm adds to a growing list of wildfires located in the Wildland-Urban Interface (WUI) and the Very High Risk Hazard Severity Zone (VHFHSZ). This outcome is the result of an urbanization processes in the area that has been driven by economic and social factors that ultimately increased its inhabitants vulnerability to wildfires. This thesis examines how the growth of cities located in the VHFHSZ in Alameda County particularly in Oakland has contributed to the production of fire vulnerability in the area, and especially how development guided by economic incentives to increase property taxes ultimately contributed to its increased fire vulnerability. In addition, it examines how political circumstances like Proposition 13 have contributed to Oaklands vulnerability to wildfires and enabled certain groups within the population to benefit disproportionately from the property tax revenue collected.
Background of the Problem
History of Fires in the Area
California
A portion of Californian's history has been written by the wildfires that have
1


shaped the state. Even though fires are part of natural disturbance regimens for California's ecosystems, these historical patterns have been disturbed by the interactions that humans have with their environment, especially over the last few hundred years. Today, this relationship between humans and their environment has led to an intensification of the problem and made wildfires a major threat to the residents of California. In fact, CalFire statistics for the past 83 years show that 70% of the largest wildfires in California happened only in the last 20 years (CalFire, 2015). Interestingly, while the destructiveness of wildfires has increased over the years, the number of wildfires itself has decreased and the amount of acres burned per fire that displays a fluctuating trend (Figure 1.1).
Wildfires Damages
500.000
450.000
9000
150.000 *00.000
250.000
300.000
150.000
100.000 50,000
% \ \ \ \ '% \ \ '% \ \ \ \ \ S
|
C
1
---------Number of lira . Acres Hunted -------- Number of Structure* Dimsgcd
Figure 1.1. Representation of the history of wildfires in California by year, the number of acres burned. The left y-axis measures total acres burned and the right y-axis measures the total number of fires. As can be observed, there is no clear trend between the number of acres burned and the number of fires. The data used in this graph indicates only the fires that happened in the SRA and it does not includes any local data (i.e. the statistics from the incorporated cities). (CalFire, 2011).
Over the same period, California's population has increased sevenfold, creating an
ever growing demand for housing across the state. Unsurprisingly, largely because
2


growing numbers of people settling in the state has translated into a corresponding increase in the number of structures exposed to wildfires, 35% of the most damaging fires in state history have occurred in the last 15 years. Further, 30% of households in California today are at high or extreme risk of being affected by a wildfire and the state has the highest number of households (ca. 375,500) at high or extreme wildfire risk in the country (NFPA, 2015). In fact as of 2013, California ranked first in the nation in terms of the yearly number of fires and total amount acres burned. Unsurprisingly, as of today, seven of the ten most costly wildfires in US history took place in California. (Department of Interior, 2016.)
Alameda County and Fire Vulnerability
Alameda County is located in the eastern portion of the San Francisco Bay area of California. In recent years, the county has experienced a growing number of fires due to a combination of compounding factors that include high winds, unusual droughts, complex terrain, excess of natural and man-made fuels, and poor urban design (FEMA 1991). The eastern part of the county (North and Sound) has borne the brunt of these fires, and the most damage has accrued in the East Bay Hills (East Bay Parks, 2015; see Figure 1.2). In fact, over the past 90 years, the hills have been the setting of 15 major fires, including the three most significant events after the Oakland Hills Firestorm, namely the Berkeley Fire (1993), the Fish Canyon Fire in Oakland (1970) and the Wild Cat Canyon Fire, also in Oakland (1980) (FEMA, 1991). All said, the Tunnel Fire of 1991 was in some ways just one more indicator of the areas vulnerability to wildfires as well as another piece of evidence that human factors contribute to producing this vulnerability.
3


Figure 1.2 Indicates the location and distribution of fires in Alameda County based on the decade it happened. The rectangle at the right present a zoom in in the Oakland/ Berkeley area. Adapted from (East Bay Regional Park District, n.d.).
Oakland's History of Development
To understand how Oaklands urban design has increased the citys vulnerability to wildfires over time, it is first important to understand the history of its urban sprawl. Urban sprawl is a well-studied phenomenon that describes the growth of low-density development in urban areas as a response to rapid increases in population (Radeloff et al., 2005). It is characterized by high numbers of people moving from rural to urban areas and by extensive resulting developments occurring near or in the WUI (FEMA, 2002: see Figure 1.3). In the specific case of Oakland, urban sprawl took place in large part in the citys fire vulnerable hills, which are often both WUI and VHFHSZ areas.
The development of Oaklands Hills begins in the 1850s, with the first logging activities in the area and the construction of the first railroads. Together, these activities combined to define the area that would be the target of future development (Simon,
4


2014). The rapid increase of the citys population following the San Francisco Earthquake of 1906 saw the construction of large single-family homes, which were built to house upper class families in the Hills (FEMA, 1991); such houses would occupy a significant portion of the Hills by the 1920s. In the 1950s and 1960s, public and private investors seeking to attract new homeowners into the area financed the construction of new upper-middle class residences and two major high-density developments along the slopes. By the 1970, two-story condominiums and townhouses followed and in 1991, when the Oakland Hills Firestorm took place, the Hills were already an established upscale neighborhood (Simon, 2014).
In part, the large-scale development of the Oakland Hills between 1950s and 1970s was driven by the desire to increase the citys budget through the collection of property tax from its new residents.Unfortunately, around the same time, the Tax Revolt movement was gaining momentum, a process that culminated with the passage of Proposition 13 in 1978, which would ultimately reduce how much tax could be collected by limiting the growth of house values (Simon, 2014).
The Geography of Alameda County and Oakland
The county of Alameda is located in California, in the eastern portion of the San Francisco Bay area. According to the U.S. Census Bureau (U.S.Census Bureau, 2015), the county covers a total of 821 square miles 739.02 square miles of land and 82 square miles of water. Alameda County is home to 1.5 million people, 90.6% of which live in 14 incorporated cities, and mainly in Oakland which holds the county's seat. The 14 incorporated cities are Alameda, Albany, Berkeley, Dublin, Emeryville, Fremont,
5


Hayward, Livermore, Newark, Oakland, Piedmont, Pleasanton, San Leandro, and Union City (Figure 1.3). The county also houses six unincorporated communities Ashland, Castro Valley, Cherryland, Fairview, San Lorenzo, and Sunol.
Album ^Hcrkck>| Lmctvv illc
Incorporated ( ilin in Alnim-dn County
PtcximoiK
\Lun Dublin
Sun I oindio
I r. ii-u >
HmHBIIN
I f i He
I lUlfl < ll\
NcW-k 1 ,CI,knl
Akuncda Caunty lnaxpuiatcd Cities
0 2 2545 9 135 18
I btoes
Figure 1.3 Map of Alameda county's incorporated cities. The unincorporated cities are not displayed in this map, the reason why is because these cities do not governed themselves but instead belong to the State Responsibility Areas.
This thesis does not consider data from the unincorporated communities because their fire security services are managed by the county since they are located on the State's Responsibility Area (SRA). Alameda County is bordered by Contra Costa County to the north, San Joaquin and San Mateo Counties to the east, Stanislaus County to the southeast, and Santa Clara County to the south. Geographically, Alameda County is defined by a series of hills and ridges that run from north to south in its western portion and divides
6


the county into two parts: the 32-mile long coastal plain and the Livermore-Amador Valley. The series of hills and ridges extends across many cities in the county, and they can be up to 12-mile wide and 1,500ft high, depending on the area. In the south-eastern portion of the county, next to the Livermore-Amador Valley, the Diablo Range begins, reaching elevations up to 3700ft.
The city of Oakland is located in the northern portion of the county, next to San Francisco Bay. The city covers 78 square miles (55.8 square miles of land and 22.2 of water) and is home to 406,000 people, or about one quarter of the county's population, making it the eighth largest city in California (Census). The city is bordered by Berkeley to the north, San Leandro to the south, Emeryville to the north-west, Alameda across the estuary, and Piedmont, a small city within the northern portion of Oakland. Characterized by a Mediterranean climate, the city ranges in elevation from sea level to 1,900ft (Oakland Geology, 2010). Oakland's territory houses a variety of habitats, including 19 miles of coastline, smaller patches of wetland, large areas of grassland, oak woodlands, and hills.
The city of Oakland is a vibrant urban community that comprises a myriad of cultures and ethnic groups that cross-cut socio-economic backgrounds. According to the U.S. Census, Oakland is home to 406,000 people, or about a quarter of Alameda Countys total population of 1,510,271 according to the latest census figures. The city comprises 28% of the county's households and 60% of its housing units are occupied by renters (compared to 50% for the county). Oakland is also one of the most ethnically diverse cities in the country, with 27 % foreign-bom inhabitants and 40 % of people speaking
7


languages other than English at home. Today, Oakland's racial makeup is 28% African American, 26% white (non-Hispanic) 25% Latino, 17% Asian, and 4% other. However, these figures have changed dramatically over the past 60 years: In 1940, for instance, 95% of the population was white, a figure that had dropped to about 60% by 1970 and reached the low 30s in the 1990s (US Census). Equally important are the high levels of poverty that characterize Oakland: according to the 2010 census, 20.5% of Oakland residents live in poverty compared to 13% for Alameda County as a whole (Figure 1.4).
Median Home Value in Oakland (2013)
Parcel -Median Home Value
3 No Data
> 350 k
n 350 K lo 500 K
500 k 750 K. |>750K
Figure 1.4 Map of Oaklands tract median home value in 2013. This map indicates the distribution of the median home value in Oakland based on the census tract. The values
are divided in four categories below 350k between 350k and 500k, 500k 750k and more than 750k. This categories where created based on division of the data in quartiles.
8


The city of Oakland is divided in two main parts, the Hills and the Flatlands, each of which is characterized by distinct own social, economic and political make-ups (Simon 2014, Dooling and Simon 2012). The social changes just discussed have also varied by area, with the Hills having become inhabited mostly by white residents while the Flatlands became mostly non-white over the same period (Simon 2014). Likewise, average house prices are also closely tethered to location. In 1940, the average house cost $100,000 in the Hills and while $70,000 in the Flatlands; by 2010, these figures had reached $900,000 in the Hills and $400,000 in the Flatlands, that is to say, a nine-fold price increase in the Hills but less than a six-fold increase for the Flatlands (Simon 2014). Similarly, today the homeownership rate is lowest in the Flatlands where 25%-33% of the population also lives below the poverty line (McClintock 2011; Figure 1.4).
The Fire Hazard Severity Zones
The Fire Hazard Severity Zone is a designation created by Californias Department of Forests and Fire (CalFire) to identify areas most susceptible to fire and influence the way people build in and protect them. This designation was created by measuring the physical conditions that makes an area susceptible to fires and modeling the likelihood that it will of catch fire in the next 30 to 50 years. That said, the FHSZ evaluates fire hazards and not fire risk, the latter being the potential damage that can be caused by a fire. The probability of an area catching fire is calculated by using the following Fire Hazard Elements: a. vegetation (vegetation over a 30- to 50-year time horizon); b. topography (up steep slopes); c. weather (hot, dry, and windy conditions); d. crown fire potential (top of trees and tall brush); e. ember production and movement (the spread of
9


fire brands from the main fire); f. likelihood (chances of an area burning based on history) (CalFire, 2007).
Fire hazards zones are assigned to one of three categories: moderate, high, and very high. Californias state law dictates that the FHSZ designations need to be used in all State Responsible Areas, including all unincorporated communities. Local agencies (incorporated cities) are encouraged by CalFire to incorporate the Very High Fire Hazard Severity Zone designation for hazard prevention and planning (CalFire, 2015d). In 2008, CalFire created maps for the five cities in Alameda county that are located in (or partially located in) within the VHFHSZ; these are Berkeley, Oakland, Piedmont, Pleasanton and San Leandro (CalFire, 2015).
Economic Responsibility for Fire Management
Identifying who bears the economic responsibility for fire mitigation and prevention efforts in the area and where the money for these efforts should come from is another important issue. As damages caused by wildfires continue to increase, so does the cost to maintain and protect the areas they have affected. Fire mitigation efforts are funded by state and municipal sources, both of which draw needed revenue mainly from collected tax, and especially property tax, though this is the only source. At the local level, each of Alameda Countys 14 incorporated cities is at least partially responsible for protecting their territory; these municipalities include Albany, Berkeley, Dublin, Emeryville, Fremont, Hayward, Livermore, Newark, Oakland, Piedmont, Pleasanton, San Leandro, and Union City (Figure 1.3). In contrast, it is Alameda County that manages the State Responsible Areas (SRA) responsible for the protection of the unincorporated
10


communities of Ashland, Castro Valley, Cherryland, Fairview, San Lorenzo, and Sunol.
According to Californias Legislative Analysts Office, the amount of property taxes paid by a homeowner is determined by two factors. First, the Tax Rate is based on the location (or Tax Rate Area [TRA]) of a parcel within the county/city; in Alameda County, the TRA was 1.086-1.405% of the total property cost for FY 2012-2013. The second factor includes Fixed Charges and Special Assessment, which are special fees voted by residents. One example of these is the special fee of $65 charged to residents living in the Oakland Wildfire Fire Prevention Assessment Area. Once tax revenue is collected, 1% of it is funneled to the county budget while the remainder is directed to the cities (e.g., if a parcels TRA is 1.405%, 1% goes to the county while the remaining
0.405% goes to the city).(Figure 1.5 )
Both the county and the cities that comprise it have a primary fund called the General Fund which manages all revenues and expenditures. In Oakland, for FY2012/2013, property tax accounted for 30.82% of the citys General Purpose Fund, which was allocated to various expenditures.
Oaklands municipal budget comprises both the General Purpose Fund and the Non-Discretionary Funds; together, they are called All Funds. The General Purpose Fund is the main source of money for the Fire Service Agency(Table 1.1). In FY 2012-2013, 24% of the General Purpose Fund went to the Fire Service Agency. The sources of revenue for the Fire Service Agency come from the local (96.25%), county (3.20%) and federal (0.55%) levels. For the same fiscal year, the General Purpose Fund contributed to 87.7% of the Fire Service Agency budget, making it the Agencys main source of money .
11


P*iHKl> T\e $ 320.4 M
SIMc FcxWi.il A f xal Unmurnl Ant
$ I.2TTM
Property Tnn $125,100,501
Uka Taxes
$273,511,907
- Dumirn Lkom Tn. < nlKv rNB( (kunil Fund
$2.022 4 M
(jflKnl Fluid $397,478,464
Fur IWfvuWnml
$ 110.855.515
- 223*. corner from Ptegieity Tax Revenues. the ml num boui chapex ( aeixtcn (00 4 4t)and other miuw(l7.)S)
Fur SctMfc Ajccotv $108552.305
4715, corner from hcycill I aver Revenues oyiaal to $95 309.445 Ibr iniuay^i 22 3 comer fur* rancor rouccer
Nw Vnxc Aecucx $ 15* 840.0.41
ITfcn Ajprocws
$143,422,392
H (Mclaad [ liKorymUd clwr []5UU RofraMNlia Am
Figure 1.5 Illustration of the division between county- and city-level budgets. Interestingly, for that same period, while 22.95% of the citys budget was directed to fire mitigation, 87.7% of the revenues came from property taxes. In contrast, in Alameda Countys proposed budget, 15% of collected property tax is allocated to fund activities like fire services; the rest is allocated to education (40%), redevelopment (13%), the various cities (18%) and miscellaneous items.
Table 1.1 Oaklands breakdown of revenues by fund for the Fire Service Agency for FY2012-2013. White row indicate federal funds; dark grey rows indicate county/state funds; light grey rows indicate local/city level funds.
Name of F und.Source of Money total Amount \niounl 1 vrd (or Fire Servlets Percent of Ike F und used foe F ire Serv ices Percentage* of ( oMrUautlom to the Budget
(uncial Fund (kitcral Purpose 197 .4?* 4M 95.209.445 2195 *7 7|
Self Imurancc Liability 19.305 >49 i.4*i .no 1.77 IJ7
Reeve liny Fropam yW|.Tf7 48,870 854 095
Comprehensive (lean-up I8.C04.5JI9 179.274 109 017
711.3*0 0*6
US IV*p( ol KitmiicIaimI Security 187,891 187891 100 00 0.17
fcdctil l Agency 429.4 IT 429.158 *9*4 040
hniK Counts Measure N: Fund
Measure Y: Public Safety Act 2004 Wildland Fire Prevention Aucu Dtunct Weiner Court Vegetation Myim I linnet
myiEfl
Supplemental \vvc
* I
Scvtcr Service Fund
24.TJ2 1.413.545 22.54l.7ftl 1,850,51* *,20)
T4M97
49.0)8.: 19
25ftjn
ToUl
424.UIO.24V
108452.204
1410 <10
12


In FY 2012-2013, 24% of the General Purpose Fund went to the Fire Service Agency. The sources of revenue for the Fire Service Agency come from the local (96.25%), county (3.20%) and federal (0.55%) levels. For the same fiscal year, the General Purpose Fund contributed to 87.7% of the Fire Service Agency budget, making it the Agencys main source of money .
Fire Mitigation Activities
The fire mitigation activities in the city of Oakland are regulated by the Oakland Fire Service Agency and is target at two levels, the citywide and the VHFHSZ. The Fire Prevention Bureau Oakland, a subdivision of the Fire Service Agency, is in charge of overseeing the fire mitigation activities at the two levels. The bureaus role is to provide the and ensure the compliance with fire prevention codes and standards to insure the communities health and safety at the city level. This is done by providing various services at the citywide level like fire safety education, fire cause investigations, inspection of high hazard occupancies, fire code enforcement, hazardous materials regulation, and vegetation management (City of Oakland, 2016). In addition, the Fire Prevention Bureau is also in charge to oversee the Wildfire Prevention Assessment District, a voters approved tax collected in the Special Assessment portion of the property for the people that live in the VHFHSZ. The role of this special fee is to fund prevention programs in the VHFHSZ like the Goat Grazing Program Property Owner Free Chipping and Debris Removal program, Vegetation Management Program (on public lands), Fire Prevention Education & Training Program, Roving Fire Patrol Program and Support Services for Inspection Program. In FY2012/2013, the Fire Prevention Bureau adopted
13


budget was $5,586,370, from which 33% ($1,850,518) was funded by The Wildfire Prevention Assessment District Fund to provide fire mitigation efforts in the VHFHSZ of Oakland.
Statement of the Problem
The operating costs of municipal fire departments are mainly funded by property taxes. As mentioned above, the Oakland Hills were heavily developed in 1950s to 1970s to increase the amount of collected property tax and boost the citys operating budget. Since the city is responsible for the costs of wildfire mitigation and since some parts of the city are more likely to be directly affected by fire than others, funds collected though property taxes can be used to protect the more fire vulnerable areas. Today, the Hills are significantly more affluent than the Flatlands in Oakland, meaning that the less affluent part of the population may well be paying to protect the most affluent one, which would perpetuate cycles of inequalities.
In principle, property tax revenue should offset the cost of living in highly vulnerable areas. Based on fire prevention costs, the houses located in these vulnerable areas are clearly very expensive for the city to maintain, but the amount paid in property taxes by individual homeowner may not actually correspond to the real cost of owning houses in the Hills. If that is the case, it is doubly problematic since it means that more resources are funnelled to protect the most exposed areas (i.e., the Hills), leaving correspondingly less money to pay for municipal services in other, less affluent areas (i.e., the Flatlands). This would compound problems deriving from wealth disparities across the city, since the people who are least vulnerable to wildfires (in the Flatlands)
14


remain more socially vulnerable because they are also less able to react to other challenges as a result of their limited socio-political agency and economic marginalization.
With these elements in mind, this thesis seeks to critically examine the economic history of cities in the VHFHSZ of Alameda County and how urban planning potentially enabled some people to receive more benefits than others from the revenues generated by this development, which may have contributed to the production of future vulnerability. The thesis uses political ecology as a theoretical framework to identify three main topics vulnerability, urban sprawl and economic responsibility through which these issues can be tackled.
Research Questions
The development of cities in Alameda County, especially Oakland, appears to have served as a tool to generate increasing revenue and to have potentially enabled certain parts of the population to benefit from this system more than others. This in turn likely contributed to the production of vulnerability throughout the county. To approach this topic, the subject was divided into two parts:
1. How do the VHFHSZ and Non-VHFHSZ differ in terms of how much tax revenue they generate in the various incorporated cities in Alameda County and in particular in Oakland?
2. How has Proposition 13 affected Oakland's capacity to collect property tax in the VHFHSZ and Non-VHFHSZ?
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Format of the Study
The research presented in this quantitative study is based on an Alameda Assessor Office dataset. This dataset indicates the Assessed Property Values for properties in Alameda County (2012) and calculates the fixed tax rate based on the TRA of the parcel. The dataset includes records for almost half a million Alameda County residential properties for FY 2012-2013 (businesses are excluded). This dataset thus permits to identify who pays tax (and how much of it) and to compare this to the risk of fire for the area. The research presented here analyzes these records and is divided in two stages: the first will determine the amount of property tax generate from the various cities located in the VHFHSZ and Non-VHFHSZ within Alameda County; the second will compare how political circumstances like Proposition 13 may have complicated the capacity for cities to collect adequate amounts of property tax. It should be pointed out here that this study disregards fixed charges and special assessments because these are voted-in fees meant to fund specific public projects that residents of a given city will directly benefit from.
Significance of the Study
At its most basic level, this study aim is show how much tax revenue is being generated, who is paying this amount, and how these payments relate to actual property values. Oakland contains two parallel societies that differ in social, economic and environmental characteristics, and which are exposed to urban challenges in different ways. Traditionally, political ecology has sought to address how marginalized groups of people live in the most vulnerable areas. In the case of Oakland, however, we face an opposite situation: the areas most vulnerable to fire (i.e., the VHFHSZ) are occupied
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groups of wealthy people while the areas less vulnerable to fire (Non-VHFHSZ) are less wealthy. This situation was complicated by the passage of Proposition 13 which was designed to keep the assessed value of houses artificially low (compared to actual home values) and ultimately had the effect of reducing the potential amount of revenue collected though property tax. This situation potentially benefited the wealthier members of the community by creating pockets of people that paid proportionally less than their share in property taxes.
This thesis seeks to provide a picture of the distribution of property taxes collected in the VHFHSZ and Non-VHFHSZ. In addition, it addresses how political circumstances like Proposition 13 have allowed for certain parts of the city to disproportionately benefit from the property tax system in place. As a result, the least vulnerable members of the community (who happen to be less affluent) pay for the fire protection for the most vulnerable, who happens to be the citys most wealthy citizens. The results from the study contribute to a growing body of research that explores the issue of vulnerability in the First World and how this vulnerability can be shaped by political circumstances.
Definition of Terms
Proposition 13
Proposition 13 (1978) was responsible for creating a major change in Californias taxation system by limiting the amount of money that can be collected though property taxes by keeping house values artificially low (i.e., lagging well behind inflation). Since the rate of homeownership and property value increases in the Hills was higher, people
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living in the Hills supported the proposition to a greater degree than those living the Flatlands. Ultimately, Proposition 13 opened the door to intensified development in the city as a tool to generate more tax revenue through property taxes, a phenomenon that ultimately contributed to the production of vulnerability to fires (Simon 2014; Dooling, Simon 2012).
Risk
The probability that a system is affected by a hazardous event leading to negative consequences (United Nations, 2009). In order to calculating risk we need to identify the hazard event (frequency and intensity of the treat), exposure (people or assesses affected by in the hazard) and vulnerability (the lack of capacity of a population to sustain potential looses from a hazardous event).
Risk = Hazard Event x Exposure x Vulnerability
Very High Fire Hazard Severity Zone (VHFHSZ)
In Alameda County, the Very High Fire Hazard Severity Zone is defined based on the information provided in CalFire 'Fire Hazard Severity Zones'. This area is located in the local, state and federal responsibility areas. It was defined by CalFire to delineate the areas of greatest fire hazard and fire risk as a way to measure the physical fire behaviour. The zone is based on measuring various fire hazard elements like topography, slope, vegetation, weather, crown fire potential, and ember production and movement Vulnerability
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Vulnerability can be defined as the characteristic of a system that makes it susceptible to the effects of a hazard(United Nation, 2009) and the likelihood the system would experience harm based on the exposure to a hazard (Turner, B. L., 2003). In order to determine how a system can be exposed to, affected by, or impacted by the hazard, it is important to identify elements that affect vulnerability (United Nation, 2009).
Vulnerability in this thesis refers to the hazard exposure based on the geographical location. In the case of Oakland, according to CalFire, the area most vulnerable to fires is the VHFHSZ, located mainly in the eastern portion of the city along the Hills. For the purpose of this thesis, vulnerability to wildfires (metric) is defined by the structures exposed to fire and to a lesser extent the adaptive capacity of people that live/work in these structures.
Wildland Urban Interface (WUI)
The WUI is the area where were urbanization has expanded to the intermingled and undeveloped wildland (Radeloff et al., 2005). Composed of interface and intermix communities, the WUI is defined by the minimum density of houses in an area (i.e., one structure per 40 acres). Traditionally, the WUI has been described as an area highly vulnerable to fire. The International Association of Wildland Fire (IAWF) organization defines the WUI as the geographic location where structures and flammable vegetation merge in a wildfire-prone environment (IAWF, 2013). In the wester US, 72% of houses are located in the WUI (the county average is 39%) (Radeloff et al., 2005), meaning people face an increasing risk and vulnerability to wildfires.
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CHAPTER II
THEORY AND LITERATURE REVIEW
The theoretical framework used in this thesis combines two elements. First, a political ecology perspective helps understand how vulnerability to hazards could have been produced by the pursuit of cities to increased tax revenue. Specifically, it helps raise the question of how political circumstances like Proposition 13 affected the capacities of the city to generate revenues. Second, the concept of the production of vulnerability is used to describe areas more exposed to wildfires, based on economic, social and environmental factors. Furthermore, the continuous production of fire vulnerability in Oakland results from the joint influence of both decision-making and city planning. This thesis examines how factors like urban sprawl and political facilitations like Proposition 13, help increased the hazard vulnerability areas with.
Framework: Political Ecology
Introduction
Political ecology is a field of study that uses political, economic and social frameworks to examine environmental issues. This multidisciplinary approach seeks to understand the relationship between nature and society and the consequences of this relationship on the environment and sustainable livelihoods (Watts, 2000; p. 257). Political ecology recognizes that environmental change can be the result of activities that are shaped by their political context, in which degradation and deterioration result from, and continue to shape the relationship between humans and the environment (Stott and Sullivan 2000). Moreover, this approach explores how broader systems of power and
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influence, impact unevenly who benefits most within a social-economic system (Robbins, 2012).
Bryant and Bailey (1997, pp. 27-28) outline three fundamental assumptions of political ecology:
1. "Costs and benefits associated with environmental change are for the most part
distributed among actors unequally;"
2. "Unequal distribution of environmental costs and benefits reinforces or reduces
existing social and economic inequalities;"
3. "Differentiated social and economic impact of environmental change also has political implications in terms of the altered power of actors in relation to other actors." The Political Ecology of Hazards
Traditionally, the political ecology framework argues that marginalization occurs when vulnerable segment of the population get systematically denied full access and/or control over their resources (Bryant and Bailey, 1997; Robbins, 2004). This situation can be seen very clearly in developing countries, where political, economic and social relationships often severely limit the ability of people to deal effectively with environmental change (Robbins, 2002; 2004). That said, the marginalization process generally concentrates vulnerability to hazards within certain segments of a population. However, the effects of that hazard vulnerability on the marginalization of communities are not always the same. For instance, the process leading to people living in vulnerable areas varies according to whether you are living in the developed or the developing world (Collins, 2008). In developed countries, people who are not marginalized in the least
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often purposely choose to live in areas that are more vulnerable than others (e.g., the inhabitant of the Oakland Hills). This is because of social arrangements like insurance coverage, land use regulations, emergency response and disaster relief subsidies that enable the wealthy to settle in these highly vulnerable places without suffering the same consequences as they would in impoverished neighborhoods, or developing countries (Collins, 2008; p. 22). Given that certain segments of the population are more vulnerable to specific hazards than others, the political ecology of hazards deals with the effects of social inequalities on the capacity of these vulnerable groups to cope with and manage the risk posed by hazards (Wisner et al., 2004). In this case, risk is described as compound function of biophysical hazard exposure and peoples' vulnerability (Collins, 2008; p. 22). Social vulnerability refers to the pre-existing conditions influencing a persons or a groups ability to cope with a hazard and its aftermath.
The Elements that Shape Hazards
Vulnerability and the risk to fires in Oakland have been shaped by contributing factors like urban sprawl and state policies, like Proposition 13, that drove the development in the area. The political ecology framework helps highlight a series of multi-scale contributing factors that shaped vulnerability to fires in Oakland. Using this framework provides an intellectual structure to investigate how political decisions and facilitations allowed and encouraged people to settle and build in fire vulnerable areas, thus increasing vulnerability to wildfires in the area. Consequently, vulnerability was in large part the result of these same political circumstances. Using a political ecology framework to confront this problem allows us to examine who was responsible for
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making these areas vulnerable and to assess the role of private citizen vs that of the government in fire prevention and mitigation. Untangling the history of urban development in the Hills will permit the identification of beneficiaries of the present situation as well as an analysis of the hidden dimensions of who bears the real cost of sprawl relative to the cost of mitigation.
Proposition 13
In 1978, almost two-thirds of Californians voted to pass Proposition 13 to restructure property taxation in the state by significantly reducing the amount paid in property taxes (Legislative Analysts Office, 2012). This new legislation introduced two important elements: first, the maximum owed tax by property was fixed at 1% of its value, and second, a propertys assessed value could only increase by one percent annually, unless there was a change in ownership or a significant renovation was undertaken, both of which could increase the value of the property to current market assessment (Oakland Policy Budget, 2009). Proposition 13 therefore reduced the amount of revenue that could be collected though property taxes by keeping the assessed value of the home artificially low (i.e., substantially below inflation), which stunted price growth over time and, consequently, potential city revenue. Proposition 13 was the result of the neoliberal ideology that was fundamental to Californias Tax Revolt, which reflected peoples discontent with public spending. During this time, neoliberalism help restructure the relationship between the state and the market, ultimately creating deregulations that benefited the wealthiest (Hohle, 2015).
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Urban Sprawl
Urban sprawl is defined as the horizontal expansion and development of cities into land that is undeveloped (EPA, 2014; Nechyba and Walsh, 2004). Several factors have allowed cities and suburbs to expand into exurbs and rural areas. First, population growth: over the past centuries, as US population has continued to grow rapidly, the number of people living in urban centers has grown considerably. For instance, in 1790, only 5% of the US population lived urban centers (Census Data). It was really only after World War II that urban development flourished and by 1950, more than 50% of the national population had moved to urban centers. Today, over 80% of the US population lives in urban areas (Nechyba and Walsh, 2004). Second, increased income: population growth was accompanied by an increase in income due to diversification in the job market, the number of available jobs, the variety of jobs, and the amount of pay; this gave people greater economic power. Lastly, a change in transportation behaviors based on the cheaper cost of transportation also facilitated the horizontal growth of cities, especially after World War II (Brueckner, 2000).
The growing body of research on urban sprawl has identified a myriad of factors to help describe and understand this concept. First, the basic measurement unit for urban sprawl is the urban cluster which the US Census Office defines as an area that contains 500-1000 people per square mile. Second, cities have grown based on physical (geometric) and functional (economic) patterns in order to help with the division of labor generated from scaled economics (Batty, 2008). Third, measuring urban sprawl can be challenging because it is not a unidimensional phenomenon. Multiple studies have
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attempted to measure urban sprawl by characterizing this phenomenon by its growth rate, density (distance and proximity), spatial geometry (shape, size), accessibility, and aesthetic measures (Frenkel and Ashkenazi, 2008; Theobald, 2005). Fourth, there are multiple views and studies addressing the benefits and downsides of urban sprawl. On the one hand, critics argue that this excessive growth is a problem that needs to be limited and controlled. On the other, supporters tend to agree that urban sprawl bolsters the overall economy due to the demands of growing population and the increase in property tax collected from the land developed.
As discussed previously, many fundamental forces drive urban sprawl but it is safe to say that the process of urbanization is closely related to the value of land (Brueckner & Kim, 2003). In recent years, several studies have explored the relationship between land use (zoning) and productivity, and how this affects the value of the land (i.e. urban land is valued higher than non-urban land). Researchers have found that there is a close relationship between how land is zoned (urban vs. non-urban) and its value. Land zoned as urban is worth more than non-urban land because of the money collected strictly through land taxes is less than the amount collected in property tax (Brueckner & Kim, 2003). Since property taxation has traditionally been an important source of revenue for cities, the potential for collecting larger amounts of money through increased property taxes can boost land development in and especially around cities (Brueckner & Kim, 2003).
Oakland Property Values and Taxes
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The city of Oakland presents a markedly uneven distribution of wealth, with the Hills being significantly more affluent than the Flatlands. Also, the Hills are located in the VHFHSZ, which makes them much more vulnerable to fire than the Flatlands. According to census data (US Census, n.d.), the mean income of Oakland residents is $52,583 and the medium value of owner-occupied houses is $428,900 (citywide). In the Hills the average value of a house is $ 900,000 compared to about $400,000 in the Flatlands (Simon and Dooling, 2012). Based on these prices alone, one can argue that the Hills are a very expensive and exclusive area; in fact, over the last 70 years, the average price for a house in the Hills has increased nine-fold compared to an increase of only 6.5 times in the Flatlands (Simon 2014). Since the cost of living in the Hills is higher than living in the Flatlands, one would expect that property taxes from the Hills would contribute more to the general city budget, in the same way that house insurance is higher for those who live in vulnerable areas. Based on the cost of housing of these two areas and trends in home price increase over time, it is however possible to see that one area has benefited more than the other from city planning and budgeting.
Elements that Shape Vulnerability in the Context of Political Ecology
The structural causes that lead to the increase in fire vulnerability in the area resulted from the poorly planed development of the city and the incentive to developed guided by economic reasons. These rapid urban growth into the Hills was possible because the new wealthy residents could afford to live in fire prone areas with the help of social facilitations (like fire insurance) that ultimately help them reduce the potential looses from a hazardous event. In addition, political circumstances, like proposition 13
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increased the fire vulnerability in the area because it allowed for the wealthy to pay reduced property taxes (based of properties assesses below market value) that ultimately contributed less to the city budgets .
Framework II: The Concept of Vulnerability and its Production
Historically, there has been a tendency to impose a disconnection between human and natural systems and to study them as separate elements of a puzzle. Currently, however, there is a growing trend of multidisciplinary research that links and studies these two systems together. The concept of vulnerability is one of these links that allows social and natural systems to be studied together (Simon and Dooling, 2012). According to the United Nations, vulnerability is the set of characteristics and circumstances of a community, system or asset that make it susceptible to the damaging effects of a hazard (United Nation, 2009). The concept of vulnerability deals with the relationship of humans with the environment and the social forces that shaped this relationship (Bankoff et al, 2004). Vulnerability is thus shaped by political, economic and social factors. Increases in vulnerability can enable certain members of a population to become more vulnerable than others based on their socio-economic characteristics. Vulnerability to hazards like fires can thus be described as a complex multifaceted relationship between social and ecological systems where social systems can be exposed to, affected by, or impacted by hazards (Simon and Dooling, 2012).
The factors that shape vulnerability to fires are assigned to one of two main categories: environmental and social. An ecosystems vulnerability to fires can increase when its balance is broken. Environmental factors like drought, low precipitation rates,
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type of land cover, type of vegetation, elevation, slope and an excess of natural fuel can all increase vulnerability to fire in an area. Similarly, social factors contribute to shape fire vulnerability and the exposure of people to these hazards. First, we must consider policy and budget considerations, since fuel reduction practices are constantly changing in response to budgetary considerations due to their cost and the fact that they are not always done properly. Second, the direction of urban sprawl and the rate of environmental modification also matter. As population continues to expand, it is necessary to take measures to control and regulate urbanization into formerly natural areas. Third, the characteristics of the population are also important. For instance, the demographics of an area can indicate variable levels of vulnerable populations for given hazards, like pregnant women, single parent households, elderly citizens, and young children. The income and education levels and the social background of the people in the area also have an influence (e.g., can they speak English, do they know how to react to a hazardous situation, do they have good fire insurance, are they poor or rich, etc.). Fourth is the proximity of people to the hazard (e.g., do they live in a high fire risk area or next to the mountains). Fifth, we must consider peoples economic capacity to recover form a fire (e.g., are they covered by insurance, do they qualify for government help). Finally, the capacity of people to react to a fire is also critical (e.g., do they have a car to evacuate in case of a fire, do they have good insurance to cover the cost of rebuilding their homes, etc.)
Human actions are often largely responsible for increasing vulnerability. In the specific case of the WUI, vulnerability to fires has increased over the years as a result of
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human actions that constantly reshape their ecosystems. Vulnerability is deeply rooted in the history of development of a place and can only be understood within its historical context and that of the social conditions of the population. Access to political power (or lack of it) and uneven distribution of wealth can reinforce social relationships and perpetuate (or amplify) disparities and the cycle of vulnerability (Thomas et al., 2013). The social characteristics of a population (e.g., health, income, disability, age, gender, ethnicity, literacy, or immigration status) can also aggravate vulnerability (Bankoff, 2006; Thomas et al., 2013; Wisner et al., 2003). As a consequence, the production of vulnerability is constantly shaped by human actions, which in turn can leave us more exposed to hazards like fire.
As it was indicated previously, the concept of vulnerability is a dynamic and can indicates multiple meanings. In this thesis, vulnerability refers to the hazard exposure based on the geographical location. In the case of Oakland, according to CalFire, the area most vulnerable to fires is the VHFHSZ, located mainly in the eastern portion of the city along the Hills. That said, vulnerability to wildfires (metric) is defined by the structures exposed to fire and the people that live/work in these structures.
Summary
Human-environment relations are complex and multifaceted; they are shaped by political forces, and neoliberal economic policies that tend to reinforce the uneven distribution of costs and benefits that emerge from these human-environment interactions. Power structures have allowed enable certain social groups to profit from political circumstances. Vulnerability to hazards is constantly shaped by human actions where
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social systems generate unequal exposure to risk. The city of Oakland is divided in two areas, the Hills and the Flatland. The first is very vulnerable to fire but happens to be very wealthy, while the second area is not vulnerable to fire but is less affluent. The political ecology framework helps us to frame how vulnerability to hazards was produced by the efforts of cities to increase tax revenue. This raises the question of how political circumstances like Proposition 13 may have affected the capacity of the city to generate revenue.
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CHAPTER III
METHODS
Introduction
The Oakland Tunnel Fire of 1991 left a deep mark on the history of California. Since then, the city of Oakland and the state of California have made multiple efforts to reduce the possibility of another disaster of similar magnitude. This study examines how urban development in the VHFHSZ in Alameda County may have contributed to the production of vulnerability (exposure) to fire within the area. In particular, it explores how the search for higher revenue contributed to increased risk to fire hazards throughout the area. To answer these questions, this thesis employs a quantitative research strategy to compare the tax revenue collected from houses located in areas vulnerable to fire to that from properties in low-risk areas. Furthermore, the research analyzes the long-term effects Proposition 13 has had on house values and how this may have affected the total amount of revenue collected in fire vulnerable areas. This is done to empirically describe housing in both locations, in order to objectively compare and contrast them. Ultimately, the results of the study framed in a political ecology perspective permit a discussion of the consequences of urban development driven by political incentives and also how political circumstances impacted the overall fire vulnerability (exposure to the hazard) of the area.
Research Design
The research was conducted and data were collected during a research assistantship conducted at Stanford University in 2013 in the context of the
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"Vulnerability in Production" project, a running initiative supervised by Dr. Gregory Simon (from CU Denver) in collaboration with researchers from both schools. Some of the data presented here were gathered during this research assistantship and the rest were acquired and analyzed after I had returned to UC Denver. The research focuses on how the development of cities in Alameda County and specifically Oakland was used as a tool to generate greater municipal tax revenue and how political circumstances like Proposition 13 contributed to Oaklands vulnerability to wildfire, while perhaps unwittingly enabling certain parts of the population to profit more than others from this extra revenue. To examine this development, the subject was divided into two parts:
1. How do the VHFHSZ and Non-VHFHSZ differ in terms of how much tax revenue they generate in the various incorporated cities in Alameda County and in particular in Oakland?
2. How has Proposition 13 affected Oakland's capacity to collect property tax in the VHFHSZ and Non-VHFHSZ?
The dataset used in this study contains the following independent variables (a) city (the various incorporated cities in Alameda County); (b) WUI or Non-WUI (located within the Wildland-Urban Interface or not); (c) VHFHSZ or Non-VHFHSZ (located within the Very High Fire Hazard Severity Zone or not); (d) Time (when was the house purchased). The following dependent variables were also included in the database: (a) The total amount of money collected in property taxes (city wide, WUI/Non-WUI and within the VHFHSZ/Non-VHFHSZ); (b) The total size of the area (city wide, WUI/Non-WUI and within the VHFHSZ/Non-VHFHSZ); (c) The year the structure was last
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reassess in value; (d) The total cost of the property (city wide and within the VHFHSZ/ Non-VHFHSZ).
Data
The main dataset used for this analysis comes from the Alameda Assessors Office, which compiled the Assessor Secured Roll 1 parcel information for Alameda County Finalcial Year 2012/2013. This dataset contains nearly half a million records for Alameda County, including residential, commercial industrial and other parcels. The information given for each record includes: a. the parcel number; b. the address; c. total value (land value and the land improvements); d. land use code (residential, commercial, industrial, etc.); e. the description of residential parcels (single, 2-4 units, and 5+ units parcels); f. the primary and secondary TRA (tax rate area); g. other information (like tax reduction for owners, etc.).
In order to standardize the dataset and make it more uniform, I derived a single unit of measurement, called Single Family Parcels. This was done according to the following sequential criteria:
1. Identify the residential parcels using the Property Assessment information codes from the assessors office (See Appendix A) and select occupied Single Family Parcels based on the use codes (1100 Single family residential homes used as such;
The county's Assessor Secured Roll file is a list of properties Assessed Value, based on the hen against the real cost of the property itself. In contrast to the secured roll, the unsecured property tax includes property like boats and airplanes, and the lien against the cost is not the property itself. The assessed value indicates 100% of the full value. http://www.acgov.0rg/a11ditor/tax/faqs.htm#PtaxSec
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1140 Single family residential home, R&T 402.1; 1150 Historical residential; 1190 -Single family residential (tract) common area or use; 1200 Single family res home with non-economic 2nd unit; 1300 Single Family Res home with slight commercial ind; 1440 Single Family Res Duet Style, R&T 402.1; 1900 Single family res manufactured).
2. Using the information given in the primary and secondary TRA and the rate indicated by the 2012-2013 Alamedas Tax Rate Book (See Appendix B for summary), calculated the fixed tax rate for each record.
3. Finally, to avoid skewing the results, houses that did not have any information (null values) or that paid very little (i.e., less than $100 a year) were excluded for the final analysis. In other words, properties that cost less than about $10,000 were omitted, to avoid giving undue influence to empty or partially built houses among other exceptions.
This dataset was later joined to a series of GIS layers containing the parcels location and shape for the various cities in Alameda County. In addition to the Assessor Secured Roll data, other GIS layers were used to complete the analysis (see table 3.1); henceforth, all GIS layer used NAD83 StatePlane CA III Ftps 0403 (US feet) projection. Table 3.1 List of GIS layers used
Layer Source Original Projection
County Boundary Alameda County.shp Alameda County GIS viewer WGS1984 Mercator
Alameda Parcels Parcels.shp Office of Alameda County NAD_1983_State Plane CA III
Fire Hazard Zone ** clfhszl06 3 l.shp CalFire NAD 1983 Alberts
The Wildland-Urban Interface WildlandUrbanlntermix05 l.shp CalFire NAD_1927_Alberts
Cities in Alameda *** City Limits, shp Alameda County CDA NAD_1983_ State Plane CAIII
* This layer was joined to tax dataset using the Joins and Relate Function by the held named GisJoin.
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* * This layer contained the three levels of FHSZ. Using the select by attribute, I selected the VHFHSZ and exported to layer into a new layer.
* * The city limits layer contain all of the cities in one layer, Using the select by attribute, I selected each city by name and exported into a layer.
Data Processing and Analysis
The data was collected during the summer of 2013 as part of a research assistantship conducted at Stanford University in the context of the "Vulnerability in Production" project under the supervision of Dr. Gregory Simon. The data processing and analysis presented here were done in subsequent semesters as part of the thesis work. In order to address the research questions presented earlier, the data processing and analysis section of this thesis is divided in two portions based on the two research questions.
Question 1: How do the VHFHSZ and Non-VHFHSZ differ in terms of how much tax revenue they generate in the various incorporated cities in Alameda County and
in particular in Oakland?
The first part of the methodology seeks to quantify how much property tax was paid by the various residential parcels in each of the cities in Alameda County and in particular for the cities located in the VHFHSZ. In order to answer this question, I used ArcGis to analyze the dataset previously described (in the data section) in conjunction with the GIS layers (Table 3.1). Given that the tax dataset was very large and was making the computer analysis very slow, I broke down the dataset into smaller pieces. To begin the analysis, I first created the outline of each city from the Cities of Alameda layer (see Table 3.2 a), then used the joint the data to the tax dataset (see Table 3.2 b). This part provided me with the information on total area, number of parcels, number of single family residential parcels, net home values, total amount of property taxes collected, the
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mean and SD for each of the incorporated cities in Alameda County. The data were later characterized using descriptive statistics to establish the mean, standard deviation and coefficient of variation of the number of parcels, and the amount of taxes paid. This first step allowed me to create a basic profile of the county and a distribution of the home values and property taxes paid.
Then, I used the Select by Location tool to identify the parcels located within the VHFHSZ layer for each city and the exported the layer (see table 3.2 e). The spatial method used was have the centroid in the source layer feature, in order to avoid accounting for the same polygon in two different layers. For example, if one portion of a parcel was located in the VHFHSZ layer and the rest in the Non-VHFHSZ, the location of the centroid of the polygon was what determined whether the parcel was considered as being located in the VHFHSZ. The result provided information on the total area, number of parcels, number of single family residential parcels, net home values, total amount of property taxes collected etc., for the part of the city located within the VHFHSZ for each of the incorporated cities in Alameda County.
After reconstructing the distribution of the parcels located in the VHFHSZ for the various cities, the next step was to determine the distribution of the parcels not located in the VHFHSZ. In order to identify the parcels in the Non-VHFHSZ, I used the citywide layer and the Erase tool to erase the parcels located in the VHFHSZ (Table 3.2 f).
This technique allowed me to make sure there were no doubles in the data and there were no polygons counted in both the VHFHSZ and the Non-VHFHSZ. The results provided information on the total area, number of parcels, number of single family residential
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parcels, net home values, total amount of property taxes collected etc., for the part of the city not located the VHFHSZ.
According to California Department of Forestry and Fire Protection (CalFire), the VHFHSZ is the most vulnerable area to fires in Alameda County (compared to the WUI); for this reason, this research focuses on the VHFHSZ vs the Non-VHFHSZ areas. Nonetheless, since the great majority of the fire mitigation literature focuses on preventing fires in the WUI, I used the same methodology to identify the parcels located in the WUI and Non-WUI. These various data then allowed me to compare and contrast the relationship between WUI/Non-WUI and VHFHSZ/Non-VHFHSZ. It also allowed me to discuss why we should preferentially use the VHFHSZ designation.
This methodology allowed me to identify all of the residential parcels contained at the citywide, VHFHSZ, Non-VHFHSZ WUI and Non-WUI levels for the various incorporated cities in Alameda county (Table 3.2). Then, I analyzed the data collected using descriptive statistics to establish the mean, standard deviation and coefficient of variation of the number of parcels. As a result, the GIS analysis, Excel querying and statistical analysis allowed me to address quantitatively how the VHFHSZ and Non-VHFHSZ differ for the various incorporated cities in Alameda County.
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Table 3.2: List of layers created including a description of each. The following layers and naming convention were used for all of the incorporated cities in Alameda County.
Layer Processing Notes
a Name of city Ex: Oakland - Selection Select by attribute select by name of city - Geoprocessing Intersect (outline of city selected and the Alameda parcels layer) City outline with parcels
b Name of city + Tax Ex: OaklandTax - Joins and Relates Join (joined tax dataset to the City layer using the held GisJoin. - Export the layer City outline, parcels and tax information.
C Name of city + WET Ex: Oakland_WUI - Selection Select by location (Target layer: CityTax; Source layer: WUI) *Spatial method: have the centroid in the source layer feature -Export the layer The parcels and the tax information located in the WUI. This was done to avoid accounting for the same polygon in two different layers (i.e. if the parcel was partially occupied by the WUI layer, the location of the centroid of the polygon will decide whether it belong or not to the WUI layer)
d Name of city + NONWUf Ex: Oakland_NONWUI - Analysis tools overlay Erase (input feature CityTax layer; erase feature: City_WUT layer. The parcels and the tax information not located in the WUI.
e Name of city + VHFHSZ Ex: Oakland_VHFHSZ - Selection Select by location (Target layer: CityTax; Source layer: VHFHSZ) *Spatial method: have the centroid in the source layer feature -Export the layer The parcels and the tax information located in the VHFHSZ. This was done to avoid accounting for the same polygon in two different layers (i.e. if the parcel was partially occupied by the VHFHSZ layer, the location of the centroid of the polygon will decide whether it belong or not to the VHFHSZ layer)
f Name of city+ NONVHFHSZ Ex: Oakland_NONVHHSZ - Analysis tools overlay Erase (input feature CityTax layer; erase feature: CityJVHFHSZ layer. The parcels and the tax information not located in the VHFHSZ.
38


Question 2: How does Proposition 13 affected Oakland's capacity to collect money
from property taxes in the VHFHSZ and Non-VHFHSZ?
The second part of the methodology seeks to provide a picture of the distribution in the property values in Oakland and of the effects that tax laws like Proposition 13 have had on property values over the years. Proposition 13, passed in 1978, limited the amount that can be collected in property taxes. As a result, property values were maintained artificially low and well below inflation. Thus, the amount of property tax collected can vary significantly even between neighboring properties, since it is based on the year the property last changed its reassessment value (i.e., changed owners or had significant remodeling that lead to a reassessment). Given that Proposition 13 provided a setting for producing irregular patterns in home value distribution, the second portion of this analysis was designed to identify areas where there might be residents under- or overpaying tax on their houses (i.e. properties that are paying below the median home value)To answer this question, I used the VHFHSZ and Non-VHFHSZ datasets previously generated to identify areas whose home value had not kept with the property market. To do that, the methodology considers two elements, the property value and the year of reassessment of the value.
Property Values
This part of the study was designed to identify parcels that paid below or above the median home value. To do this, the dataset included a field called Total Net which indicated the value of the property. In order to take into account the cost variation from the various portions of the city, I calculated a new field called Cost Comp that used the
39


US Census tract Median Home value (field name: T_MedVal) information and compared it to the net value (Total_Net). Then, I calculated the product by by 100 and dividing that figure by the tract value field, I was able to derive a percentage measure of how much (or less) the property is paying. To give an example, if a house net value (field name: Total Net) is $250k and the Census tract Median Home value (field name: T_MedVal) is $300k, I subtracted the $300k $250K =50. Then, I multiply 50 by 100% and divided by 300, the result was 16.66% which correlates to the field theCostComp. From there, I created a new field called Cost_Comp2 that classified the percentages in categories. This was done with the help of Select by Attributes tool, I assigned the following values to the following categories: 1 = 0-10% below asking prize; 2= 10-25% below asking prize; 3 = 25-50% below asking prize; 4 = 50-100% below asking prize; 5 = >100% below asking prize. I used the categories previously created (i.e., Cost_Comp2 = 1) to create a series of points that indicated the location of parcels that payed below. From there, I was able to use the Optimized hot spot analysis tool to find clusters of properties paying below and above market value (based on the categories created in the field Cost_Comp2). The result of this first portion yields a series of data and maps that indicating clusters within the city of the areas paying below and above the tract's median home price in the VHFSZ and the Non-VHFHSZ.
Year of the Property Reassessment
This section aims to provide an overview of the effects that the year of a property last reassessed had on the value. Since the year of reassessment can be a limiting factor of how much a property can increase in value, it is important to see whether or not there
40


is a relationship between low values and the year the property was purchased. To do this, the dataset included a field called last-documented_prefix which indicated the year the property got last reassessed in value. I summarized the data based on the location ( VHFHSZ/ Non-VHFHSZ) and the year of reassessment.
41


CHAPTER IV
RESULTS
Introduction
The Oakland Tunnel Fire of 1991 remains the most damaging wildfire in Californias history and to this day the state government continues to make multiple efforts to reduce the possibility of another disaster of that scale. This thesis examines how urban development emerging in Alameda County along the VHFHSZ (as a way to increase property taxes) potentially contributed to the production of vulnerability to fire (exposure to the hazard based on the geographic location) within the area. In order to examine this subject, the Results chapter of this thesis is divided in two sections. The first section addresses the question of how the VHFHSZ and Non-VHFHSZ differ, in terms of property tax revenue generated, across the various incorporated cities in Alameda County, in particular Oakland. The second section addresses the impact of Proposition 13 on Oakland's capacity to collect money from property taxes in the VHFHSZ and Non-VHFHSZ.
Question 1: How do the VHFHSZ and NonVHFHSZ differ for the various incorporated cities in Alameda County and in particular in Oakland?
In order to answer my first research question, the subject was divided into 3 portions. First, I began by providing a profile of Alameda County, including a full description of the area, the number of residential parcels (per city) and the total amount of property tax collected (per city). From there, I indicate the location of the VHFHSZ and the WUI in Alameda County, including a description of the area, the number of the
42


residential parcels (per city) and the total amount of property taxes collected (per city). This part allowed me to explain why we should focus the research on the VHFHSZ and not the WUI. Finally, I focus in the description and location of the VHFHSZ in Alameda County and its cities. This part provides a description of the area, the number of the residential parcels (per city) and total amount of property taxes collected (per city) from the VHFHSZ and Non-VHFHSZ.
Part 1: Alameda County
The county is located in the eastern portion of the San Francisco Bay area and covers 744.31 square miles (sqmi), over half of which is urban. The urban sprawl of the county runs parallel to the coast and decreases with the beginning of the hills that run through the middle of the county. The original dataset included nearly half a million records (445,427) from the Assessor Secured Roll for Alameda County FY 2012/2013. This dataset included the information for Alameda Countys residential, commercial, industrial, rural and institutional parcels. The information given for each record includes the parcel number, the address, the total value (land value and the land improvements), the land use code (residential, commercial, industrial, etc.), the description of residential parcels (single, 2-4 units, and 5+ units parcels), the primary and secondary TRA (tax rate area) and other information (like tax reduction for owners).
The results from the data analyzed for the first question are summarized in two parts. Table 4.1 contains the information for the area, the number of parcels, the total amount of property tax collected, and the mean and SD of the Single Family Residential
43


Parcels property taxes. Figure 4.1 present the total property taxes collected in 2013 in
each of the incorporated cities of Alameda County.
Table 4.1: Total property taxes collected 2013 in each of the incorporated cities of Alameda County
All Panels r Family Htimrs Parrels
Total Parcels Residential Percent Total tries Single Tots! Tates Mean SO
Parcels Residential (US dollars I Family Parcels 1 US dollars)
Alameda Is. ISJ2Z 17.255 91 16 Mi.T55.CiOk 14.074 60.154.464 41271 2.722
Albans 4.661 4.174 I9 60 Ift.Wl.tTO 3*725 16.444.304 4.416 3.029
Hcrkelcs 26.216 21.660 90 14 II4.59TJI26 17.514 79.671.664 4344 1.906
Dublin II,MO 10.11? 47 16 55 321.22* I.99K 49,791366 5314 2.949
Inicrvsille 1.127 166 50 22 4.472.105 220 524,714 2.40! l>7*
Fremont 56.46? 51.825 91 78 254349.415 49.076 212.271.021 4.711 1388
llavmnl 12.149 27.810 46 5? 85J4.1.497 25.119 70.446.918 2306 IJ470
1 rvcrmorc 26.906 24.549 91 24 94.142.301 23355 91.012.601 4JOOO 2.496
Newark 11,616 10.634 91.54 16.371,524 10.009 11.495300 1366 1.961
Oakland 94.1152 47.511 14 55 V40.964.764 44.609 254.617.972 1.766 1.444
Piedmont 4.030 3.94} 94 04 .16.469,114 1J4S2 16.521.401 9.442 4.965
Pleasanton 21.954 20.161 92.74 124.62746* 19.610 122.711300 6359 <744
San Leandro 21.014 20.759 40 19 61.245,977 19.000 14.016.064 2.444 1.644
Union Cny !** 16.16? 14.948 114.422 92 71 60.744,974 IJ77.I94JI95 I4JI6 277321 57.345J55 1.165.524,090 4.006 2341
From these data it was possible to draw the following observations: First, in Alameda County, 80% of the parcels (353,553 records including all types) are located within the 14 incorporated cities. The remaining 20% are distributed in the unincorporated communities and the SRA. Second, the city of Oakland, home to one quarter of the county's population, holds 28% of the parcels (98,852), from which 88% ( 87,533 parcels) are classified as residential, and in particular 69% (68,669 parcels) are Single Family Residential Parcels homes. Third, in Alameda County in FY 2012/2013, the Single Family Residential Parcels paid 85% ($1,165,524,696) of all property tax. In Oakland, the residential parcels contributed to 25% ($340,968,764) of the countys Property taxes, from which 76% ($258,617,972) came from Single Family Residential
44


Parcels. Fourth, the mean property tax paid by a Single Family Residential Parcel varied from city to city, the lowest being in Emeryville ($2,403) and the highest being Piedmont ($9,482).
400M
350M
300M J5 250M
I
B200M
I
| 150M
100M
50M OM .
OK 10K 20K 30K 40K
Total Area (sqmi) 1.25
I 20.00
4000
60.00
7678
City
Alameda b.
Albany
Berkeley
Dublin
Emeryville
Fremont
Hayward
Livermore
Newark I Oakland
Piedmont
I Pleasanton
San Leandro Union City
50K 60K 70K 80K
Single Family Parcels [Units]
o
Figure 4.1. The citywide level scatter plot of Single Family Residential Parcels by the total tax. The figure presents the relationship and size of the number Single Family Residential Parcels, the total taxes and the total area for each city at the citywide level. As is indicated by the legend, the size of the area is indicated by the size of the square, and the color code represent the various cities in Alameda County.
Fifth, even though the per capita property tax for Single Family Residential Parcels is highly variable (mean) so is the dispersion of the values around the mean. Sixth, compared to the rest of the cities, Oaklands standard deviation is greater than that most other cities, which indicates a very large distribution of property tax amounts. Seventh, in
45


general, as the number of parcels increase so does the amount collected from the properties, as is indicated by the very high R-squared value for this relationship.
In summary, residential parcels represent the vast majority of parcels in Alameda County, and about one quarter of these parcels are located in Oakland. The amount of taxes collected varies based on the number of parcel within the city and the total area.
The mean per capita property tax of the Single Family Residential Parcels is highly variable between cities, but so is the dispersion of the values around the mean (SD). Oakland presents the largest distribution on the data compared to the rest of the cities. Part 2: The VHFHSZ and the WIJI in Alameda
The VHFHSZ is a designation for a fire hazard zone model developed by the California Department of Forestry and Fire Protection (CalFire) and adopted by the local government to designate high fire risk zones. In Alameda, the VHFHSZ covers 8.1% (60.10 sqmi) of the territory and it runs almost diagonally along the hills from north to south. CalFire classified the fire hazard into three different levels: moderate, high and very high. These three levels apply to SRA territory except for the last level (Very High) which also applies to local territories (i.e., incorporated cities). With that in mind, in 2008 CalFire created identified and created maps for the cities at risk in Alameda County (Berkeley, Oakland, Piedmont, Pleasanton and San Leandro) (CalFire, 2015). As can be seen from the maps, the distribution of the VHFHSZ overlaps almost completely with the location of the WUI (Figure 4.2 and 4.3). This overlap it not a coincidence since the role of the VHFHSZ is to identify the portions of wildland vulnerable to fire hazards (CalFire, 2007).
46


x
The Ven High Tire Huurd Severity Zone in Alumcda CA
Albany^
^lk-itxlr\
Ktncrwille
Piedmont

- >!ir I. I
V*n I candro
I I I t 111 11
rlcavuilon
Hai id
I Fnion C its
Newark Hemcmt
MU Ms/
AUmrvti ( ounls
Incmpoialcd (Hies
13 5
I Miles,
Figure 4.2 Map of the distribution of the Very High Fire Hazard Severity Zone (VHFHSZ) in Alameda County. In Alameda the VHFHSZ overlaps some of the urban profile, this designation can be found in five cities: Berkeley, Oakland, Piedmont, San Leandro and Pleasanton.
In contrast, the WUI that area where urbanization has expanded into the intermingled and undeveloped wildland (Radeloff et al., 2005) covers 58.2% (433.02 sqmi) of Alameda County and it crosses the countys wetland, grassland/scrubland and woodland ecoregion, and it is found in all of the incorporated cities except Emeryville. Because the WUI is generally considered a place that is very sensitive to fires, it is included in this study but it is important to note that not all of the ecosystems the WUI comprises present the same risk of fire. As a result, since the WUI in this case study is not
47


Album \ ^tkffcclry
Lmcnvdlc
NMIdland -Irbam Inter face in Alameda. t'A
Piedmont
A Limed**
Ibiblm
McMMlOII
S in | eantlto
II DM vsl
I 'niott tits
Newark ,cnk,'
Livetmote
win
Incorporated C mo Alameda County
0 225 4 5 9
a good indicator for areas vulnerable to fire, the research is mainly interested in the
VHFHSZ and uses the WUI as a reference.
Figure 4. 3 Map of the distribution of the Wildland -Urban Interface (WUI) in Alameda county, California. In Alameda, the WUI covers a large percentage of the territory and it can be found in all of the incorporated cities except Emeryville.
The area covered by the WUI is six times larger than the VHFHSZ and covers twice as many cities. Figure 4.4 and 4.5 display the relationship between the number of Single Family Residential Parcels and the amount of property taxes collected. The total area occupied by the WUI and VHFHSZ is also indicated in these two figure.
48


200M
180M
I60M
140M
OK $K 10K I5K 20K 23K 30K 35K 40K Single Family Parcel (Units)
Total Area (sqmi)
0.89
f 10.00 20.00
30.00
40.00 53.92
City
Alameda Is.
Albany
Berkeley
Dublin I Fremont
Hayward
Livermore
Newark
Oakland
Piedmont
Pleasanton
San l-carxiro Union City
Figure 4.4. The WUI level scatter plot of Single Family Residential Parcels by the total taxes. As indicated in the legend, the size of the area is indicated by the size of the square.
20OM
180M
160M
Total Area (sqmi)
0.19
500
1000 17.32
140M
1
| 120M Q
& 100M
j
a 80M
2
60M
City
Berkeley Oakland
Piedmont I Pleasanton
San Leandro
40M
20M
0M
OK SK 10K ISK 20K 25K 30K 3SK 40K
Single Family Parcel (Uniti]
Figure 4.5 The VHFHSZ level scatter plot of Single Family Residential Parcels by the total tax. As indicated in the legend, the size of the area is indicated by the size of the square.
49


From these two figures, it is possible to observe the following patterns. First, as the
number of parcels increases so does the amount of tax collected. Second, as the size (total
area) of the city increases, so does the number of Single Family Residential Parcels and
the amount paid in property tax. This relationship is very clear with the units located in
the VHFHSZ; however in the WUI, this relationship does not follow the same pattern.
For example, Oakland occupies a smaller area than Fremont but contains more parcels
and raises more tax revenue, while Berkeley is one of the smallest cities (in terms of its
area) but draws the 4th highest amount in property taxes.
Part 3: The VHFHSZ and the Non-VHFHSZ
Five cities in Alameda County contain a portion of the VHFHSZ, but the size of
that area and the number of parcels contained in these areas varies greatly between cities
(Table 4.2). The percentage of a city that is covered by the VHFHSZ also varies
according to the location of the city. First are Oakland and Berkeley with 25% and 20%,
respectively, then Piedmont with 8% and finally Pleasanton and San Leandro with 2%
each. Based on these data, we can make the following observations. First, the average per
capita property tax (e.g., the mean calculated by dividing the total amount of tax
collected by the number of parcels) of Single Family Residential Parcels in the VHFHSZ
is more than the average property tax of Single Family Residential Parcels in the Non-
VHFHSZ. Second, the mean property tax for the Single Family Residential Parcels is
more variable (based on the dispersion of the values from the mean SD) in the VHFHSZ
than in the Non-VHFHSZ. Third, Piedmont and Pleasanton have the highest average
50


property tax in the VHFHSH; in the case of the Non-VHFHSZ Piedmont leads, with
almost 50% more than the others.
As discussed previously, the VHFHSZ is the area most vulnerable to fires in Oakland, and this analysis divides the city in two areas, VHFHSZ and non-VHFHSZ. That said, this section examines the different factors that can shape the relationship between the number of Single Family Residential Parcels and the amount collected in property tax within these two areas.
Table 4.2: Total property taxes collected 2013 within the VHFHSZ in each of the incorporated cities of Alameda County.
3 i TIFMS7. Nan VHF HSZ
City Single Family Pared Total Tnct ( dollar* ) Mean SD Percent of Pared* in VHFHSZ Single Family Pared Total Taxes ( dollars ) Mean SO
Berkeley 3.570 20.478.067 5.736 4.803 20 36% 13.064 50.105.601 54330 3.578
Oakland 17,460 104.706.846 5.007 4.8KS 25.43% 51.200 153.011,126 S3.006 3,073
Piedmont *24 5,646.460 11.255 10,028 8.41% 3.528 32.876,913 $0,319 8,844
Pleasanton 458 $.123,340 II. IN 6.467 2 34% 10.152 117,607.860 $6,141 4.631
Son Leandro 503 2.076J32 4.128 2.534 265% 18.407 51.050331 V2800 1.603
lolal 136.031.255 106.350 4I535U052
Based on the data collected for the city of Oakland (Table 4.3), it was possible to observe the following patterns. First, 29% of Oaklands territory is located in the VHFHSZ which corresponds to 25% of all Single Family Residential Parcels. In contrast, 75% of the Single Family Residential Parcels are located in the Non-VHFHSZ (Table 4.3). Second, 40% ($104 Millions) of the property tax in the city is paid by people who live in the VHFHSZ and the remaining 60 % ($153 millions) by the people that live in the Non-VHFHSZ areas (Table 4.3). Third, based on the box-and-whiskers plot of the
51


distribution of the property taxes for the Single Family Residential Parcels in Oakland (Figure 4.4), the people that live in the VHFHSZ pay higher taxes than the ones living in the Non-VHFHSZ based on the size of the boxes and the median line. Furthermore, the VHFHSZ presents a higher distribution (or spread of the values) than the Non-VHFHSZ. That said, it is important to consider that the citywide and the Non-VHFHSZ distributions are similar because there are three times more in the Non-VHFHSZ than in the VHFHSZ (i.e., the Non-VHFHSZ sample represents a much larger fraction of the total number of houses in the city).
Distribution of lax Collected in Oakland
100,000.00 -i--------------------------------------------
=
10,000 00
100.00 1 1 Non- VHFHSZ VHFHSZ All
Location
Figure 4.6 Box-and-whiskers plot of the distribution of the property taxes for the Single Family Residential Parcels Residential Parcels in Oakland based on location of the property. The light and dark grey boxes indicate the middle quartiles (2nd and 3rd quartiles, respectively) containing one quarter of the data each. The middle line in between the two boxes indicates the median of the data. Finally the top and bottom are the 1st and 4th quartiles, respectively, holding one quarter of the data each. The end of the top and bottom lines indicate the maximum and minimum number.
52


Question 2: How does Proposition 13 affected Oakland's capacity to collect money
from property taxes in the VHFHSZ and Non-VHFHSZ?
Before 1978, the property values were sky rocketing in California, Proposition 13 limited the amount of property taxes that can be collected. As a result, assessed property values dropped and taxes accrued at a rate well below inflation. This situation created an uneven distribution of home values and the concomitant property tax that could be collected even between immediately adjacent properties. Proposition 13 affected Oakland's capacity to collect money because it limited the assessment value of a property, only allowing for the property to update its price when the property changed owner or the property underwent major renovations resulting in an increase in value. Since the capacity to collect money is based on the year of purchase and the cost paid, I examined the two criteria to see if there is any relationship for the distribution of the two.
Part 1: Property Value
Oaklands property value distribution varies according to location (based on social and economic variables not analyzed in this thesis) and the time when the property was last sold or reassessed. The Hot Spot analysis indicates the distribution of single family residential parcel based on the value of the home (Figure 4.7). The map indicated what we already know, two concentrations, one of the properties of high value and the other low value. The a great portion of the distribution of properties of high value overlaps (as it was expected) with the Hills and the value of the home (Figure 4.7). The map indicated what we already know, two concentrations, one of the properties of high value and the other low value.
53


Figure 4.7 Map of distribution of Oaklands single family units based on the Asses value of the home. The hot spots (red) in the map indicate the areas were 90% (or more) of the single family units pay high value for there property. In contrast the cold spot indicate the areas were 90% (or more) of the single family units pay Tow values. The high and low values are calculated by using the value of total value of the house and comparing it to the rest of the values. The areas that are in white indicate that there is a high variability between the property values.
The a great portion of the distribution of properties of high value overlaps (as it was expected) with the Hills and the VHFHSZ. Although, not all the Hills indicate the presence of high values, the southern portion of the Hills is designed to not significant, and small part (west of the Hills, next to Piedmont) present high value properties. An
54


interesting result is the middle portion (white), this area does not contain hot/cold spot, which indicates that there is a high variability in the data (i.e great variation within the property values).
To account for the already established social and economic dynamics of the city, I considered the median home value based on city tracts. A census tract is a geographic unit that groups people (between 1200 and 8000 people) of similar economic and social status used as a constant statistical subdivision of a metropolitan area. In order take in consideration the high variability of property values based on the location (i.e. the average cost of a house in the hills is $900,000 and in the Flatland is $400,000), I compared the census tract median home value to the total value of each single family units (Figure 4.8).
The resulting values indicated, the percentage from which the properties were under value based on tracts median home value. Different from what it was expected, the Hills presented property values closer to the tract median home value. Different from what it was expected, the Hills presented property values closer to the tract median home value. In contrast, the Flatlands indicated that there are a greater number of properties that are far away from the tract median home value. However, the map does not indicate the number of houses paying below the median home value, but shows the percentage difference of the houses paying below the median home value. This said, the distribution of percentages can be the result of high variability in prices in the Non VHFHSZ.
55


Figure 4. 8 Map of the distribution of the comparison between values for the Oaklands single family units. This map in percentages the comparison between the property value and the tract median home value. The higher the percentage the more difference between the property value and the median home value. This map indicates that in the Hills all of the property values are closer to the tract median home value. In contrast, the Flatlands indicates that there is greater number of properties that are farther away from the tract median home value. This map does not indicates the number of houses paying below the median home value, it shows the percentage difference, of houses paying below are paying a higher percentage than the Hills.
Part 2, Year of the Property Reassessment Value
Using the reassessed year value we can see when houses were bought in the VHFHSZ and Non-VHFHSZ. The information about year of purchase for Oakland is
56


summarized in Table 4.5 and it indicates the following. First, since 2010, 30% of the houses in VHFHSZ and 28% in the Non-VHFHSZ were bought or reassessed in value. Second, from 2000 to 2013, 74 % of the houses in Oakland were reassessed in value to bring it up to date. Third, since 2000, one quarter of all of the properties in Oakland were bought in the VHFHSZ and the rest in the Non-VHFHSZ, which makes sense since 25% of the single family residential parcels are located in the VHFHSZ. Fourth, there is a slightly higher percentage of houses that were bought between 1960 and 1980 in Non-VHFHSZ. Finally, based on the number of single family residential parcels, there is no
real difference between the houses bought in the VHFHSZ and the Non-VHFHSZ.
Table 4.3 Distribution of property last date of purchase or reassessed value based on year and location (VHFHSZ and Non-VHFHSZ).
VHFHSZ Nun VHFHSZ
Year Number of Units Percentage based on the VHFHSZ/ Nun VHFHSZ Total Percentage Number of Units Percentage based on the VHFHSZ Non VHFHSZ Total Percentage Total
I95W 33 33 0 4 66 67 0 6
I9MT nn 1071 0 642 *9 29 i 719
I9W 402 19 65 J 1.644 *0 35 3 2.046
I9S4V 724 19.72 5 2.94* *02* 6 3j672
I9W 2.720 23 55 17 7,926 74 45 16 10,646
:ooir 7.311 23 95 46 23.209 76 05 46 30.520
2oi Total | SfrSSS 66.561
The distribution of property values based on the year the property was last bought or reassessed and its location help illustrated a more complete picture of the home values (Figure 4.6). The graph indicates, first, that the mean in the VHFHSZ is significantly higher than the mean in the Non-VHFHSZ area. Second, there is a weak relationship between the cost of the property and the year the house was bought and this is indicated
57


by the low R-squared value. The reason behind this is that values are clustered to the upper left comer of the graph, indicating that we are not seeing a correlation so much as a bounding or limiting effect of year of property value adjustment. In conclusion, the year a house was bought does not linearly determine the value of that house today, but it certainly limits the maximum value that house will have. The more recently a house was reassessed in value, the higher the maximum price of that house, so basically newer houses can be a lot more valuable and generate more tax revenue that houses that were bought many years ago.
Dhlribulion of Property laves in Oakland, CA Based on the Year the Property wan Purchaed for Owner occupied units
100,000
Year l.ocalioa
Figure 4.6 Box-and-whiskers plot of the distribution of Single Family Residential Parcels Residential Parcels property taxes in Oakland, C A based on the year the property was purchased.
Using the information provided in the last year of reassessment of the property, I
mapped the geographic distribution of the properties. The results show an even distribution throughout the city, with no clear concentrations (or hot spots). Give large
58


size of the dataset, the end result did not create a intuitively clear distribution which is
why the map was not included in the results.
In order to see is there was an statistical significant between the two samples (or not), I used an unpaired (two sample) t-Test to take in consideration the difference in sample size. The t-test aimed to compared the price of the houses bought in the last 10 years (2003 to 2013) to the ones bought before (1950 to 2002) in the VHFHSZ and the NonVHFHSZ. The results indicated that there was no significant difference between new houses bought in the VHFHSZ (Al) and the NonVHFHSZ (A2), also, that there was no significant difference between older houses bought in the VHFHSZ (Bl) and the NonVHFHSZ (B2).
Table 4.4 Descriptive statistics for the VHFHSZ and Non-VHFHSZ based on the date of purchase / reassessed in value (new- reassess in value during the last 10 years ; old -reassessed in value more than 10 years ago).
Type Mean Count ST
Al VHFHSZ /New 518,894 10,384 359,644
A2 NonVHFHSZ / New 249,759 32,514 240,746
Bl VHFHSZ / Old 340,164 5,293 260,945
B2 NonVHFHSZ / Old 165,182 17,347 158,604
The properties bought in the last 10 years in the VHFHSZ and the NonVHFHSZ present not significant difference between the two, using a width of the Confidence interval of 95% (z) and the resulting confidence interval was 1.96 for both t-test. The results for the confidence interval were same for the houses purchased in the last 10 years in the VHFHSZ and the NonVHFHSZ, which means that the difference between the two was not significant. The test also indicated that the value of t-difference for the houses
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bought in the last 10 years was 71.324 and slightly lower (46.249) for for the houses bought more than 10 years ago.
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CHAPTERV
DISCUSSION
Introduction
The key working hypothesis of this thesis is that the development of cities in Alameda County particularly in Oakland appears to have served as a tool to increase tax revenue, a process that potentially allowed certain segments of the population to benefit more than others from the system. To test the hypothesis, the analysis was divided into two parts:
1. How do the VHFHSZ and Non-VHFHSZ differ in terms of how much tax revenue they generate in the various incorporated cities in Alameda County and in particular in Oakland?
2. How has Proposition 13 affected Oakland's capacity to collect money from property taxes in the VHFHSZ and Non-VHFHSZ?
Key Findings
This section summarizes important findings from a detailed analysis of a dataset from Alameda Countys Secured Roll Assessor for FY2012/2013. Comprising almost half a million records, this dataset contains information on location, property value and land use type, among other things. Using ArcGIS, I was able to spatially reference the location of houses and whether or not they are located in the VHFRSZ and/or the WUI. It also allowed me to visually map out the spatial distribution of Single Family Residence
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Parcels within the city. The following are the key conclusions reached as a result of this methodology:
1. The Fire Hazard Severity Zone is a designation to identify areas susceptible to fire for the State Responsibility Areas (SRA). These hazards zones are assigned to one of three levels: moderate, high, and very high. CalFire has encouraged local agencies (i.e., cities) to incorporate these designations in their hazard prevention planning, especially the VHFHSZ. This area is defined by a complex model that takes in consideration vegetation, topography, weather, crown fire potential and ember production and movement (CalFire, 2015). Given that the VHFHSZ was created to measure the potential and likelihood of an area burning, this designation indicates an areas vulnerably to fire which explains why the analysis presented here used the VHFHSZ/Non-VHFHSZ distinction.
2. Residential parcels represent the vast majority of parcels in Alameda County, and about one quarter of them are located in Oakland. The amount of tax collected varies based on the number of parcels within a given city and their total area. For FY 2012/2013, the average tax per Single Family Residential Parcel (mean) was highly variable, ranging from a low of $2,403 in Emeryville to a high $ 9,482 in Piedmont, with Oakland falling between these extremes with a mean tax of $3,766. This wide spread also characterizes the dispersion of tax amount from the mean (i.e., SD). The standard deviation on the mean tax for all of Alameda County is largest in Oakland (SD = $3,848).
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3. In Oakland, 25% of Single Family Residential Parcels are located in the VHFHSZ, a broadly comparable figure to the 28% of the city that is located in the VHFHSZ. In contrast, 40 % ($104 Millions) of the property taxes in the city are paid by people who live in the VHFHSZ and the remaining 60 % ($153 millions) by the people that live in the Non-VHFHSZ areas. That said, in FY2012/2013, the mean payed in property taxes by the single family homes was $ 5997 in the VHFHSZ and $ 3006 in the Non-VHFHSZ. For the other concerned cities, the proportions are as follows: Berkeley,
20 % of the single family residential parcels in the VHFHSZ pay 25% of the tax; Piedmont, 8% pay 10% of the tax; Pleasanton, 2% pay 4% of the tax; and San Leandro, 3% pay 4% of the tax. These data are important because they show that, across the board, people who live in the VHFHSZ actually contribute more to the city budget than those who dont. A follow-up question that emerges from this observation, however, is whether Proposition 13 has allowed them to contribute as much as they can or should, or whether their tax contribution is somehow constrained by artificially low house prices.
4. The distribution of property values in Alameda is conditioned by the location of parcels and their year of purchase. In general, properties located in the VHFHSZ are more expensive than those located in the Non-VHFHSZ. At the same time, political circumstances like Proposition 13 have led more recent homebuyers to pay more in property taxes than older homeowners. These circumstances have directly affected the assessed value of houses in Oakland and in Alameda County, helping to perpetuate dynamics created by the division of the city between the Hills and the Flatlands which are further compounded over time, since the longer homeowners occupies their property, the
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less they will pay in property tax because the assessed value of the property will not have kept up with assessed value. These situation resulted in the residents of the Flatlands of Oakland to pay higher property tax rates relative to their income.
Policy Implications
Based on the results generated from the research of my thesis, this next section seeks to critically address a series of issues related to the topic of this research. The main goal is to contribute to the growing body of research focused on fire vulnerability in the area and to influence future discussions about hazard vulnerability.
Vulnerability, a Dynamic Concept
For the purpose of this thesis vulnerability refers to the hazard exposure based on the geographical location. Vulnerability in this thesis refers to the hazard exposure based on the geographical location. In the case of Oakland, according to CalFire, the area most vulnerable to fires is the VHFHSZ, located mainly in the eastern portion of the city along the Hills. For the purpose of this thesis, vulnerability to wildfires (metric) is defined by the structures exposed to fire and to a lesser extent the adaptive capacity of people that live/work in these structures.
The concept of vulnerability is dynamic and encompasses multiples meanings based on the predisposition of a system and the capacity to adapt in the face of a hazardous event. This thesis defined vulnerability to hazards based on the level of exposure (geographical location), however, identifying vulnerable populations exposed to hazards it is not as clear cut as would first appears In the case of Oakland, socially
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marginalized communities are not located in the areas most exposed to fires, in fact the areas vulnerable to fire are occupied by the wealthiest members of the community. As a result, Oakland comprises two parallel societies that differ in social, economic and environmental characteristics, where one is exposed to hazard and the other is not.
For this reason, it is important to take in consideration how the concept of vulnerability to hazards can manifests itself in different contexts and it can differentially affect distinct groups within a population. Social vulnerability is the set of characteristics and circumstances of a community or a system that makes it susceptible to the damaging effects of a hazard (United Nation, 2009). In the case of Oakland, it is easy to assume that the people who live in fire-prone areas, that is, those whose houses and property will be destroyed and who might possibly lose their lives, are the only victims of the fire. However, this perspective overlooks other group who can be also affected by the fire even though they reside outside the hazardous area. In the case of Oakland, for instance, people in the Hills who live within the perimeter of the high fire risk area belong to very affluent communities and generally have health and property insurance and can apply the relief aid given by the government to recover from fires. In contrast, people in the Flatlands, compared to hill residents, provide a greater proportion of their income spent on property taxes (compared to the VHFHSZ). Thus, even though people living in the Flatlands may not have been affected directly by the fire burning the house, their capacity for resilience was affected by a portion of these revenues go to pay for fire protection, which is not something that flatland residents benefit from. This is unfair because many
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of the residents of the Flatlands are least able to afford higher tax rates, whereas more hill residents could probably afford slightly higher rates.
Oaklands polarized population creates a dilemma on how to deal with other instances of social vulnerability to hazards. On the one hand, we have the people who live directly in the area affected by the hazard but have the economic resources and means to ultimately reduce their vulnerability while. On the other, there is a marginalized population that lives in areas less exposed to fires but also is less resilient to even minor problems like having to pay relatively higher property tax rates when compared to household income.
The Limit that Guides Urban Sprawl
The results indicated that the VHFHSZ generate a lot of money for cities through tax revenues. Together, the homes located in the VHFHSZ pay more in property taxes than other Non-VHFHSZ residents. In Oakland, 25% of single family residential parcels are located in the VHFHSZ, but these units are responsible for providing 40% of the property taxes in the area. Based on this numbers alone, it proves that the idea to expand the urban perimeter to increment the amount in property taxes worked for Oakland. However, to justify urban sprawl as a way to get more revenue through property taxes poses multiple problems, however. First, urban development relies on the local governments to provide public services from the taxes collected from these new developments, but often the real cost of providing public services (e.g. municipal services like police, water, streets, sanitation, public libraries), it is not covered fully by
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the taxes gathered (EPA, 2014; Brueckner, 2000; Burchell, et al., 2005).The idea that it is possible to collect more money thought property taxes to increase city budgets by developing new areas does not take into consideration the real cost of maintaining these new areas. Therefore, if the cost of maintenance of an area exceeds the revenue generated by the area, it defeats the purpose of building it up in the first place. The idea that land development occurs to boost city budgets to pay for city 'activities' (i.e. police, fire department) contradicts itself when the final cost of development increases when maintaining these areas is more costly (e.g. how can we justify building in areas that are vulnerable, when the cost of maintenance of these areas due to their vulnerability is much higher compared to the rest of the city?).
Effective Tax System
Finally, there is a need to define what constitutes a fair and appropriate taxation system. In the case of Oakland, the city effectively comprises two parallel societies that differ in their social, economic and political make-ups. As mention before, the Hills are exposed to fire and the Flatland is not and the Hills provide a larger contribution to property taxes (median home property tax is $5997) than the Flatlands ($3006 median). In order to provide a fair an efficient tax system, however, we need to take in consideration the high variation (e.g. between the Hills and the Flatlands) in Oakland for assessed property values. In addition, it is crucial to ensure that each unit located in the VHFHSZ and the Non-VHFHSZ carries their own weight to ensure their accountability (LAO, 2002). Finally, the cost of public services should be distributed equally; in this
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case, since fire defense is a significant portion of the citys budget, property taxes need to reflect the cost to fire protection for areas that are vulnerable.
Future Research
Future research should aim to calculate the potential amount in property tax that could be collected if all property values were up-to-date with the present-day market value of given properties. One way this could be done with the available data is by using the year of reassessment to create a backward calculation of the inflation rates. Other lines of future research also include calculating property assessed values datasets from various years in order to track those changes over the years.
The WUI is not the best geographical indicator for measuring or assessing fire vulnerable areas. To date, much of the literature on fire vulnerability has equated the WUI with location for greater risk. The WUI is the area where were the urbanization expands into the intermingled and undeveloped wildland (Radeloff et al., 2005). However, it also encompasses various ecosystems like wetlands, grasslands and woodlands, not all of which are vulnerable to fire in the same way. Given that the WUI covers a large range of habitats and ecosystems, it is not the most precise manner of identifying vulnerable areas, which explains why it was not used in this thesis. To argue that because an area is WUI, it is therefore vulnerable (or should require analysis of vulnerability) takes focus away from the areas that are truly at high risk. Furthermore, to create rules (like building codes) for zones that are not WUI might be counterproductive since the WUI is highly variable
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ecologically, being defined first and foremost by the fact that it surrounds the periphery of a city.
Limitations of the Study
One of the limitations of the study was the lack of information in the dataset about the size of the properties and the number of homes within each parcel. These two data would have allowed me to develop a more complete picture of the structure of residential property tax. Finally, it would have been very useful to have comparable datasets from other years to calculate changes in property values, city budgets, and fire service budgets before and after the Tunnel Fire.
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REFERENCES
Alameda County, California (2012). Tax Rate For the Fiscal Year 2012/2013. Retrieved from : https://www.acgov.org/auditor/tax/2012-13%20TaxRateBook.pdf
Bankoff, G. (2006). The Tale of the Three Pigs: Taking Another Look at Vulnerability in the Light of the Indian Ocean Tsunami and Hurricane Katrina. Retrieved from: http:// understandingkatrina.ssrc.org/Bankoff/
Bankoff, G., Frerks, G., Hilhorst, D., (Eds.) (2004).Mapping Vulnerability: Disasters, Development, and People. Earthscan.
Batty, M. (2008). The Size, Scale, and Shape of Cities. Science. 319 (8) 796-771
Brueckner, J. K., Kim, H. (2003). Urban Sprawl and the Property Tax. International Tax and Public Finance Journal. 10(1): 5-23
Bryant, R., and S. Bailey. 1997. Third World Political Ecology. London: Routledge.
California Department of Forest and Fire Protection (CalFire). (2007). Fact Sheet: Californias Fire Hazard Severity Zones. Office of the State Fire Marshal. Retrived from: http://www.fire.ca.gov/fire_prevention/downloads/FHSZ_fact_sheet.pdf
California Department of Forest and Fire Protection (CalFire). (2011). CAL FIRE Jurisdiction Fires, Acres, Dollar Damage, and Structures Destroyed Retrived from: http:// www.fire.ca.gov/communications/downloads/fact_sheets/firestats.pdf
California Department of Forest and Fire Protection (CalFire). (2015a). Top 20 Largest California Wildfires. Retrieve from: www.fire.ca.gov/communications/downloads/ fact_sheets/Top20_Acres.pdf
California Department of Forest and Fire Protection (CalFire). (2015b). Top 20 Most Damaging California Wildfires. Retrieve from: http://www.fire.ca.gov/communications/ downloads/fact_sheets/Top20_Damaging.pdf
California Department of Forest and Fire Protection (CalFire). (2015c).Top 20 Deadliest California Wildfires. Retrieve from: http://calfire.ca.gov/communications/downloads/ fact_sheets/Top20_Deadliest.pdf
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California Department of Forest and Fire Protection (CalFire). (2015d) Fire Hazard Severity Zones Maps. Retrieved from: http://www.fire.ca.gov/fire_prevention/ fire_preventi onwil dl andzone s
City of Oakland California (2009) FY 2011-13 Adopted Policy Budget. Retrieved from: http://www2.oaklandnet.eom/Government/o/CityAdministration/d/BudgetOffice/
Collins, T., 2005. Households, forests, and fire hazard vulnerability in the American West: a case study of a California community. Global Environment Change B: Environmental Hazards 6(1) 23-37.
Collins, T., 2008. The political ecology of hazard vulnerability: marginalization, facilitation and the production of differential risk to urban wildfires in Arizonas white mountains. Journal Political Ecology 15, 21-43.
Dooling, S. and Simon, G. L. (2012). Cities, Nature and Development: The Politics and Production of Urban Vulnerabilities. Ashgate Publishing, Aldershot, UK.
East Bay Regional Park District (n.d.). Fire History in the East Bay. Retrieved from: http://www.ebparks.org/Assets/_Nav_Categories/About_Us/Fire/History+All+Fires.pdf
Federal Emergency Management Agency (FEMA). 1992. The East Bay Hills Fire Oakland-Berkeley, California. U.S. Fire Administration/Technical Report Series USFA-TR-060.
Frenkel, A., Ashkenazi, M. (2008).Measuring urban sprawl: how can we deal with it?
Environment and Planning B: Planning and Design. 35: 56-79
Hohle, R. (2015). Race and the Origins of the American Neoliberalism. Taylor and Francis Publisher.
Insurance Information Institute. (2014). Wildfires. Retrieve from: http://www.iii.org/fact-statistic/wildfires
International Association of Willand Fire (IAWF). (2013). WUI Facr Sheet. Retrieved from http://www.iawfonline.org/pdf/WUI_Fact_Sheet_08012013.pdf
Legislative Analyst Office (LAO). (2012). Understanding Californias Property Taxes. Retrieved from: http://www.lao.ca.gov/reports/2012/tax/property-tax-primer-l 12912.pdf
Liverman, D.M. (1990). Drought impacts in Mexico: climate, agriculture, technology, and land tenure in Sonora and Puebla. Annals of the Association of American Geographers 80 (1) 49-72.
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National Fire Protection Association (NFPA).(2015). Home Structure Fires. Retrived from: www.nfpa.org/~/media/Files/Research/NFPA%20reports/.../oshomes.pdf
Nechyba, T. J., Walsh, R.P (2004). Urban Sprawl. Journal of Economic Perspectives 18(4): 177-200
Radeloff, V. C., Hammer, R. B., Stewart, S. F, Fried, J. S., Holcomb, S. S., And Mckeefry, J. F., (2005). The Wildland-Urban Interface In The United States. Journal Ecological Applications, 15(3), 2005, pp. 799-805
Robbins, P. (2002). Obstacles to a First World political ecology? Looking near without looking up. Environment and Planning A 34(8): 1509-1513.
Robbins, P. (2004). Political Ecology: A Critical Introduction. Malden, MA: Blackwell Publishing.
Simon, G. L. and Dooling, S. (2013). Flame and Fortune in California: The material and political dimensions of vulnerability. Global Environmental Change-Human and Policy Dimensions 23(6): 1410-1423.
Simon, G. L. (2014). Vulnerability-in-Production: A Spatial History of Nature, Affluence, and Fire in Oakland, California. Annals of the Association of American Geographers 104(6): 1199-1221.
Sullivan, S and Stott, P (2000) Political Ecology: science, myth and power. Arnold Publication, London.
Theobald, D. M. (2005). Landscape Patterns of Exurban Growth in the USA from 1980 to 2020. Journal Ecology and Society. 10(1): 32
Thomas, D. S. K., Phillips, B. D., Lovekamp, W. E., Fothergill, A. (2013). Social Vulnerability to Disasters, Second Edition. CRC Press
US Census (n.d.). Quick Facts: Oakland City, California. Retrived from: http:// www.census.gov/quickfacts/table/PST045215/0653000,00
Watts, M. (2000). Political Ecology. In Sheppard, E. and T. Barnes (eds.), A Companion to Economic Geography. Blackwell. Blackwell Publishing
Wisner, B., Blaikie, P, Cannon, T., Davis, 1.(2004). At Risk: Natural Hazards, Peoples Vulnerability and Disasters, 2nd ed. Routledge, London.
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APPENDIX A
Property Assessment Information

Code Description
00 999 Exempt, Not Assessed by County, Mobile Homes and Tracts
1000 1999 Single Family Residential
2000 2999 Multiple Residential, 2-4 Units and Mobile Homes
3000 3999 Coimnercial (See also 8X & 9X Series)
4000 4999 Industrial
5000 5999 Rural
6000 6999 Institutional
7000 7999 Multiple Residential, 5 or more units
8000 8999 Improved Coimnercial
9000 9999 Improved Coimnercial


Descri ption of Single Family Categories
1000 Vacant residential land, zoned 4 units or less
1040 Vacant residential land, R&T 402.1
1100 Single
1101 Medical-Residential
1120 Residential
1130 Residential
1140 Single family residential home, R&T 402.1
1150 Historical
1190 Single
1200 Single
1300 Single
1400 Single
1420 Single Family Res Duet Style, First Sale
1430 Single Family Res Duet Style, R&T 402.1, First Sale
1440 Single Family Res Duet Style, R&T 402.1
1500 Townhouse
1505 Townhouse
1520 Townhouse Planned Development, First Sale
1525 Single Family Townhouse Style Condominium, First Sale
1530 Residential Townhouse Planned Development, R&T 402.1, First Sale
1535 Townhouse Style Condominium, R&T 402.1, First Sale
1540 Townhouse Planned Development, R&T 402.1
1545 Townhouse
1590 Townhouse Planned Development, Coimnon Area or use
1595 Townhouse Style Condominium, Coimnon Area or use
1600 SFR
1620 SFR Detached Site Condominium, First Sale
1630 SFR Detached Site Condominium, R&T 402.1, First Sale
1640 SFR Detached Site Condominium, R&T 402.1
1690 SFR Detached Site Condominium, Common Area or use
1700 Single
1800 SFR
1820 SFR Planned Development Tract, First Sale
1830 SFR Planned Development Tract, R&T 402.1, First Sale
1840 SFR Planned Development Tract, R&T 402.1
1890 SFR Planned Development Tract, Coimnon Area or use
1900 Single
1901 Single
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APPENDIX B
City Primary I RA Secondary TRA Tax Rate
Alameda Island 21 0, 2-7, 1.1409
1 1.2240
Albany 22 0, 1 1.3814
Berkeley 13 0-5 1.2472
26 0-18, 20-23, 25-31, 33-43 ,401, 700 1.1534
Dublin 19 1.1237
24 1.1148
32 1.1483
Emeryville 14 0, 1,3, 4, 6 1.1259
2, 5 1.1980
12 1-4, 6-24, 28-53, 55, 56, 58-62, 64-68, 70-73, 75, 77, 78, 80 -84, 86, 89-92, 94-115, 117-144, 146-165, 167-196, 198-204, 206-213, 206-213, 215-217, 220-229, 231-247, 480 1.1241
5, 54, 57, 63, 69, 74, 79, 85, 87, 88, 93, 116, 197, 205,214,219, 230 1.1172
Fremont 25, 26, 27, 219 1.1076
76 1.1400
145 1.1255
166 1.1027
800, 812, 873 1.0897
25 0, 4, 5, 7, 11-15, 20, 21, 34, 48, 64, 73, 97-99, 102, 103, 116, 117, 121, 122, 124, 149, 150, 169, 172, 197, 202, 214-216, 236, 1.1423
1-3, 6, 8-10, 16-19, 22-30, 32, 33, 35, 36, 42-47, 50-56, 60-63, 65-70, 74, 75, 77, 84, 86, 87, 95, 96, 101, 104, 107, 109, 110, 112, 113, 114, 118, 125, 126, 128-148, 155-163, 165-168, 170, 171, 173-196, 198-201, 203-208, 211-213, 217-224, 226-230, 232-235, 237-240, 402, 426, 430, 477 1.0866
31, 37, 39, 49, 59, 85, 92, 93, 225, 231 1.1879
38, 83 1.1698
40, 89, 91, 94, 111 1.1948
Hayward 41, 76, 80, 81, 127 1.0935
57, 58, 78, 209, 210 1.1047
71, 72 1.1276
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79 1.1116
82, 119, 120 1.1504
88, 90, 151, 152, 164 1.1237
100 1.1465
105, 106, 108 1.0935
115 1.1646
123 1.1492
153, 154 1.1418
Livermore 16 0-42, 44-51, 53-69, 71-77, 81, 82, 84-86, 88-94, 96-99, 401, 464, 700 1.1097
43, 52, 70, 78, 80, 83, 87, 95 1.1148
79 1.1504
Newark 11 1-50 1.2026
Oakland 17 1, 11-14, 16, 19-22, 24-27, 30-33, 36-38, 41-47, 401 1.4057
5, 17-18, 34,35 1.3475
6, 7 1.3500
8, 28 1.3226
9 1.2943
10, 15 1.3543
23 1.3382
29 1.4079
39, 40 1.3314
Piedmont 18 0 1.2125
Pleasanton 19 0-14, 17-19, 22, 23, 25, 28, 29, 31-66, 75-101, 105-107, 109-121, 126, 400, 700, 731, 1.1504
15, 16, 20, 24, 26, 27, 30, 67-74, 122, 123 1.1534
103 1.0980
108, 124, 125 1.1148
804 1.0826
San Leandro 10 1-5, 7-10, 12-16, 18-20, 22, 24-26, 30, 32-36, 38-42, 45, 48, 50, 54, 57, 61-64, 66-68, 73, 74-75, 77-81, 83-85, 88, 90-100 1.1398
6, 11, 17, 21, 23, 27, 28, 31, 37, 43, 49, 53, 60, 65, 71, 72, 76, 82, 86, 87, 89 1.1423
29 1.1466
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15 1. 2, 4, 6-9, 11-13, 15, 16, 18-22, 24, 26, 28, 30-32, 34-36, 38, 41, 42, 45-48, 50, 51, 53, 60, 61, 63-65, 67, 69-79, 81-83, 86, 88-91, 97, 463, 1.1948
3, 5, 10, 14, 25, 29, 33, 39, 44, 52, 54-58, 84, 85, 87, 93-96 1.2113
Union City 17, 37, 49, 80, 1.0935
23, 43, 59, 62, 68, 462 1.1879
27 1.2107
40 1.1147
66 1.0866
800, 821 1.1604
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Full Text

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A SPATIAL ANALYSIS OF PROPERTY TAX REVENUE AND FIRE VULNERABILITY IN OAKLAND, CALIFORNIA by ALEJANDRA URIBE ALBORNOZ B.A. Arizona State University, 2007 A thesis submitted to the Faculty of the Graduate School of the University of Colorado Denver in partial fulfillment of the requirements for the degree of Master of Science Environmental Science 2016

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2016 ALEJANDRA URIBE ALBORNOZ ALL RIGHT RESERVED ii

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This thesis for the Master of Science degree by Alejandra Uribe Albornoz has been approved for the Environmental Science Program by Gregory Simon, Chair Deborah Thomas Rafael Moreno December 17, 2016 iii

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Uribe Albornoz, Alejandra (M.S., Environmental Science) The Geography of Inequality and the Fear of Fire Thesis directed by Associate Professor Gregory Simon ABSTRACT In 1991 the Oakland Hills firestorm burned the hillsides of northern Oakland and south-east Berkeley, in northern California. To this day, this fire remains the most damaging wildfire in California's history and the second deadliest in the state. Fires like the Oakland firestorm are a result of the urbanization processes guided by economic and social factors into fire vulnerable areas (like the Very High Fire Hazard Severity Zone VHFHSZ). This thesis is an spatial analysis of property tax revenue and fire vulnerability, in particular exam ines how the urban development in Alameda County resulting for the cities' desire to increase property taxes potentially contributed to the production of vulnerability to fire within the area. In particular, how the VHFHSZ and Non-VHFHSZ differ, in terms of property tax rev enue generated, across the various incorporated cities in Alameda County, in particular Oak land and the impact of Proposition 13 on Oakland's capacity to collect money from property taxes in the VHFHSZ and Non-VHFHSZ. The data set used for this research is the "Assessor Secured Roll Financial Year 2012/2013" from the Alameda County Assessors Office. This data set contains information about the location and price (among other things) of about half a million parcels in Alameda C ounty. The research combines two element for the theoretical framework to discuss the re search questions and the result. First the political ecology ecology perspective is used to un iv

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derstand how vulnerability to hazards could have been produced by the pursuit of cities to increased tax revenue. Second, the concept of the production of vulnerability is used to de scribe areas more exposed to wildfires, based on economic, social and environmental factors. Furthermore, the continuous production of fire vulnerability in Oakland results from the joint influence of both decision-making and city planning. The research concludes with the policy implications and recommendations based on the results generated. The form and content of this abstract are approved I recommend its publication Approved: Gregory Simon v

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DEDICATION I would like to dedicate this thesis to my husband Julien Riel-Salvatore for all of his unconditional love and support, I would have not been able to follow this dream without him. I will also like to thank my parents for passing on to me their love for nature and academia. I finally want to mention my two sons Mateo and Sebastian who make me want to be the best person I can be. vi

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ACKNOWLEDGEMENTS I would like to thank my advisor Gregory Simon for all his guidance and patience, and for providing me the opportunity work with him during a research assistant at Stanford.. I also want to thank Deborah Thomas for all of her knowledge and pushing me to be the best I can be. Thank you also to Rafael Moreno for all of his classes and continuous long-distance support while working on completing my masters and thesis from abroad. Finally, I want to thank to the people at The Center for Spatial and Textual Analysis (CESTA) at Stanford for giving me the opportunity to work with you and learn many new things. vii

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TABLE OF CONTENTS CHAPTER I. INTRODUCTION .... 1 Background of the Problem .. 1 History of Fires in the Area 1 California 3 Alameda County and Fire Vulnerability 3 Oakland' History of Development 4 The Geography of Alameda County and Oakland 5 The Fire Hazard Severity Zones ... 9 Economic Responsibility for for Fire Management .. 1 0 Fire Mitigation Activities .. 13 Statement of the Problem .. 14 Research Question 15 Format of the Study ... 16 Significance of the Study ... 16 Definitions of Terms .. 17 Proposition 13 1 7 Risk 18 Very High Fire Hazard Severity Zone ... 18 Vulnerability .. 18 WildlandUrban Interface ..... 19 viii

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II. THEORY AND LITERATURE REVIEW ... 20 Framework I: Political Ecology 20 Introduction 20 The Political Ecology of Hazards .. 21 The Elements that Shape Hazards .. 22 Proposition 13 23 Urban Sprawl 2 4 Oakland Property Values and Taxes .. 25 Framework II: The Concept of Vulnerability and its Production .. 27 Summary 29 III. METHODS 31 Introduction 31 Research Design 31 Data Data Processing and Analysis ... 3 5 Question 1 35 Question 2 39 Property Values 39 Year of the Property Reassessment 40 IV. RESULTS 42 ix

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Question 1 .. 42 Part 1: Alameda County 43 Part 2: The VHFHSZ and the WUI in Alameda 46 Part 3: The VHFHSZ and the Non-VHFHSZ .. 50 Question 2 52 Part 1: Property Value 53 Part 2. Year of the Property Reassessment Value .. 56 V. DISCUSSION Introduction 61 Key Findings .. 61 Policy Implications 64 Vulnerability, a Dynamic Concept 64 The Limit that Guides Urban Sprawl 66 Effective Tax System 67 Future Research 68 Limitations of the Study 69 REFERENCES .. 70 APPENDIX 73 x

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LIST OF TABLES TABLE 1.1 Oakland's breakdown of revenues by fund for the Fire Service Agency for FY2012-2013. 12 3.1 List of GIS layers used 34 3.2 List of layers created including a description of each. .... 38 4.1: Total property taxes collected 2013 in each of the incorporated cities of Alameda Count y. 44 4.2: Total property taxes collected 2013 within the VHFHSZ in each of the incorporated cities of Alameda County. 51 4.3 Distribution of property last date of purchase or reassessed value based on year and location (VHFHSZ and Non-VHFHSZ). .. 57 4.4 Descriptive statistics for the VHFHSZ and Non-VHFHSZ based on the date of purchase / reassessed in value .. 59 xi

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LIST OF FIGURES FIGURE 1.1 Representation of the history of wildfires in California by year 2 1.2 Location and distribution of fires in Alameda County based on the decade it happened 4 1.3 Map of Alameda county's incorporated cities 6 1.4 Map of Oakland tract median home value .. 8 1.5 Illustration of the division between countyand city-level budgets 12 4.1. The citywide level scatter plot of Single Family Residential Parcels by the total tax .. .. 45 4.2 Map of the distribution of the Very High Fire Hazard Severity Zone (VHFHSZ) in Alameda County 47 4. 3 Map of the distribution of the Wildland -Urban Interface (WUI) in Alameda county, California ..48 4.4. The WUI level scatter plot of Single Family Residential Parcels by the total taxes 49 4.5 The VHFHSZ level scatter plot of Single Family Residential Parcels by the total tax 49 4.6 Box-and-whiskers plot of the distribution of the property taxes for the Single Family Residential Parcels in Oakland based on location of the property .. 52 4.7 Map of distribution of Oakland's single family units based on the Assessed xii

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value of the home 54 4.8 Map of the distribution of the comparison between values for the Oakland's single family units 56 4.9 Box-and-whiskers plot of the distribution of Single Family Residential Parcels Residential Parcels property taxes in Oakland, CA based on the year the property was purchased .. 58 xiii

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LIST OF ABBREVIATIONS CALFIRE California Department of Forest and Fire Protection FY Financial Year HZSZ Fire Hazard Severity Zone SRA State Responsible Area VHFHSZ Very High Fire Hazard Severity Zone WUI Wildland Urban Interface xiv

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CHAPTER I INTRODUCTION In 1991 the Oakland Hills firestorm (aka, the Tunnel Fire) burned the hillsides of northern Oakland and south-east Berkeley, in northern California. To this day, this fire remains the most damaging wildfire in California's history and the second deadliest in the state: it burned 1600 acres, destroyed 2900 structures, killed 25 people and seriously injured another 150 people. The Oakland Hills firestorm adds to a growing list of wildfires located in the Wildland-Urban Interface (WUI) and the Very High Risk Hazard Severity Zone (VHFHSZ). This outcome is the result of an urbanization processes in the area that has been driven by economic and social factors that ultimately increased its inhabitants' vulnerability to wildfires. This thesis examines how the growth of cities located in the VHFHSZ in Alameda County particularly in Oakland has contributed to the production of fire vulnerability in the area, and especially how development guided by economic incentives to increase property taxes ultimately contributed to its increased fire vulnerability. In addition, it examines how political circumstances like Proposition 13 have contributed to Oakland's vulnerability to wildfires and enabled certain groups within the population to benefit disproportionately from the property tax revenue collected. Background of the Problem History of Fires in the Area California A portion of Californian's history has been written by the wildfires that have 1

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shaped the state. Even though fires are part of natural disturbance regimens for California's ecosystems, these historical patterns have been disturbed by the interactions that humans have with their environment, especially over the last few hundred years. Today, this relationship between humans and their environment has led to an intensification of the problem and made wildfires a major threat to the residents of California. In fact, CalFire statistics for the past 83 years show that 70% of the largest wildfires in California happened only in the last 20 years (CalFire, 2015). Interestingly, while the destructiveness of wildfires has increased over the years, the number of wildfires itself has decreased and the amount of acres burned per fire that displays a fluctuating trend (Figure 1.1). Figure 1.1. Representation of the history of wildfires in California by year, the number of acres burned. The left y-axis measures total acres burned and the right y-axis measures the total number of fires. As can be observed, there is no clear trend between the number of acres burned and the number of fires. The data used in this graph indicates only the fires that happened in the SRA and it does not includes any local data (i.e. the statistics from the incorporated cities). (CalFire, 2011). Over the same period, California's population has increased sevenfold, creating an ever growing demand for housing across the state. Unsurprisingly, largely because 2

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growing numbers of people settling in the state has translated into a corresponding increase in the number of structures exposed to wildfires, 35% of the most damaging fires in state history have occurred in the last 15 years. Further, 30% of households in California today are at high or extreme risk of being affected by a wildfire and the state has the highest number of households (ca. 375,500) at high or extreme wildfire risk in the country (NFPA, 2015). In fact as of 2013, California ranked first in the nation in terms of the yearly number of fires and total amount acres burned. Unsurprisingly, as of today, seven of the ten most costly wildfires in US history took place in California. (Department of Interior, 2016.) Alameda County and Fire Vulnerability Alameda County is l ocated in the eastern portion of the San Francisco Bay area of California. In recent years, the county has experienced a growing number of fires due to a combination of compounding factors that include high winds, unusual droughts, complex terrain, excess of natural and man-made fuels, and poor urban design (FEMA 1991). The eastern part of the county (North and Sound) has borne the brunt of these fires, and the most damage has accrued in the East Bay Hills (East Bay Parks, 2015; see Figure 1.2). In fact, over the past 90 years, the hills have been the setting of 15 major fires, including the three most significant events after the Oakland Hills Firestorm, namely the Berkeley Fire (1993), the Fish Canyon Fire in Oakland (1970) and the Wild Cat Canyon Fire, also in Oakland (1980) (FEMA, 1991). All said, the Tunnel Fire of 1991 was in some ways just one more indicator of the area's vulnerability to wildfires as well as another piece of evidence that human factors contribute to producing this vulnerability. 3

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Figure 1.2 Indicates the location and distribution of fires in Alameda County based on the decade it happened. The rectangle at the right present a zoom in in the Oakland/ Berkeley area. Adapted from ( East Bay Regional Park District, n.d.). Oakland's History of Development To understand how Oakland's urban design has increased the city's vulnerability to wildfires over time, it is first important to understand the history of its urban sprawl. Urban sprawl is a well-studied phenomenon that describes the growth of low-density development in urban areas as a response to rapid increases in population ( Radeloff et al., 2005). It is characterized by high numbers of people moving from rural to urban areas and by extensive resulting developments occurring near or in the WUI (FEMA, 2002: see Figure 1.3). In the specific case of Oakland, urban sprawl took place in large part in the city's fire vulnerable hills, which are often both WUI and VHFHSZ areas. The development of Oakland's Hills begins in the 1850s, with the first logging activities in the area and the construction of the first railroads. Together, these activities combined to define the area that would be the target of future development (Simon, 4

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2014). The rapid increase of the city's population following the San Francisco Earthquake of 1906 saw the construction of large single-family homes, which were built to house upper class families in the Hills (FEMA, 1991); such houses would occupy a significant portion of the Hills by the 1920s. In the 1950s and 1960s, public and private investors seeking to attract new homeowners into the area financed the construction of new uppermiddle class residences and two major high-density developments along the slopes. By the 1970, two-story condominiums and townhouses followed and in 1991, when the Oakland Hills Firestorm took place, the Hills were already an established upscale neighborhood (Simon, 2014). In part, the large-scale development of the Oakland Hills between 1950s and 1970s was driven by the desire to increase the city's budget through the collection of property tax from its new residents.Unfortunately, around the same time, the Tax Revolt' movement was gaining momentum, a process that culminated with the passage of Proposition 13 in 1978, which would ultimately reduce how much tax could be collected by limiting the growth of house values (Simon, 2014). The Geography of Alameda County and Oakland The county of Alameda is located in California, in the eastern portion of the San Francisco Bay area. According to the U.S. Census Bureau (U.S.Census Bureau, 2015), the county covers a total of 821 square miles 739.02 square miles of land and 82 square miles of water. Alameda County is home to 1.5 million people, 90.6% of which live in 14 incorporated cities, and mainly in Oakland which holds the county's seat. The 14 incorporated cities are Alameda, Albany, Berkeley, Dublin, Emeryville, Fremont, 5

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Hayward, Livermore, Newark, Oakland, Piedmont, Pleasanton, San Leandro, and Union City (Figure 1.3). The county also houses six unincorporated communities Ashland, Castro Valley, Cherryland, Fairview, San Lorenzo, and Sunol. Figure 1.3 Map of Alameda county's incorporated cities. The unincorporated cities are not displayed in this map, the reason why is because these cities do not governed themselves but instead belong to the State Responsibility Areas. This thesis does not consider data from the unincorporated communities because their fire security services are managed by the county since they are located on the State's Responsibility Area (SRA). Alameda County is bordered by Contra Costa County to the north, San Joaquin and San Mateo Counties to the east, Stanislaus County to the southeast, and Santa Clara County to the south. Geographically, Alameda County is defined by a series of hills and ridges that run from north to south in its western portion and divides 6

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the county into two parts: the 32-mile long coastal plain and the Livermore-Amador Valley. The series of hills and ridges extends across many cities in the county, and they can be up to 12-mile wide and 1,500ft high, depending on the area. In the south-eastern portion of the county, next to the Livermore-Amador Valley, the Diablo Range begins, reaching elevations up to 3700ft. The city of Oakland is located in the northern portion of the county, next to San Francisco Bay. The city covers 78 square miles (55.8 square miles of land and 22.2 of water) and is home to 406,000 people, or about one quarter of the county's population, making it the eighth largest city in California (Census). The city is bordered by Berkeley to the north, San Leandro to the south, Emeryville to the north-west, Alameda across the estuary, and Piedmont, a small city within the northern portion of Oakland. Characterized by a Mediterranean climate, the city ranges in elevation from sea level to 1,900ft (Oakland Geology, 2010). Oakland's territory houses a variety of habitats, including 19 miles of coastline, smaller patches of wetland, large areas of grassland, oak woodlands, and hills. The city of Oakland is a vibrant urban community that comprises a myriad of cultures and ethnic groups that cross-cut socio-economic backgrounds. According to the U.S. Census, Oakland is home to 406,000 people, or about a quarter of Alameda County's total population of 1,510,271 according to the latest census figures. The city comprises 28% of the county's households and 60% of its housing units are occupied by renters (compared to 50% for the county). Oakland is also one of the most ethnically diverse cities in the country, with 27 % foreign-born inhabitants and 40 % of people speaking 7

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languages other than English at home. Today, Oakland's racial makeup is 28% African American, 26% white (non-Hispanic) 25% Latino, 17% Asian, and 4% other. However, these figures have changed dramatically over the past 60 years: In 1940, for instance, 95% of the population was white, a figure that had dropped to about 60% by 1970 and reached the low 30s in the 1990s (US Census). Equally important are the high levels of poverty that characterize Oakland: according to the 2010 census, 20.5% of Oakland residents live in poverty compared to 13% for Alameda County as a whole (Figure 1.4). Figure 1.4 Map of Oakland's tract median home value in 2013. This map indicates the distribution of the median home value in Oakland based on the census tract. The values are divided in four categories below 350k between 350k and 500k, 500k 750k and more than 750k. This categories where created based on division of the data in quartiles. 8

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The city of Oakland is divided in two main parts, the Hills and the Flatlands, each of which is characterized by distinct own social, economic and political make-ups (Simon 2014, Dooling and Simon 2012). The social changes just discussed have also varied by area, with the Hills having become inhabited mostly by white residents while the Flatlands became mostly non-white over the same period (Simon 2014). Likewise, average house prices are also closely tethered to location. In 1940, the average house cost $100,000 in the Hills and while $70,000 in the Flatlands; by 2010, these figures had reached $900,000 in the Hills and $400,000 in the Flatlands, that is to say, a nine-fold price increase in the Hills but less than a six-fold increase for the Flatlands (Simon 2014). Similarly, today the homeownership rate is lowest in the Flatlands where 25%-33% of the population also lives below the poverty line (McClintock 2011; Figure 1.4). The Fire Hazard Severity Zones The Fire Hazard Severity Zone is a designation created by California's Department of Forests and Fire (CalFire) to identify areas most susceptible to fire and influence the way people build in and protect them. This designation was created by measuring the physical conditions that makes an area susceptible to fires and modeling the likelihood that it will of catch fire in the next 30 to 50 years. That said, the FHSZ evaluates fire hazards and not fire risk, the latter being the potential damage that can be caused by a fire. The probability of an area catching fire is calculated by using the following "Fire Hazard Elements": a. vegetation (vegetation over a 30to 50-year time horizon); b. topography (up steep slopes); c. weather (hot, dry, and windy conditions); d. crown fire potential (top of trees and tall brush); e. ember production and movement (the spread of 9

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fire brands from the main fire); f. likelihood (chances of an area burning based on history) (CalFire, 2007). Fire hazards zones are assigned to one of three categories: moderate, high, and very high. California's state law dictates that the FHSZ designations need to be used in all State Responsible Areas, including all unincorporated communities. Local agencies (incorporated cities) are encouraged by CalFire to incorporate the "Very High Fire Hazard Severity Zone" designation for hazard prevention and planning (CalFire, 2015d). In 2008, CalFire created maps for the five cities in Alameda county that are located in (or partially located in) within the VHFHSZ; these are Berkeley, Oakland, Piedmont, Pleasanton and San Leandro (CalFire, 2015). Economic Responsibility for Fire Management Identifying who bears the economic responsibility for fire mitigation and prevention efforts in the area and where the money for these efforts should come from is another important issue. As damages caused by wildfires continue to increase, so does the cost to maintain and protect the areas they have affected. Fire mitigation efforts are funded by state and municipal sources, both of which draw needed revenue mainly from collected tax, and especially property tax, though this is the only source. At the local level, each of Alameda County's 14 incorporated cities is at least partially responsible for protecting their territory; these municipalities include Albany, Berkeley, Dublin, Emeryville, Fremont, Hayward, Livermore, Newark, Oakland, Piedmont, Pleasanton, San Leandro, and Union City (Figure 1.3). In contrast, it is Alameda County that manages the State Responsible Areas (SRA) responsible for the protection of the unincorporated 10

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communities of Ashland, Castro Valley, Cherryland, Fairview, San Lorenzo, and Sunol. According to California's Legislative Analyst's Office, the amount of property taxes paid by a homeowner is determined by two factors. First, the Tax Rate is based on the location (or Tax Rate Area [TRA]) of a parcel within the county/city; in Alameda County, the TRA was 1.086-1.405% of the total property cost for FY 2012-2013. The second factor includes Fixed Charges and Special Assessment, which are special fees voted by residents. One example of these is the special fee of $65 charged to residents living in the Oakland Wildfire Fire Prevention Assessment Area. Once tax revenue is collected, 1% of it is funneled to the county budget while the remainder is directed to the cities (e.g., if a parcel's TRA is 1.405%, 1% goes to the county while the remaining 0.405% goes to the city).(Figure 1.5 ) Both the county and the cities that comprise it have a primary fund called the "General Fund" which manages all revenues and expenditures. In Oakland, for FY2012/2013, property tax accounted for 30.82% of the city's General Purpose Fund, which was allocated to various expenditures. Oakland's municipal budget comprises both the General Purpose Fund and the Non-Discretionary Funds; together, they are called All Funds. The General Purpose Fund is the main source of money for the Fire Service Agency(Table 1.1). In FY 2012-2013, 24% of the General Purpose Fund went to the Fire Service Agency. The sources of revenue for the Fire Service Agency come from the local (96.25%), county (3.20%) and federal (0.55%) levels. For the same fiscal year, the General Purpose Fund contributed to 87.7% of the Fire Service Agency budget, making it the Agency's main source of money 11

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Figure 1.5 Illustration of the division between countyand city-level budgets. Interestingly, for that same period, while 22.95% of the city's budget was directed to fire mitigation, 87.7% of the revenues came from property taxes. In contrast, in Alameda County's proposed budget, 15% of collected property tax is allocated to fund activities like fire services; the rest is allocated to education (40%), redevelopment (13%), the various cities (18%) and miscellaneous items. Table 1.1 Oakland's breakdown of revenues by fund for the Fire Service Agency for FY2012-2013. White row indicate federal funds; dark grey rows indicate county/state funds; light grey rows indicate local/city level funds. 12

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In FY 2012-2013, 24% of the General Purpose Fund went to the Fire Service Agency. The sources of revenue for the Fire Service Agency come from the local (96.25%), county (3.20%) and federal (0.55%) levels. For the same fiscal year, the General Purpose Fund contributed to 87.7% of the Fire Service Agency budget, making it the Agency's main source of money Fire Mitigation Activities The fire mitigation activities in the city of Oakland are regulated by the Oakland Fire Service Agency and is target at two levels, the citywide and the VHFHSZ. The Fire Prevention Bureau Oakland, a subdivision of the Fire Service Agency, is in charge of overseeing the fire mitigation activities at the two levels. The bureau's role is to provide the and ensure the compliance with fire prevention codes and standards to insure the communities health and safety at the city level. This is done by providing various services at the citywide level like "fire safety education, fire cause investigations, inspection of high hazard occupancies, fire code enforcement, hazardous materials regulation, and vegetation management" (City of Oakland, 2016). In addition, the Fire Prevention Bureau is also in charge to oversee the Wildfire Prevention Assessment District, a voters approved tax collected in the Special Assessment portion of the property for the people that live in the VHFHSZ. The role of this special fee is to fund prevention programs in the VHFHSZ like the Goat Grazing Program Property Owner Free Chipping and Debris Removal program, Vegetation Management Program (on public lands), Fire Prevention Education & Training Program, Roving Fire Patrol Program and Support Services for Inspection Program. In FY2012/2013, the Fire Prevention Bureau adopted 13

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budget was $5,586,370, from which 33% ($1,850,518) was funded by The Wildfire Prevention Assessment District Fund to provide fire mitigation efforts in the VHFHSZ of Oakland. Statement of the Problem The operating costs of municipal fire departments are mainly funded by property taxes. As mentioned above, t he Oakland Hills were heavily developed in 1950s to 1970s to increase the amount of collected property tax and boost the city's operating budget. Since the city is responsible for the costs of wildfire mitigation and since some parts of the city are more likely to be directly affected by fire than others, funds collected though property taxes can be used to protect the more fire vulnerable areas. Today, the Hills are significantly more affluent than the Flatlands in Oakland, meaning that the less affluent part of the population may well be paying to protect the most affluent one, which would perpetuate cycles of inequalities. In principle, property tax revenue should offset the cost of living in highly vulnerable areas. Based on fire prevention costs, the houses located in these vulnerable areas are clearly very expensive for the city to maintain, but the amount paid in property taxes by individual homeowner may not actually correspond to the real cost of owning houses in the Hills. If that is the case, it is doubly problematic since it means that more resources are funnelled to protect the most exposed areas (i.e., the Hills), leaving correspondingly less money to pay for municipal services in other, less affluent areas (i.e., the Flatlands). This would compound problems deriving from wealth disparities across the city, since the people who are least vulnerable to wildfires (in the Flatlands) 14

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remain more socially vulnerable because they are also less able to react to other challenges as a result of their limited socio-political agency and economic marginalization. With these elements in mind, this thesis seeks to critically examine the economic history of cities in the VHFHSZ of Alameda County and how urban planning potentially enabled some people to receive more benefits than others from the revenues generated by this development, which may have contributed to the production of future vulnerability. The thesis uses political ecology as a theoretical framework to identify three main topics vulnerability, urban sprawl and economic responsibility through which these issues can be tackled. Research Questions The development of cities in Alameda County, especially Oakland, appears to have served as a tool to generate increasing revenue and to have potentially enabled certain parts of the population to benefit from this system more than others. This in turn likely contributed to the production of vulnerability throughout the county. To approach this topic, the subject was divided into two parts: 1. How do the VHFHSZ and Non-VHFHSZ differ in terms of how much tax revenue they generate in the various incorporated cities in Alameda County and in particular in Oakland? 2. How has Proposition 13 affected Oakland's capacity to collect property tax in the VHFHSZ and Non-VHFHSZ? 15

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Format of the Study The research presented in this quantitative study is based on an Alameda Assessor Office dataset. This dataset indicates the Assessed Property Values for properties in Alameda County (2012) and calculates the fixed tax rate based on the TRA of the parcel. The dataset includes records for almost half a million Alameda County residential properties for FY 2012-2013 (businesses are excluded). This dataset thus permits to identify who pays tax (and how much of it) and to compare this to the risk of fire for the area. The research presented here analyzes these records and is divided in two stages: the first will determine the amount of property tax generate from the various cities located in the VHFHSZ and Non-VHFHSZ within Alameda County; the second will compare how political circumstances like Proposition 13 may have complicated the capacity for cities to collect adequate amounts of property tax. It should be pointed out here that this study disregards fixed charges and special assessments because these are voted-in fees meant to fund specific public projects that residents of a given city will directly benefit from. Significance of the Study At its most basic level, this study aim is show how much tax revenue is being generated, who is paying this amount, and how these payments relate to actual property values. Oakland contains two parallel societies that differ in social, economic and environmental characteristics, and which are exposed to urban challenges in different ways. Traditionally, political ecology has sought to address how marginalized groups of people live in the most vulnerable areas. In the case of Oakland, however, we face an opposite situation: the areas most vulnerable to fire (i.e., the VHFHSZ) are occupied 16

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groups of wealthy people while the areas less vulnerable to fire (Non-VHFHSZ) are less wealthy. This situation was complicated by the passage of Proposition 13 which was designed to keep the assessed value of houses artificially low (compared to actual home values) and ultimately had the effect of reducing the potential amount of revenue collected though property tax. This situation potentially benefited the wealthier members of the community by creating pockets of people that paid proportionally less than their share in property taxes. This thesis seeks to provide a picture of the distribution of property taxes collected in the VHFHSZ and Non-VHFHSZ. In addition, it addresses how political circumstances like Proposition 13 have allowed for certain parts of the city to disproportionately benefit from the property tax system in place. As a result, the least vulnerable members of the community (who happen to be less affluent) pay for the fire protection for the most vulnerable, who happens to be the city's most wealthy citizens. The results from the study contribute to a growing body of research that explores the issue of vulnerability in the First World and how this vulnerability can be shaped by political circumstances. Definition of Terms Proposition 13 Proposition 13 (1978) was responsible for creating a major change in California's taxation system by limiting the amount of money that can be collected though property taxes by keeping house values artificially low (i.e., lagging well behind inflation). Since the rate of homeownership and property value increases in the Hills was higher, people 17

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living in the Hills supported the proposition to a greater degree than those living the Flatlands. Ultimately, Proposition 13 opened the door to intensified development in the city as a tool to generate more tax revenue through property taxes, a phenomenon that ultimately contributed to the production of vulnerability to fires (Simon 2014; Dooling, Simon 2012). Risk The probability that a system is affected by a hazardous event leading to negative consequences (United Nations, 2009). In order to calculating risk we need to identify the hazard event (frequency and intensity of the treat), exposure (people or assesses affected by in the hazard) and vulnerability (the lack of capacity of a population to sustain potential looses from a hazardous event). Risk = Hazard Event x Exposure x Vulnerability Very High Fire Hazard Severity Zone (VHFHSZ) In Alameda County, the Very High Fire Hazard Severity Zone is defined based on the information provided in CalFire 'Fire Hazard Severity Zones'. This area is located in the local, state and federal responsibility areas. It was defined by CalFire to delineate the areas of greatest fire hazard and fire risk as a way to measure the physical fire behaviour. The zone is based on measuring various fire hazard elements like topography, slope, vegetation, weather, crown fire potential, and ember production and movement Vulnerability 18

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Vulnerability can be defined as the characteristic of a system that makes it susceptible to the effects of a hazard(United Nation, 2009) and the likelihood the system would experience harm based on the exposure to a hazard (Turner, B. L., 2003). In order to determine how a system can be exposed to, affected by, or impacted by the hazard, it is important to identify elements that affect vulnerability (United Nation, 2009). Vulnerability in this thesis refers to the hazard exposure based on the geographical location. In the case of Oakland, according to CalFire, the area most vulnerable to fires is the VHFHSZ, located mainly in the eastern portion of the city along the Hills. For the purpose of this thesis, vulnerability to wildfires (metric) is defined by the structures exposed to fire and to a lesser extent the adaptive capacity of people that live/work in these structures. Wildland Urban Interface (WUI) The WUI is the area where were urbanization has expanded to the intermingled and undeveloped wildland (Radeloff et al., 2005). Composed of interface and intermix communities, the WUI is defined by the minimum density of houses in an area (i.e., one structure per 40 acres). Traditionally, the WUI has been described as an area highly vulnerable to fire. The International Association of Wildland Fire (IAWF) organization defines the WUI as the "geographic location where structures and flammable vegetation merge in a wildfire-prone environment" (IAWF, 2013). In the wester US, 72% of houses are located in the WUI (the county average is 39%) (Radeloff et al., 2005), meaning people face an increasing risk and vulnerability to wildfires. 19

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CHAPTER II THEORY AND LITERATURE REVIEW The theoretical framework used in this thesis combines two elements. First, a political ecology perspective helps understand how vulnerability to hazards could have been produced by the pursuit of cities to increased tax revenue. Specifically, it helps raise the question of how political circumstances like Proposition 13 affected the capacities of the city to generate revenues. Second, the concept of the production of vulnerability is used to describe areas more exposed to wildfires, based on economic, social and environmental factors. Furthermore, the continuous production of fire vulnerability in Oakland results from the joint influence of both decision-making and city planning. This thesis examines how factors like urban sprawl and political facilitations like Proposition 13, help increased the hazard vulnerability areas with. Framework: Political Ecology Introduction Political ecology is a field of study that uses political, economic and social frameworks to examine environmental issues. This multidisciplinary approach seeks to understand the relationship between nature and society and the consequences of this relationship on the environment and sustainable livelihoods (Watts, 2000; p. 257). Political ecology recognizes that environmental change can be the result of activities that are shaped by their political context, in which degradation and deterioration result from, and continue to shape the relationship between humans and the environment (Stott and Sullivan 2000). Moreover, this approach explores how broader systems of power and 20

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influence, impact unevenly who benefits most within a social-economic system (Robbins, 2012). Bryant and Bailey (1997, pp. 27-28) outline three fundamental assumptions of political ecology: 1. "Costs and benefits associated with environmental change are for the most part distributed among actors unequally;" 2. "Unequal distribution of environmental costs and benefits reinforces or reduces existing social and economic inequalities;" 3. "Differentiated social and economic impact of environmental change also has political implications in terms of the altered power of actors in relation to other actors." The Political Ecology of Hazards Traditionally, the political ecology framework argues that marginalization occurs when vulnerable segment of the population get systematically denied full access and/or control over their resources (Bryant and Bailey, 1997; Robbins, 2004). This situation can be seen very clearly in developing countries, where political, economic and social relationships often severely limit the ability of people to deal effectively with environmental change (Robbins, 2002; 2004). That said, the marginalization process generally concentrates vulnerability to hazards within certain segments of a population. However, the effects of that hazard vulnerability on the marginalization of communities are not always the same. For instance, the process leading to people living in vulnerable areas varies according to whether you are living in the developed or the developing world (Collins, 2008). In developed countries, people who are not marginalized in the least 21

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often purposely choose to live in areas that are more vulnerable than others (e.g., the inhabitant of the Oakland Hills). This is because of social arrangements like "insurance coverage, land use regulations, emergency response and disaster relief subsidies" that enable the wealthy to settle in these highly vulnerable places without suffering the same consequences as they would in impoverished neighborhoods, or developing countries (Collins, 2008; p. 22). Given that certain segments of the population are more vulnerable to specific hazards than others, the political ecology of hazards deals with the effects of social inequalities on the capacity of these vulnerable groups to cope with and manage the risk posed by hazards (Wisner et al., 2004). In this case, risk is described as "compound function of biophysical hazard exposure and peoples' vulnerability" (Collins, 2008; p. 22). Social vulnerability refers to the pre-existing conditions influencing a person's or a group's ability to cope with a hazard and its aftermath. The Elements that Shape Hazards Vulnerability and the risk to fires in Oakland have been shaped by contributing factors like urban sprawl and state policies, like Proposition 13, that drove the development in the area. The political ecology framework helps highlight a series of multi-scale contributing factors that shaped vulnerability to fires in Oakland. Using this framework provides an intellectual structure to investigate how political decisions and facilitations' allowed and encouraged people to settle and build in fire vulnerable areas, thus increasing vulnerability to wildfires in the area. Consequently, vulnerability was in large part the result of these same political circumstances. Using a political ecology framework to confront this problem allows us to examine who was responsible for 22

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making these areas vulnerable and to assess the role of private citizen vs that of the government in fire prevention and mitigation. Untangling the history of urban development in the Hills will permit the identification of beneficiaries of the present situation as well as an analysis of the hidden dimensions of who bears the real cost of sprawl relative to the cost of mitigation. Proposition 13 In 1978, almost two-thirds of Californians voted to pass Proposition 13 to restructure property taxation in the state by significantly reducing the amount paid in property taxes (Legislative Analyst's Office, 2012). This new legislation introduced two important elements: first, the maximum owed tax by property was fixed at 1% of its value, and second, a property's assessed value could only increase by one percent annually, unless there was a change in ownership or a significant renovation was undertaken, both of which could increase the value of the property to current market assessment (Oakland Policy Budget, 2009). Proposition 13 therefore reduced the amount of revenue that could be collected though property taxes by keeping the assessed value of the home artificially low (i.e., substantially below inflation), which stunted price growth over time and, consequently, potential city revenue. Proposition 13 was the result of the neoliberal ideology that was fundamental to California's Tax Revolt, which reflected people's discontent with public spending. During this time, neoliberalism help restructure the relationship between the state and the market, ultimately creating deregulations that benefited the wealthiest (Hohle, 2015). 23

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Urban Sprawl Urban sprawl is defined as the horizontal expansion and development of cities into land that is undeveloped (EPA, 2014; Nechyba and Walsh, 2004). Several factors have allowed cities and suburbs to expand into exurbs and rural areas. First, population growth: over the past centuries, as US population has continued to grow rapidly, the number of people living in urban centers has grown considerably. For instance, in 1790, only 5% of the US population lived urban centers (Census Data). It was really only after World War II that urban development flourished and by 1950, more than 50% of the national population had moved to urban centers. Today, over 80% of the US population lives in urban areas (Nechyba and Walsh, 2004). Second, increased income: population growth was accompanied by an increase in income due to diversification in the job market, the number of available jobs, the variety of jobs, and the amount of pay; this gave people greater economic power. Lastly, a change in transportation behaviors based on the cheaper cost of transportation also facilitated the horizontal growth of cities, especially after World War II (Brueckner, 2000). The growing body of research on urban sprawl has identified a myriad of factors to help describe and understand this concept. First, the basic measurement unit for urban sprawl is the "urban cluster" which the US Census Office defines as an area that contains 5001000 people per square mile. Second, cities have grown based on physical (geometric) and functional (economic) patterns in order to help with the division of labor generated from scaled economics (Batty, 2008). Third, measuring urban sprawl can be challenging because it is not a unidimensional phenomenon. Multiple studies have 24

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attempted to measure urban sprawl by characterizing this phenomenon by its growth rate, density (distance and proximity), spatial geometry (shape, size), accessibility, and aesthetic measures (Frenkel and Ashkenazi, 2008; Theobald, 2005). Fourth, there are multiple views and studies addressing the benefits and downsides of urban sprawl. On the one hand, critics argue that this excessive growth is a problem that needs to be limited and controlled. On the other, supporters tend to agree that urban sprawl bolsters the overall economy due to the demands of growing population and the increase in property tax collected from the land developed. As discussed previously, many fundamental forces drive urban sprawl but it is safe to say that the process of urbanization is closely related to the value of land (Brueckner & Kim, 2003). In recent years, several studies have explored the relationship between land use (zoning) and productivity, and how this affects the value of the land (i.e. urban land is valued higher than non-urban land). Researchers have found that there is a close relationship between how land is zoned (urban vs. non-urban) and its value. Land zoned as urban is worth more than non-urban land because of the money collected strictly through land taxes is less than the amount collected in property tax (Brueckner & Kim, 2003). Since property taxation has traditionally been an important source of revenue for cities, the potential for collecting larger amounts of money through increased property taxes can boost land development in and especially around cities (Brueckner & Kim, 2003). Oakland Property Values and Taxes 25

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The city of Oakland presents a markedly uneven distribution of wealth, with the Hills being significantly more affluent than the Flatlands. Also, the Hills are located in the VHFHSZ, which makes them much more vulnerable to fire than the Flatlands. According to census data (US Census, n.d.), the mean income of Oakland residents is $52,583 and the medium value of owner-occupied houses is $428,900 (citywide). In the Hills the average value of a house is $ 900,000 compared to about $400,000 in the Flatlands (Simon and Dooling, 2012). Based on these prices alone, one can argue that the Hills are a very expensive and exclusive area; in fact, over the last 70 years, the average price for a house in the Hills has increased nine-fold compared to an increase of only 6.5 times in the Flatlands (Simon 2014). Since the cost of living in the Hills is higher than living in the Flatlands, one would expect that property taxes from the Hills would contribute more to the general city budget, in the same way that house insurance is higher for those who live in vulnerable areas. Based on the cost of housing of these two areas and trends in home price increase over time, it is however possible to see that one area has benefited more than the other from city planning and budgeting. Elements that Shape Vulnerability in the Context of Political Ecology The structural causes that lead to the increase in fire vulnerability in the area resulted from the poorly planed development of the city and the incentive to developed guided by economic reasons. These rapid urban growth into the Hills was possible because the new wealthy residents could afford to live in fire prone areas with the help of social facilitations (like fire insurance ) that ultimately help them reduce the potential looses from a hazardous event. In addition, political circumstances, like proposition 13 26

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increased the fire vulnerability in the area because it allowed for the wealthy to pay reduced property taxes ( based of properties assesses below market value) that ultimately contributed less to the city budgets Framework II: The Concept of Vulnerability and its Production Historically, there has been a tendency to impose a disconnection between human and natural systems and to study them as separate elements of a puzzle. Currently, however, there is a growing trend of multidisciplinary research that links and studies these two systems together. The concept of vulnerability is one of these links that allows social and natural systems to be studied together (Simon and Dooling, 2012). According to the United Nations, vulnerability is the set of characteristics and circumstances of a community, system or asset that make it susceptible to the damaging effects of a hazard (United Nation, 2009). The concept of vulnerability deals with the relationship of humans with the environment and the social forces that shaped this relationship (Bankoff et al, 2004 ). Vulnerability is thus shaped by political, economic and social factors. Increases in vulnerability can enable certain members of a population to become more vulnerable than others based on their socio-economic characteristics. Vulnerability to hazards like fires can thus be described as a complex multifaceted relationship between social and ecological systems where social systems can be exposed to, affected by, or impacted by hazards (Simon and Dooling, 2012). The factors that shape vulnerability to fires are assigned to one of two main categories: environmental and social. An ecosystem's vulnerability to fires can increase when its balance is broken. Environmental factors like drought, low precipitation rates, 27

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type of land cover, type of vegetation, elevation, slope and an excess of natural fuel can all increase vulnerability to fire in an area. Similarly, social factors contribute to shape fire vulnerability and the exposure of people to these hazards. First, we must consider policy and budget considerations, since fuel reduction practices are constantly changing in response to budgetary considerations due to their cost and the fact that they are not always done properly. Second, the direction of urban sprawl and the rate of environmental modification also matter. As population continues to expand, it is necessary to take measures to control and regulate urbanization into formerly natural areas. Third, the characteristics of the population are also important. For instance, the demographics of an area can indicate variable levels of vulnerable populations for given hazards, like pregnant women, single parent households, elderly citizens, and young children. The income and education levels and the social background of the people in the area also have an influence (e.g., can they speak English, do they know how to react to a hazardous situation, do they have good fire insurance, are they poor or rich, etc.). Fourth is the proximity of people to the hazard (e.g., do they live in a high fire risk area or next to the mountains). Fifth, we must consider people's economic capacity to recover form a fire (e.g., are they covered by insurance, do they qualify for government help). Finally, the capacity of people to react to a fire is also critical (e.g., do they have a car to evacuate in case of a fire, do they have good insurance to cover the cost of rebuilding their homes, etc.) Human actions are often largely responsible for increasing vulnerability. In the specific case of the WUI, vulnerability to fires has increased over the years as a result of 28

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human actions that constantly reshape their ecosystems. Vulnerability is deeply rooted in the history of development of a place and can only be understood within its historical context and that of the social conditions of the population. Access to political power (or lack of it) and uneven distribution of wealth can reinforce social relationships and perpetuate (or amplify) disparities and the cycle of vulnerability (Thomas et al., 2013). The social characteristics of a population (e.g., health, income, disability, age, gender, ethnicity, literacy, or immigration status) can also aggravate vulnerability (Bankoff, 2006; Thomas et al., 2013; Wisner et al., 2003). As a consequence, the production of vulnerability is constantly shaped by human actions, which in turn can leave us more exposed to hazards like fire. As it was indicated previously, the concept of vulnerability is a dynamic and can indicates multiple meanings. In this thesis, vulnerability refers to the hazard exposure based on the geographical location. In the case of Oakland, according to CalFire, the area most vulnerable to fires is the VHFHSZ, located mainly in the eastern portion of the city along the Hills. That said, vulnerability to wildfires (metric) is defined by the structures exposed to fire and the people that live/work in these structures. Summary Human-environment relations are complex and multifaceted; they are shaped by political forces, and neoliberal economic policies that tend to reinforce the uneven distribution of costs and benefits that emerge from these human-environment interactions. Power structures have allowed enable certain social groups to profit from political circumstances. Vulnerability to hazards is constantly shaped by human actions where 29

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social systems generate unequal exposure to risk. The city of Oakland is divided in two areas, the Hills and the Flatland. The first is very vulnerable to fire but happens to be very wealthy, while the second area is not vulnerable to fire but is less affluent. The political ecology framework helps us to frame how vulnerability to hazards was produced by the efforts of cities to increase tax revenue. This raises the question of how political circumstances like Proposition 13 may have affected the capacity of the city to generate revenue. 30

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CHAPTER III METHODS Introduction The Oakland Tunnel Fire of 1991 left a deep mark on the history of California. Since then, the city of Oakland and the state of California have made multiple efforts to reduce the possibility of another disaster of similar magnitude. This study examines how urban development in the VHFHSZ in Alameda County may have contributed to the production of vulnerability (exposure) to fire within the area. In particular, it explores how the search for higher revenue contributed to increased risk to fire hazards throughout the area. To answer these questions, this thesis employs a quantitative research strategy to compare the tax revenue collected from houses located in areas vulnerable to fire to that from properties in low-risk areas. Furthermore, the research analyzes the long-term effects Proposition 13 has had on house values and how this may have affected the total amount of revenue collected in fire vulnerable areas. This is done to empirically describe housing in both locations, in order to objectively compare and contrast them. Ultimately, the results of the study framed in a political ecology perspective permit a discussion of the consequences of urban development driven by political incentives and also how political circumstances impacted the overall fire vulnerability (exposure to the hazard) of the area. Research Design The research was conducted and data were collected during a research assistantship conducted at Stanford University in 2013 in the context of the 31

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"Vulnerability in Production" project, a running initiative supervised by Dr. Gregory Simon (from CU Denver) in collaboration with researchers from both schools. Some of the data presented here were gathered during this research assistantship and the rest were acquired and analyzed after I had returned to UC Denver. The research focuses on how the development of cities in Alameda County and specifically Oakland was used as a tool to generate greater municipal tax revenue and how political circumstances like Proposition 13 contributed to Oakland's vulnerability to wildfire, while perhaps unwittingly enabling certain parts of the population to profit more than others from this extra revenue. To examine this development, the subject was divided into two parts: 1. How do the VHFHSZ and Non-VHFHSZ differ in terms of how much tax revenue they generate in the various incorporated cities in Alameda County and in particular in Oakland? 2. How has Proposition 13 affected Oakland's capacity to collect property tax in the VHFHSZ and Non-VHFHSZ? The dataset used in this study contains the following independent variables (a) city (the various incorporated cities in Alameda County); (b) WUI or Non-WUI (located within the Wildland-Urban Interface or not); (c) VHFHSZ or Non-VHFHSZ (located within the Very High Fire Hazard Severity Zone or not); (d) Time (when was the house purchased). The following dependent variables were also included in the database: (a) The total amount of money collected in property taxes (citywide, WUI/Non-WUI and within the VHFHSZ/Non-VHFHSZ); (b) The total size of the area (citywide, WUI/NonWUI and within the VHFHSZ/Non-VHFHSZ); (c) The year the structure was last 32

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reassess in value; (d) The total cost of the property (citywide and within the VHFHSZ/ Non-VHFHSZ). Data The main dataset used for this analysis comes from the Alameda Assessor's Office, which compiled the "Assessor Secured Roll" parcel information for Alameda 1 County Finalcial Year 2012/2013. This dataset contains nearly half a million records for Alameda County, including residential, commercial industrial and other parcels. The information given for each record includes: a. the parcel number; b. the address; c. total value (land value and the land improvements); d. land use code (residential, commercial, industrial, etc.); e. the description of residential parcels (single, 2-4 units, and 5+ units parcels); f. the primary and secondary TRA (tax rate area); g. other information (like tax reduction for owners, etc.). In order to standardize the dataset and make it more uniform, I derived a single unit of measurement, called Single Family Parcels'. This was done according to the following sequential criteria: 1. Identify the residential parcels using the Property Assessment information codes from the assessor's office (See Appendix A) and select occupied "Single Family Parcels" based on the "use codes" ( 1100 Single family residential homes used as such; 1 The county's Assessor Secured Roll file is a list of properties' "Assessed Value", based on the lien against the real cost of the property itself. In contrast to the secured roll, the unsecured property tax includes property like boats and airplanes, and the lien against the cost is not the property itself. The "assessed value" indicates 100% of the full value. http://www.acgov.org/auditor/tax/faqs.htm#PtaxSec 33

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1140 Single family residential home, R&T 402.1; 1150 Historical residential; 1190 Single family residential (tract) common area or use; 1200 Single family res home with non-economic 2nd unit; 1300 Single Family Res home with slight commercial/ind; 1440 Single Family Res Duet Style, R&T 402.1; 1900 Single family res manufactured ). 2. Using the information given in the primary and secondary TRA and the rate indicated by the "2012-2013 Alameda's Tax Rate Book" (See Appendix B for summary), calculated the fixed tax rate for each record. 3. Finally, to avoid skewing the results, houses that did not have any information (null values) or that paid very little (i.e., less than $100 a year) were excluded for the final analysis. In other words, properties that cost less than about $10,000 were omitted, to avoid giving undue influence to empty or partially built houses among other exceptions. This dataset was later joined to a series of GIS layers containing the parcels' location and shape for the various cities in Alameda County. In addition to the "Assessor Secured Roll" data, other GIS layers were used to complete the analysis (see table 3.1); henceforth, all GIS layer used NAD83 StatePlane CA III Fips 0403 (US feet) projection. Table 3.1 List of GIS layers used This layer was joined to tax dataset' using the Joins and Relate Function' by the eld named "GisJoin". Layer Source Original Projection County Boundary Alameda_County.shp Alameda County GIS viewer WGS_1984 Mercator Alameda Parcels Parcels.shp Office of Alameda County NAD_1983_State Plane CA III Fire Hazard Zone ** c1fhsz106_3_1.shp CalFire NAD_1983 Alberts The Wildland-Urban Interface WildlandUrbanIntermix05_1.shp CalFire NAD_1927_Alberts Cities in Alameda *** City_Limits.shp Alameda County CDA NAD_1983_ State Plane CA III 34

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* This layer contained the three levels of FHSZ. Using the select by attribute', I selected the VHFHSZ and exported to layer into a new layer. The city limits layer contain all of the cities in one layer, Using the select by attribute', I selected each city by name and exported into a layer. Data Processing and Analysis The data was collected during the summer of 2013 as part of a research assistantship conducted at Stanford University in the context of the "Vulnerability in Production" project under the supervision of Dr. Gregory Simon. The data processing and analysis presented here were done in subsequent semesters as part of the thesis work. In order to address the research questions presented earlier, the data processing and analysis section of this thesis is divided in two portions based on the two research questions. Question 1: How do the VHFHSZ and Non-VHFHSZ differ in terms of how much tax revenue they generate in the various incorporated cities in Alameda County and in particular in Oakland? The first part of the methodology seeks to quantify how much property tax was paid by the various residential parcels in each of the cities in Alameda County and in particular for the cities located in the VHFHSZ. In order to answer this question, I used ArcGis to analyze the dataset previously described (in the data section) in conjunction with the GIS layers (Table 3.1). Given that the tax dataset was very large and was making the computer analysis very slow, I broke down the dataset into smaller pieces. To begin the analysis, I first created the outline of each city from the "Cities of Alameda" layer (see Table 3.2 a), then used the joint the data to the tax dataset (see Table 3.2 b). This part provided me with the information on total area, number of parcels, number of single family residential parcels, net home values, total amount of property taxes collected, the 35

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mean and SD for each of the incorporated cities in Alameda County. The data were later characterized using descriptive statistics to establish the mean, standard deviation and coefficient of variation of the number of parcels, and the amount of taxes paid. This first step allowed me to create a basic profile of the county and a distribution of the home values and property taxes paid. Then, I used the "Select by Location" tool to identify the parcels located within the VHFHSZ layer for each city and the exported the layer (see table 3.2 e). The spatial method used was "have the centroid in the source layer feature", in order to avoid accounting for the same polygon in two different layers. For example, if one portion of a parcel was located in the VHFHSZ layer and the rest in the Non-VHFHSZ, the location of the centroid of the polygon was what determined whether the parcel was considered as being located in the VHFHSZ. The result provided information on the total area, number of parcels, number of single family residential parcels, net home values, total amount of property taxes collected etc., for the part of the city located within the VHFHSZ for each of the incorporated cities in Alameda County. After reconstructing the distribution of the parcels located in the VHFHSZ for the various cities, the next step was to determine the distribution of the parcels not located in the VHFHSZ. In order to identify the parcels in the Non-VHFHSZ, I used the citywide layer and the "Erase tool" to erase the parcels located in the VHFHSZ (Table 3.2 f). This technique allowed me to make sure there were no doubles in the data and there were no polygons counted in both the VHFHSZ and the Non-VHFHSZ. The results provided information on the total area, number of parcels, number of single family residential 36

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parcels, net home values, total amount of property taxes collected etc., for the part of the city not located the VHFHSZ. According to California Department of Forestry and Fire Protection (CalFire), the VHFHSZ is the most vulnerable area to fires in Alameda County (compared to the WUI); for this reason, this research focuses on the VHFHSZ vs the Non-VHFHSZ areas. Nonetheless, since the great majority of the fire mitigation literature focuses on preventing fires in the WUI, I used the same methodology to identify the parcels located in the WUI and Non-WUI. These various data then allowed me to compare and contrast the relationship between WUI/Non-WUI and VHFHSZ/Non-VHFHSZ. It also allowed me to discuss why we should preferentially use the VHFHSZ designation. This methodology allowed me to identify all of the residential parcels contained at the citywide, VHFHSZ, Non-VHFHSZ WUI and Non-WUI levels for the various incorporated cities in Alameda county (Table 3.2). Then, I analyzed the data collected using descriptive statistics to establish the mean, standard deviation and coefficient of variation of the number of parcels. As a result, the GIS analysis, Excel querying and statistical analysis allowed me to address quantitatively how the VHFHSZ and NonVHFHSZ differ for the various incorporated cities in Alameda County. 37

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Table 3.2 : List of layers created including a description of each. The following layers and naming convention were used for all of the incorporated cities in Alameda County. Layer Processing Notes a "Name of city" Ex: Oakland Selection >> Select by attribute >> select by name of city Geoprocessing >> Intersect (outline of city selected and the Alameda parcels layer) City outline with parcels b "Name of city" + Tax Ex: OaklandTax Joins and Relates >> Join (joined tax dataset to the "City" layer using the eld "GisJoin". Export the layer City outline, parcels and tax information. c "Name of city" + WUI Ex: Oakland_WUI Selection >> Select by location (Target layer: "CityTax"; Source layer: WUI) *Spatial method: have the centroid in the source layer feature" -Export the layer The parcels and the tax information located in the WUI. This was done to avoid accounting for the same polygon in two different layers (i.e. if the parcel was partially occupied by the WUI layer, the location of the centroid of the polygon will decide whether it belong or not to the WUI layer) d "Name of city" + NONWUI Ex: Oakland_NONWUI Analysis tools >> overlay >> Erase (input feature CityTax layer; erase feature: City_WUI' layer. The parcels and the tax information not located in the WUI. e "Name of city" + VHFHSZ Ex: Oakland_VHFHSZ Selection >> Select by location (Target layer: "CityTax"; Source layer: VHFHSZ) *Spatial method: have the centroid in the source layer feature" -Export the layer The parcels and the tax information located in the VHFHSZ. This was done to avoid accounting for the same polygon in two different layers (i.e. if the parcel was partially occupied by the VHFHSZ layer, the location of the centroid of the polygon will decide whether it belong or not to the VHFHSZ layer) f "Name of city"+ NONVHFHSZ Ex: Oakland_NONVHHSZ Analysis tools >> overlay >> Erase (input feature CityTax layer; erase feature: City_VHFHSZ' layer. The parcels and the tax information not located in the VHFHSZ. 38

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Question 2: How does Proposition 13 affected Oakland's capacity to collect money from property taxes in the VHFHSZ and Non-VHFHSZ? The second part of the methodology seeks to provide a picture of the distribution in the property values in Oakland and of the effects that tax laws like Proposition 13 have had on property values over the years. Proposition 13, passed in 1978, limited the amount that can be collected in property taxes. As a result, property values were maintained artificially low and well below inflation. Thus, the amount of property tax collected can vary significantly even between neighboring properties, since it is based on the year the property last changed its reassessment value (i.e., changed owners or had significant remodeling that lead to a reassessment). Given that Proposition 13 provided a setting for producing irregular patterns in home value distribution, the second portion of this analysis was designed to identify areas where there might be residents underor overpaying tax on their houses (i.e. properties that are paying below the median home value)To answer this question, I used the VHFHSZ and Non-VHFHSZ datasets previously generated to identify areas whose home value had not kept with the property market. To do that, the methodology considers two elements, the property value and the year of reassessment of the value. Property Values This part of the study was designed to identify parcels that paid below or above the median home value. To do this, the dataset included a field called Total_Net' which indicated the value of the property. In order to take into account the cost variation from the various portions of the city, I calculated a new field called "Cost_Comp" that used the 39

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US Census tract Median Home value (field name: "T_MedVal") information and compared it to the net value' ("Total_Net"). Then, I calculated the product by by 100 and dividing that figure by the tract value' field, I was able to derive a percentage measure of how much (or less) the property is paying. To give an example, if a house net value' (field name: "Total_Net') is $250k and the Census tract Median Home value (field name: "T_MedVal") is $300k, I subtracted the $300k $250K =50. Then, I multiply 50 by 100% and divided by 300, the result was 16.66% which correlates to the field the"CostComp". From there, I created a new field called Cost_Comp2 that classified the percentages in categories. This was done with the help of "Select by Attributes tool," I assigned the following values to the following categories: 1 = 0-10% below asking prize; 2= 10-25% below asking prize; 3 = 25-50% below asking prize; 4 = 50-100% below asking prize; 5 = >100% below asking prize. I used the categories previously created (i.e., "Cost_Comp2" = 1) to create a series of points that indicated the location of parcels that payed below. From there, I was able to use the Optimized hot spot analysis' tool to find clusters of properties paying below and above market value (based on the categories created in the field Cost_Comp2). The result of this first portion yields a series of data and maps that indicating clusters within the city of the areas paying below and above the tract's median home price in the VHFSZ and the Non-VHFHSZ. Year of the Property Reassessment This section aims to provide an overview of the effects that the year of a property last reassessed had on the value. Since the year of reassessment can be a limiting factor of how much a property can increase in value, it is important to see whether or not there 40

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is a relationship between low values and the year the property was purchased. To do this, the dataset included a field called "last-documented_prefix" which indicated the year the property got last reassessed in value. I summarized the data based on the location ( VHFHSZ/ Non-VHFHSZ) and the year of reassessment. 41

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CHAPTER IV RESULTS Introduction The Oakland Tunnel Fire of 1991 remains the most damaging wildfire in California's history and to this day the state government continues to make multiple efforts to reduce the possibility of another disaster of that scale. This thesis examines how urban development emerging in Alameda County along the VHFHSZ (as a way to increase property taxes) potentially contributed to the production of vulnerability to fire (exposure to the hazard based on the geographic location) within the area. In order to examine this subject, the Results chapter of this thesis is divided in two sections. The first section addresses the question of how the VHFHSZ and Non-VHFHSZ differ, in terms of property tax revenue generated, across the various incorporated cities in Alameda County, in particular Oakland. The second section addresses the impact of Proposition 13 on Oakland's capacity to collect money from property taxes in the VHFHSZ and NonVHFHSZ. Question 1: How do the VHFHSZ and NonVHFHSZ differ for the various incorporated cities in Alameda County and in particular in Oakland? In order to answer my first research question, the subject was divided into 3 portions. First, I began by providing a profile of Alameda County, including a full description of the area, the number of residential parcels (per city) and the total amount of property tax collected (per city). From there, I indicate the location of the VHFHSZ and the WUI in Alameda County, including a description of the area, the number of the 42

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residential parcels (per city) and the total amount of property taxes collected (per city). This part allowed me to explain why we should focus the research on the VHFHSZ and not the WUI. Finally, I focus in the description and location of the VHFHSZ in Alameda County and its cities. This part provides a description of the area, the number of the residential parcels (per city) and total amount of property taxes collected (per city) from the VHFHSZ and Non-VHFHSZ. Part 1: Alameda County The county is located in the eastern portion of the San Francisco Bay area and covers 744.31 square miles (sqmi), over half of which is urban. The urban sprawl of the county runs parallel to the coast and decreases with the beginning of the hills that run through the middle of the county. The original dataset included nearly half a million records (445,427) from the "Assessor Secured Roll" for Alameda County FY 2012/2013. This dataset included the information for Alameda County's residential, commercial, industrial, rural and institutional parcels. The information given for each record includes the parcel number, the address, the total value (land value and the land improvements), the land use code (residential, commercial, industrial, etc.), the description of residential parcels (single, 2-4 units, and 5+ units parcels), the primary and secondary TRA (tax rate area) and other information (like tax reduction for owners). The results from the data analyzed for the first question are summarized in two parts. Table 4.1 contains the information for the area, the number of parcels, the total amount of property tax collected, and the mean and SD of the Single Family Residential 43

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Parcels property taxes. Figure 4.1 present the total property taxes collected in 2013 in each of the incorporated cities of Alameda County. Table 4.1: Total property taxes collected 2013 in each of the incorporated cities of Alameda County From these data it was possible to draw the following observations: First, in Alameda County, 80% of the parcels (353,553 records including all types) are located within the 14 incorporated cities. The remaining 20% are distributed in the unincorporated communities and the SRA. Second, the city of Oakland, home to one quarter of the county's population, holds 28% of the parcels (98,852), from which 88% ( 87,533 parcels) are classified as residential, and in particular 69% (68,669 parcels) are Single Family Residential Parcels homes. Third, in Alameda County in FY 2012/2013, the Single Family Residential Parcels paid 85% ($1,165,524,696) of all property tax. In Oakland, the residential parcels contributed to 25% ($340,968,764) of the county's Property taxes, from which 76% ($258,617,972) came from Single Family Residential 44

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Parcels. Fourth, the mean property tax paid by a Single Family Residential Parcel varied from city to city, the lowest being in Emeryville ($2,403) and the highest being Piedmont ($9,482). Figure 4.1. The citywide level scatter plot of Single Family Residential Parcels by the total tax. The figure presents the relationship and size of the number Single Family Residential Parcels, the total taxes and the total area for each city at the citywide level. As is indicated by the legend, the size of the area is indicated by the size of the square, and the color code represent the various cities in Alameda County. Fifth, even though the per capita property tax for Single Family Residential Parcels is highly variable (mean) so is the dispersion of the values around the mean. Sixth, compared to the rest of the cities, Oakland's standard deviation is greater than that most other cities, which indicates a very large distribution of property tax amounts. Seventh, in 45

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general, as the number of parcels increase so does the amount collected from the properties, as is indicated by the very high R-squared value for this relationship. In summary, residential parcels represent the vast majority of parcels in Alameda County, and about one quarter of these parcels are located in Oakland. The amount of taxes collected varies based on the number of parcel within the city and the total area. The mean per capita property tax of the Single Family Residential Parcels is highly variable between cities, but so is the dispersion of the values around the mean (SD). Oakland presents the largest distribution on the data compared to the rest of the cities. Part 2: The VHFHSZ and the WUI in Alameda The VHFHSZ is a designation for a fire hazard zone model developed by the California Department of Forestry and Fire Protection (CalFire) and adopted by the local government to designate high fire risk zones. In Alameda, the VHFHSZ covers 8.1% (60.10 sqmi) of the territory and it runs almost diagonally along the hills from north to south. CalFire classified the fire hazard into three different levels: moderate, high and very high. These three levels apply to SRA territory except for the last level (Very High) which also applies to local territories (i.e., incorporated cities). With that in mind, in 2008 CalFire created identified and created maps for the cities at risk in Alameda County (Berkeley, Oakland, Piedmont, Pleasanton and San Leandro) (CalFire, 2015). As can be seen from the maps, the distribution of the VHFHSZ overlaps almost completely with the location of the WUI (Figure 4.2 and 4.3). This overlap it not a coincidence since the role of the VHFHSZ is to identify the portions of wildland vulnerable to fire hazards (CalFire, 2007). 46

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Figure 4.2 Map of the distribution of the Very High Fire Hazard Severity Zone (VHFHSZ) in Alameda County. In Alameda the VHFHSZ overlaps some of the urban profile, this designation can be found in five cities: Berkeley, Oakland, Piedmont, San Leandro and Pleasanton. In contrast, the WUI that area where urbanization has expanded into the intermingled and undeveloped wildland (Radeloff et al., 2005) covers 58.2% (433.02 sqmi) of Alameda County and it crosses the county's wetland, grassland/scrubland and woodland ecoregion, and it is found in all of the incorporated cities except Emeryville. Because the WUI is generally considered a place that is very sensitive to fires, it is included in this study but it is important to note that not all of the ecosystems the WUI comprises present the same risk of fire. As a result, since the WUI in this case study is not 47

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a good indicator for areas vulnerable to fire, the research is mainly interested in the VHFHSZ and uses the WUI as a reference. Figure 4. 3 Map of the distribution of the Wildland -Urban Interface (WUI) in Alameda county, California. In Alameda, the WUI covers a large percentage of the territory and it can be found in all of the incorporated cities except Emeryville. The area covered by the WUI is six times larger than the VHFHSZ and covers twice as many cities. Figure 4.4 and 4.5 display the relationship between the number of Single Family Residential Parcels and the amount of property taxes collected. The total a r ea occupied by the WUI and VHFHSZ is also indicated in these two figure. 48

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Figure 4.4. The WUI level scatter plot of Single Family Residential Parcels by the total taxes. As indicated in the legend, the size of the area is indicated by the size of the square. Figure 4.5 The VHFHSZ level scatter plot of Single Family Residential Parcels by the total tax. As indicated in the legend, the size of the area is indicated by the size of the square. 49

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From these two figures, it is possible to observe the following patterns. First, as the number of parcels increases so does the amount of tax collected. Second, as the size (total area) of the city increases, so does the number of Single Family Residential Parcels and the amount paid in property tax. This relationship is very clear with the units located in the VHFHSZ; however in the WUI, this relationship does not follow the same pattern. For example, Oakland occupies a smaller area than Fremont but contains more parcels and raises more tax revenue, while Berkeley is one of the smallest cities (in terms of its area) but draws the 4 th highest amount in property taxes. Part 3: The VHFHSZ and the Non-VHFHSZ Five cities in Alameda County contain a portion of the VHFHSZ, but the size of that area and the number of parcels contained in these areas varies greatly between cities (Table 4.2). The percentage of a city that is covered by the VHFHSZ also varies according to the location of the city. First are Oakland and Berkeley with 25% and 20%, respectively, then Piedmont with 8% and finally Pleasanton and San Leandro with 2% each. Based on these data, we can make the following observations. First, the average per capita property tax (e.g., the "mean" calculated by dividing the total amount of tax collected by the number of parcels) of Single Family Residential Parcels in the VHFHSZ is more than the average property tax of Single Family Residential Parcels in the NonVHFHSZ. Second, the mean property tax for the Single Family Residential Parcels is more variable (based on the dispersion of the values from the mean SD) in the VHFHSZ than in the Non-VHFHSZ. Third, Piedmont and Pleasanton have the highest average 50

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property tax in the VHFHSH; in the case of the Non-VHFHSZ Piedmont leads, with almost 50% more than the others. As discussed previously, the VHFHSZ is the area most vulnerable to fires in Oakland, and this analysis divides the city in two areas, VHFHSZ and non-VHFHSZ. That said, this section examines the different factors that can shape the relationship between the number of Single Family Residential Parcels and the amount collected in property tax within these two areas. Table 4.2 : Total property taxes collected 2013 within the VHFHSZ in each of the incorporated cities of Alameda County. Based on the data collected for the city of Oakland (Table 4.3), it was possible to observe the following patterns. First, 29% of Oakland's territory is located in the VHFHSZ which corresponds to 25% of all Single Family Residential Parcels. In contrast, 75% of the Single Family Residential Parcels are located in the Non-VHFHSZ (Table 4.3). Second, 40% ($104 Millions) of the property tax in the city is paid by people who live in the VHFHSZ and the remaining 60 % ($153 millions) by the people that live in the Non-VHFHSZ areas (Table 4.3). Third, based on the box-and-whiskers plot of the 51

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distribution of the property taxes for the Single Family Residential Parcels in Oakland (Figure 4.4), the people that live in the VHFHSZ pay higher taxes than the ones living in the Non-VHFHSZ based on the size of the boxes and the median line. Furthermore, the VHFHSZ presents a higher distribution (or spread of the values) than the Non-VHFHSZ. That said, it is important to consider that the citywide and the Non-VHFHSZ distributions are similar because there are three times more in the Non-VHFHSZ than in the VHFHSZ (i.e., the Non-VHFHSZ sample represents a much larger fraction of the total number of houses in the city). Figure 4.6 Box-and-whiskers plot of the distribution of the property taxes for the Single Family Residential Parcels Residential Parcels in Oakland based on location of the property. The light and dark grey boxes indicate the middle quartiles (2nd and 3rd quartiles, respectively) containing one quarter of the data each. The middle line in between the two boxes indicates the median of the data. Finally the top and bottom are the 1st and 4th quartiles, respectively, holding one quarter of the data each. The end of the top and bottom lines indicate the maximum and minimum number. 52

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Question 2: How does Proposition 13 affected Oakland's capacity to collect money from property taxes in the VHFHSZ and Non-VHFHSZ? Before 1978, the property values were sky rocketing in California Proposition 13 limited the amount of property taxes that can be collected. As a result, assessed property values dropped and taxes accrued at a rate well below inflation. This situation created an uneven distribution of home values and the concomitant property tax that could be collected even between immediately adjacent properties. Proposition 13 affected Oakland's capacity to collect money because it limited the assessment value of a property, only allowing for the property to update its price when the property changed owner or the property underwent major renovations resulting in an increase in value. Since the capacity to collect money is based on the year of purchase and the cost paid, I examined the two criteria to see if there is any relationship for the distribution of the two. Part 1: Property Value Oakland's property value distribution varies according to location (based on social and economic variables not analyzed in this thesis) and the time when the property was last sold or reassessed. The Hot Spot analysis indicates the distribution of single family residential parcel based on the value of the home (Figure 4.7). The map indicated what we already know, two concentrations, one of the properties of high value' and the other low value'. The a great portion of the distribution of properties of "high value' overlaps (as it was expected) with the Hills and the value of the home (Figure 4.7). The map indicated what we already know, two concentrations, one of the properties of high value' and the other low value'. 53

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Figure 4.7 Map of distribution of Oakland's single family units based on the Asses value of the home. The hot spots (red) in the map indicate the areas were 90% (or more) of the single family units pay high value' for there property. In contrast the cold spot indicate the areas were 90% (or more) of the single family units pay low values'. The high and low values are calculated by using the value of total value of the house and comparing it to the rest of the values. The areas that are in white indicate that there is a high variability between the property values. The a great portion of the distribution of properties of "high value' overlaps (as it was expected) with the Hills and the VHFHSZ. Although, not all the Hills indicate the presence of high values', the southern portion of the Hills is designed to not significant, and small part (west of the Hills, next to Piedmont) present high value' properties. An 54

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interesting result is the middle portion (white), this area does not contain hot/cold spot, which indicates that there is a high variability in the data (i.e great variation within the property values). To account for the already established social and economic dynamics of the city, I considered the median home value based on city tracts. A census tract is a geographic unit that groups people (between 1200 and 8000 people) of similar economic and social status used as a constant statistical subdivision of a metropolitan area. In order take in consideration the high variability of property values based on the location (i.e. the average cost of a house in the hills is $900,000 and in the Flatland is $400,000), I compared the census tract median home value to the total value of each single family units (Figure 4.8). The resulting values indicated, the percentage from which the properties were under value based on tract's median home value. Different from what it was expected, the Hills presented property values closer to the tract median home value. Different from what it was expected, the Hills presented property values closer to the tract median home value. In contrast, the Flatlands indicated that there are a greater number of properties that are far away from the tract median home value. However, the map does not indicate the number of houses paying below the median home value, but shows the percentage difference of the houses paying below the median home value. This said, the distribution of percentages can be the result of high variability in prices in the Non VHFHSZ. 55

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Figure 4. 8 Map of the distribution of the comparison between values for the Oakland's single family units. This map in percentages the comparison between the property value and the tract median home value. The higher the percentage the more difference between the property value and the median home value. This map indicates that in the Hills all of the property values are closer to the tract median home value. In contrast, the Flatlands indicates that there is greater number of properties that are farther away from the tract median home value. This map does not indicates the number of houses paying below the median home value, it shows the percentage difference, of houses paying below are paying a higher percentage than the Hills. Part 2. Year of the Property Reassessment Value Using the reassessed year value we can see when houses were bought in the VHFHSZ and Non-VHFHSZ. The information about year of purchase for Oakland is 56

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summarized in Table 4.5 and it indicates the following. First, since 2010, 30% of the houses in VHFHSZ and 28% in the Non-VHFHSZ were bought or reassessed in value. Second, from 2000 to 2013, 74 % of the houses in Oakland were reassessed in value to bring it up to date. Third, since 2000, one quarter of all of the properties in Oakland were bought in the VHFHSZ and the rest in the Non-VHFHSZ, which makes sense since 25% of the single family residential parcels are located in the VHFHSZ. Fourth, there is a slightly higher percentage of houses that were bought between 1960 and 1980 in NonVHFHSZ. Finally, based on the number of single family residential parcels, there is no real difference between the houses bought in the VHFHSZ and the Non-VHFHSZ. Table 4.3 Distribution of property last date of purchase or reassessed value based on year and location (VHFHSZ and Non-VHFHSZ). The distribution of property values based on the year the property was last bought or reassessed and its location help illustrated a more complete picture of the home values (Figure 4.6). The graph indicates, first, that the mean in the VHFHSZ is significantly higher than the mean in the Non-VHFHSZ area. Second, there is a weak relationship between the cost of the property and the year the house was bought and this is indicated 57

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by the low R-squared value. The reason behind this is that values are clustered to the upper left corner of the graph, indicating that we are not seeing a correlation so much as a bounding or limiting effect of year of property value adjustment. In conclusion, the year a house was bought does not linearly determine the value of that house today, but it certainly limits the maximum value that house will have. The more recently a house was reassessed in value, the higher the maximum price of that house, so basically newer houses can be a lot more valuable and generate more tax revenue that houses that were bought many years ago. Figure 4.6 Box-and-whiskers plot of the distribution of Single Family Residential Parcels Residential Parcels property taxes in Oakland, CA based on the year the property was purchased. U sing the information provided in the last year of reassessment of the property, I mapped the geographic distribution of the properties. The results show an even distribution throughout the city, with no clear concentrations (or hot spots). Give large 58

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size of the dataset, the end result did not create a intuitively clear distribution which is why the map was not included in the results. In order to see is there was an statistical significant between the two samples (or not), I used an unpaired (two sample) t-Test to take in consideration the difference in sample size. The t-test aimed to compared the price of the houses bought in the last 10 years (2003 to 2013) to the ones bought before (1950 to 2002) in the VHFHSZ and the NonVHFHSZ. The results indicated that there was no significant difference between new houses bought in the VHFHSZ (A1) and the NonVHFHSZ (A2), also, that there was no significant difference between older houses bought in the VHFHSZ (B1) and the NonVHFHSZ (B2). Table 4.4 Descriptive statistics for the VHFHSZ and Non-VHFHSZ based on the date of purchase / reassessed in value (newreassess in value during the last 10 years ; old reassessed in value more than 10 years ago). The properties bought in the last 10 years in the VHFHSZ and the NonVHFHSZ present not significant difference between the two, using a width of the Confidence interval of 95% (z) and the resulting confidence interval was 1.96 for both t-test. The results for the confidence interval were same for the houses purchased in the last 10 years in the VHFHSZ and the NonVHFHSZ, which means that the difference between the two was not significant. The test also indicated that the value of t-difference for the houses Type Mean Count ST A1 VHFHSZ / New 518,894 10,384 359,644 A2 NonVHFHSZ / New 249,759 32,514 240,746 B1 VHFHSZ / Old 340,164 5,293 260,945 B2 NonVHFHSZ / Old 165,182 17,347 158,604 59

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bought in the last 10 years was 71.324 and slightly lower (46.249) for for the houses bought more than 10 years ago. 60

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CHAPTER V DISCUSSION Introduction The key working hypothesis of this thesis is that the development of cities in Alameda County particularly in Oakland appears to have served as a tool to increase tax revenue, a process that potentially allowed certain segments of the population to benefit more than others from the system. To test the hypothesis, the analysis was divided into two parts: 1. How do the VHFHSZ and Non-VHFHSZ differ in terms of how much tax revenue they generate in the various incorporated cities in Alameda County and in particular in Oakland? 2. How has Proposition 13 affected Oakland's capacity to collect money from property taxes in the VHFHSZ and Non-VHFHSZ? Key Findings This section summarizes important findings from a detailed analysis of a dataset from Alameda County's Secured Roll Assessor for FY2012/2013. Comprising almost half a million records, this dataset contains information on location, property value and land use type, among other things. Using ArcGIS, I was able to spatially reference the location of houses and whether or not they are located in the VHFRSZ and/or the WUI. It also allowed me to visually map out the spatial distribution of Single Family Residence 61

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Parcels within the city. The following are the key conclusions reached as a result of this methodology: 1. The Fire Hazard Severity Zone is a designation to identify areas susceptible to fire for the State Responsibility Areas (SRA). These hazards zones are assigned to one of three levels: moderate, high, and very high. CalFire has encouraged local agencies (i.e., cities) to incorporate these designations in their hazard prevention planning, especially the VHFHSZ. This area is defined by a complex model that takes in consideration vegetation, topography, weather, crown fire potential and ember production and movement (CalFire, 2015). Given that the VHFHSZ was created to measure the potential and likelihood of an area burning, this designation indicates an area's vulnerably to fire which explains why the analysis presented here used the VHFHSZ/Non-VHFHSZ distinction. 2. Residential parcels represent the vast majority of parcels in Alameda County, and about one quarter of them are located in Oakland. The amount of tax collected varies based on the number of parcels within a given city and their total area. For FY 2012/2013, the average tax per Single Family Residential Parcel (mean) was highly variable, ranging from a low of $2,403 in Emeryville to a high $ 9,482 in Piedmont, with Oakland falling between these extremes with a mean tax of $3,766. This wide spread also characterizes the dispersion of tax amount from the mean (i.e., SD). The standard deviation on the mean tax for all of Alameda County is largest in Oakland (SD = $3,848). 62

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3. In Oakland, 25% of Single Family Residential Parcels are located in the VHFHSZ, a broadly comparable figure to the 28% of the city that is located in the VHFHSZ. In contrast, 40 % ($104 Millions) of the property taxes in the city are paid by people who live in the VHFHSZ and the remaining 60 % ($153 millions) by the people that live in the Non-VHFHSZ areas. That said, in FY2012/2013, the mean payed in property taxes by the single family homes was $ 5997 in the VHFHSZ and $ 3006 in the Non-VHFHSZ. For the other concerned cities, the proportions are as follows: Berkeley, 20 % of the single family residential parcels in the VHFHSZ pay 25% of the tax; Piedmont, 8% pay 10% of the tax; Pleasanton, 2% pay 4% of the tax; and San Leandro, 3% pay 4% of the tax. These data are important because they show that, across the board, people who live in the VHFHSZ actually contribute more to the city budget than those who don't. A follow-up question that emerges from this observation, however, is whether Proposition 13 has allowed them to contribute as much as they can or should, or whether their tax contribution is somehow constrained by artificially low house prices. 4. The distribution of property values in Alameda is conditioned by the location of parcels and their year of purchase. In general, properties located in the VHFHSZ are more expensive than those located in the Non-VHFHSZ. At the same time, political circumstances like Proposition 13 have led more recent homebuyers to pay more in property taxes than older homeowners. These circumstances have directly affected the assessed value of houses in Oakland and in Alameda County, helping to perpetuate dynamics created by the division of the city between the Hills and the Flatlands which are further compounded over time, since the longer homeowners occupies their property, the 63

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less they will pay in property tax because the assessed value of the property will not have kept up with assessed value. These situation resulted in the residents of the Flatlands of Oakland to pay higher property tax rates relative to their income. Policy Implications Based on the results generated from the research of my thesis, this next section seeks to critically address a series of issues related to the topic of this research. The main goal is to contribute to the growing body of research focused on fire vulnerability in the area and to influence future discussions about hazard vulnerability. Vulnerability, a Dynamic Concept For the purpose of this thesis vulnerability refers to the hazard exposure based on the geographical location. Vulnerability in this thesis refers to the hazard exposure based on the geographical location. In the case of Oakland, according to CalFire, the area most vulnerable to fires is the VHFHSZ, located mainly in the eastern portion of the city along the Hills. For the purpose of this thesis, vulnerability to wildfires (metric) is defined by the structures exposed to fire and to a lesser extent the adaptive capacity of people that live/work in these structures. The concept of vulnerability is dynamic and encompasses multiples meanings based on the predisposition of a system and the capacity to adapt in the face of a hazardous event. This thesis defined vulnerability to hazards based on the level of exposure (geographical location), however, identifying vulnerable populations exposed to hazards it is not as clear cut as would first appears In the case of Oakland, socially 64

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marginalized communities are not located in the areas most exposed to fires, in fact the areas vulnerable to fire are occupied by the wealthiest members of the community. As a result, Oakland comprises two parallel societies that differ in social, economic and environmental characteristics, where one is exposed to hazard and the other is not. For this reason, it is important to take in consideration how the concept of vulnerability to hazards can manifests itself in different contexts and it can differentially affect distinct groups within a population. Social v ulnerability is the set of characteristics and circumstances of a community or a system that makes it susceptible to the damaging effects of a hazard (United Nation, 2009). In the case of Oakland, it is easy to assume that the people who live in fire-prone areas, that is, those whose houses and property will be destroyed and who might possibly lose their lives, are the only victims of the fire. However, this perspective overlooks other group who can be also affected by the fire even though they reside outside the hazardous area. In the case of Oakland, for instance, people in the Hills who live within the perimeter of the high fire risk area belong to very affluent communities and generally have health and property insurance and can apply the relief aid given by the government to recover from fires. In contrast, people in the Flatlands, compared to hill residents, provide a greater proportion of their income spent on property taxes (compared to the VHFHSZ). Thus, even though people living in the Flatlands may not have been affected directly by the fire burning the house, their capacity for resilience was affected by a portion of these revenues go to pay for fire protection, which is not something that flatland residents benefit from. This is unfair because many 65

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of the residents of the Flatlands are least able to afford higher tax rates, whereas more hill residents could probably afford slightly higher rates. Oakland's polarized population creates a dilemma on how to deal with other instances of social vulnerability to hazards. On the one hand, we have the people who live directly in the area affected by the hazard but have the economic resources and means to ultimately reduce their vulnerability while. On the other, there is a marginalized population that lives in areas less exposed to fires but also is less resilient to even minor problems like having to pay relatively higher property tax rates when compared to household income. The Limit that Guides Urban Sprawl The results indicated that the VHFHSZ generate a lot of money for cities through tax revenues. Together, the homes located in the VHFHSZ pay more in property taxes than other Non-VHFHSZ residents. In Oakland, 25% of single family residential parcels are located in the VHFHSZ, but these units are responsible for providing 40% of the property taxes in the area. Based on this numbers alone, it proves that the idea to expand the urban perimeter to increment the amount in property taxes worked for Oakland. However, to justify urban sprawl as a way to get more revenue through property taxes poses multiple problems, however. First, urban development relies on the local governments to provide public services from the taxes collected from these new developments, but often the real cost of providing public services (e.g. municipal services like police, water, streets, sanitation, public libraries), it is not covered fully by 66

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the taxes gathered (EPA, 2014; Brueckner, 2000; Burchell, et al., 2005).The idea that it is possible to collect more money thought property taxes to increase city budgets by developing new areas does not take into consideration the real cost of maintaining these new areas. Therefore, if the cost of maintenance of an area exceeds the revenue generated by the area, it defeats the purpose of building it up in the first place. The idea that land development occurs to boost city budgets to pay for city 'activities' (i.e. police, fire department) contradicts itself when the final cost of development increases when maintaining these areas is more costly (e.g. how can we justify building in areas that are vulnerable, when the cost of maintenance of these areas due to their vulnerability is much higher compared to the rest of the city?). Effective Tax System Finally, there is a need to define what constitutes a fair and appropriate taxation system. In the case of Oakland, the city effectively comprises two parallel societies that differ in their social, economic and political make-ups. As mention before, the Hills are exposed to fire and the Flatland is not and the Hills provide a larger contribution to property taxes (median home property tax is $5997) than the Flatlands ($3006 median). In order to provide a fair an efficient tax system, however, we need to take in consideration the high variation (e.g. between the Hills and the Flatlands) in Oakland for assessed property values. In addition, it is crucial to ensure that each unit located in the VHFHSZ and the Non-VHFHSZ carries their own weight to ensure their accountability (LAO, 2002). Finally, the cost of public services should be distributed equally; in this 67

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case, since fire defense is a significant portion of the city's budget, property taxes need to reflect the cost to fire protection for areas that are vulnerable. Future Research Future research should aim to calculate the potential amount in property tax that could be collected if all property values were up-to-date with the present-day market value of given properties. One way this could be done with the available data is by using the year of reassessment to create a backward calculation of the inflation rates. Other lines of future research also include calculating property assessed values datasets from various years in order to track those changes over the years. The WUI is not the best geographical indicator for measuring or assessing fire vulnerable areas. To date, much of the literature on fire vulnerability has equated the WUI with location for greater risk. The WUI is the area where were the urbanization expands into the intermingled and undeveloped wildland (Radeloff et al., 2005). However, it also encompasses various ecosystems like wetlands, grasslands and woodlands, not all of which are vulnerable to fire in the same way. Given that the WUI covers a large range of habitats and ecosystems, it is not the most precise manner of identifying vulnerable areas, which explains why it was not used in this thesis. To argue that because an area is WUI, it is therefore vulnerable (or should require analysis of vulnerability) takes focus away from the areas that are truly at high risk. Furthermore, to create rules (like building codes) for zones that are not WUI might be counterproductive since the WUI is highly variable 68

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ecologically, being defined first and foremost by the fact that it surrounds the periphery of a city. Limitations of the Study One of the limitations of the study was the lack of information in the dataset about the size of the properties and the number of homes within each parcel. These two data would have allowed me to develop a more complete picture of the structure of residential property tax. Finally, it would have been very useful to have comparable datasets from other years to calculate changes in property values, city budgets, and fire service budgets before and after the Tunnel Fire. 69

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REFERENCES Alameda County, California (2012). Tax Rate For the Fiscal Year 2012/2013. Retrieved from : https://www.acgov.org/auditor/tax/2012-13%20TaxRateBook.pdf Bankoff, G. (2006). The Tale of the Three Pigs: Taking Another Look at Vulnerability in the Light of the Indian Ocean Tsunami and Hurricane Katrina. Retrieved from: http:// understandingkatrina.ssrc.org/Bankoff/ Bankoff, G., Frerks, G., Hilhorst, D., (Eds.) (2004).Mapping Vulnerability: Disasters, Development, and People. Earthscan. Batty, M. (2008). The Size, Scale, and Shape of Cities. Science 319 (8) 796-771 Brueckner, J. K., Kim, H. (2003). Urban Sprawl and the Property Tax. International Tax and Public Finance Journal 10(1): 5-23 Bryant, R., and S. Bailey. 1997. Third World Political Ecology. London: Routledge. California Department of Forest and Fire Protection (CalFire). (2007). Fact Sheet: California's Fire Hazard Severity Zones. Office of the State Fire Marshal. Retrived from: http://www.fire.ca.gov/fire_prevention/downloads/FHSZ_fact_sheet.pdf California Department of Forest and Fire Protection (CalFire). (2011). CAL FIRE Jurisdiction Fires, Acres, Dollar Damage, and Structures Destroyed Retrived from: http:// www.fire.ca.gov/communications/downloads/fact_sheets/firestats.pdf California Department of Forest and Fire Protection (CalFire). (2015a). Top 20 Largest California Wildfires. Retrieve from: www.fire.ca.gov/communications/downloads/ fact_sheets/Top20_Acres.pdf California Department of Forest and Fire Protection (CalFire). (2015b). Top 20 Most Damaging California Wildfires. Retrieve from: http://www.fire.ca.gov/communications/ downloads/fact_sheets/Top20_Damaging.pdf California Department of Forest and Fire Protection (CalFire). (2015c).Top 20 Deadliest California Wildfires. Retrieve from: http://calfire.ca.gov/communications/downloads/ fact_sheets/Top20_Deadliest.pdf 70

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California Department of Forest and Fire Protection (CalFire). (2015d) Fire Hazard Severity Zones Maps. Retrieved from: http://www.fire.ca.gov/fire_prevention/ fire_prevention_wildland_zones City of Oakland California (2009) FY 2011-13 Adopted Policy Budget. Retrieved from: http://www2.oaklandnet.com/Government/o/CityAdministration/d/BudgetOffice/ Collins, T., 2005. Households, forests, and fire hazard vulnerability in the American West: a case study of a California community. Global Environment Change B: Environmental Hazards 6 (1) 2337. Collins, T., 2008. The political ecology of hazard vulnerability: marginalization, facilitation and the production of differential risk to urban wildfires in Arizona's white mountains. Journal Political Ecology 15, 2143. Dooling, S. and Simon, G. L. (2012). Cities, Nature and Development: The Politics and Production of Urban Vulnerabilities. Ashgate Publishing, Aldershot, UK. East Bay Regional Park District (n.d.). Fire History in the East Bay. Retrieved from: http://www.ebparks.org/Assets/_Nav_Categories/About_Us/Fire/History+All+Fires.pdf Federal Emergency Management Agency (FEMA). 1992. The East Bay Hills Fire Oakland-Berkeley, California. U.S. Fire Administration/Technical Report Series USFATR-060. Frenkel, A., Ashkenazi, M. (2008).Measuring urban sprawl: how can we deal with it? Environment and Planning B: Planning and Design. 35: 56-79 Hohle, R. (2015). Race and the Origins of the American Neoliberalism. Taylor and Francis Publisher. Insurance Information Institute. (2014). Wildfires. Retrieve from: http://www.iii.org/factstatistic/wildfires International Association of Willand Fire (IAWF). (2013). WUI Facr Sheet. Retrieved from http://www.iawfonline.org/pdf/WUI_Fact_Sheet_08012013.pdf Legislative Analyst Office (LAO). (2012). Understanding California's Property Taxes. Retrieved from: http://www.lao.ca.gov/reports/2012/tax/property-tax-primer-112912.pdf Liverman, D.M. (1990). Drought impacts in Mexico: climate, agriculture, technology, and land tenure in Sonora and Puebla. Annals of the Association of American Geographers 80 (1) 4972. 71

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National Fire Protection Association (NFPA).(2015). Home Structure Fires. Retrived from: www.nfpa.org/~/media/Files/Research/NFPA%20reports/.../oshomes.pdf Nechyba, T. J., Walsh, R.P. (2004). Urban Sprawl. Journal of Economic Perspectives 18(4):177200 Radeloff, V. C., Hammer, R. B., Stewart, S. I., Fried, J. S., Holcomb, S. S., And Mckeefry, J. F., ( 2005). The WildlandUrban Interface In The United States. Journal Ecological Applications, 15(3), 2005, pp. 799805 Robbins, P. (2002). Obstacles to a First World political ecology? Looking near without looking up. Environment and Planning A 34(8):1509-1513. Robbins, P. (2004). Political Ecology: A Critical Introduction. Malden, MA: Blackwell Publishing. Simon, G. L. and Dooling, S. (2013). Flame and Fortune in California: The material and political dimensions of vulnerability. Global Environmental Change-Human and Policy Dimensions 23(6): 1410-1423. Simon, G. L. (2014). Vulnerability-in-Production: A Spatial History of Nature, Affluence, and Fire in Oakland, California. Annals of the Association of American Geographers 104(6): 1199-1221. Sullivan, S and Stott, P (2000) Political Ecology: science, myth and power. Arnold Publication, London. Theobald, D. M. (2005). Landscape Patterns of Exurban Growth in the USA from 1980 to 2020. Journal Ecology and Society. 10(1): 32 Thomas, D. S. K., Phillips, B. D., Lovekamp, W. E., Fothergill, A. (2013). Social Vulnerability to Disasters, Second Edition. CRC Press US Census (n.d.). Quick Facts: Oakland City, California. Retrived from: http:// www.census.gov/quickfacts/table/PST045215/0653000,00 Watts, M. (2000). Political Ecology. In Sheppard, E. and T. Barnes (eds.), A Companion to Economic Geography. Blackwell. Blackwell Publishing Wisner, B., Blaikie, P., Cannon, T., Davis, I.(2004). At Risk: Natural Hazards, People's Vulnerability and Disasters, 2nd ed. Routledge, London. 72

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APPENDIX A 73 Property Assessment Information Code Description 00 999 Exempt, Not Assessed by County, Mobile Homes and Tracts 1000 1999 Single Family Residential 2000 2999 Multiple Residential, 2-4 Units and Mobile Homes 3000 3999 Commercial (See also 8X & 9X Series) 4000 4999 Industrial 5000 5999 Rural 6000 6999 Institutional 7000 7999 Multiple Residential, 5 or more units 8000 8999 Improved Commercial 9000 9999 Improved Commercial

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! 74 Description of Single Family Categories 1000 1000 Single Family Residential Vacant residential land, zoned 4 units or less 1040 Vacant residential land, R&T 402.1 1100 Single 1101 Medical-Residential 1120 Residential 1130 Residential 1140 Single family residential home, R&T 402.1 1150 Historical 1190 Single 1200 Single 1300 Single 1400 Single 1420 Single Family Res Duet Style, First Sale 1430 Single Family Res Duet Style, R&T 402.1, First Sale 1440 Single Family Res Duet Style, R&T 402.1 1500 Townhouse 1505 Townhouse 1520 Townhouse Planned Development, First Sale 1525 Townhouse Style Condominium, First Sale 1530 Townhouse Planned Development, R&T 402.1, First Sale 1535 Townhouse Style Condominium, R&T 402.1, First Sale 1540 Townhouse Planned Development, R&T 402.1 1545 Townhouse 1590 Townhouse Planned Development, Common Area or use 1595 Townhouse Style Condominium, Common Area or use 1600 SFR 1620 SFR Detached Site Condominium, First Sale 1630 SFR Detached Site Condominium, R&T 402.1, First Sale 1640 SFR Detached Site Condominium, R&T 402.1 1690 SFR Detached Site Condominium Common Area or use 1700 Single 1800 SFR 1820 SFR Planned Development Tract, First Sale 1830 SFR Planned Development Tract, R&T 402.1, First Sale 1840 SFR Planned Development Tract, R&T 402.1 1890 SFR Planned Development Tract, Common Area or use 1900 Single 1901 Single

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APPENDIX B City Primary TRA Secondary TRA Tax Rate Alameda Island 21 0, 2-7, 1.1409 1 1.2240 Albany 22 0, 1 1.3814 Berkeley 13 0-5 1.2472 Dublin 26 0-18, 20-23, 25-31, 33-43 ,401, 700 1.1534 19 1.1237 24 1.1148 32 1.1483 Emeryville 14 0, 1, 3, 4, 6 1.1259 2, 5 1.1980 Fremont 12 1-4, 6-24, 28-53, 55, 56, 58-62, 64-68, 70-73, 75, 77, 78, 80 -84, 86, 89-92, 94-115, 117-144, 146-165, 167-196, 198-204, 206-213, 206-213, 215-217, 220-229, 231-247, 480 1.1241 5, 54, 57, 63, 69, 74, 79, 85, 87, 88, 93, 116, 197, 205, 214, 219, 230 1.1172 25, 26, 27, 219 1.1076 76 1.1400 145 1.1255 166 1.1027 800, 812, 873 1.0897 Hayward 25 0, 4, 5, 7, 11-15, 20, 21, 34, 48, 64, 73, 97-99, 102, 103, 116, 117, 121, 122, 124, 149, 150, 169, 172, 197, 202, 214-216, 236, 1.1423 1-3, 6, 8-10, 16-19, 22-30, 32, 33, 35, 36, 42-47, 50-56, 60-63, 65-70, 74, 75, 77, 84, 86, 87, 95, 96, 101, 104, 107, 109, 110, 112, 113, 114, 118, 125, 126, 128-148, 155-163, 165-168, 170, 171, 173-196, 198-201, 203-208, 211-213, 217-224, 226-230, 232-235, 237-240, 402, 426, 430, 477 1.0866 31, 37, 39, 49, 59, 85, 92, 93, 225, 231 1.1879 38, 83 1.1698 40, 89, 91, 94, 111 1.1948 41, 76, 80, 81, 127 1.0935 57, 58, 78, 209, 210 1.1047 71, 72 1.1276 75

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79 1.1116 82, 119, 120 1.1504 88, 90, 151, 152, 164 1.1237 100 1.1465 105, 106, 108 1.0935 115 1.1646 123 1.1492 153, 154 1.1418 Livermore 16 0-42, 44-51, 53-69, 71-77, 81, 82, 84-86, 88-94, 96-99, 401, 464, 700 1.1097 43, 52, 70, 78, 80, 83, 87, 95 1.1148 79 1.1504 Newark 11 1-50 1.2026 Oakland 17 1, 11-14, 16, 19-22, 24-27, 30-33, 36-38, 41-47, 401 1.4057 5, 17-18, 34, 35 1.3475 6, 7 1.3500 8, 28 1.3226 9 1.2943 10, 15 1.3543 23 1.3382 29 1.4079 39, 40 1.3314 Piedmont 18 0 1.2125 Pleasanton 19 0-14, 17-19, 22, 23, 25, 28, 29, 31-66, 75-101, 105-107, 109-121, 126, 400, 700, 731, 1.1504 15, 16, 20, 24, 26, 27, 30, 67-74, 122, 123 1.1534 103 1.0980 108, 124, 125 1.1148 804 1.0826 San Leandro 10 1-5, 7-10, 12-16, 18-20, 22, 24-26, 30, 32-36, 38-42, 45, 48, 50, 54, 57, 61-64, 66-68, 73, 74-75, 77-81, 83-85, 88, 90-100 1.1398 6, 11, 17, 21, 23, 27, 28, 31, 37, 43, 49, 53, 60, 65, 71, 72, 76, 82, 86, 87, 89 1.1423 29 1.1466 76

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Union City 15 1, 2, 4, 6-9, 11-13, 15, 16, 18-22, 24, 26, 28, 30-32, 34-36, 38, 41, 42, 45-48, 50, 51, 53, 60, 61, 63-65, 67, 69-79, 81-83, 86, 88-91, 97, 463, 1.1948 3, 5, 10, 14, 25, 29, 33, 39, 44, 52, 54-58, 84, 85, 87, 93-96 1.2113 17, 37, 49, 80, 1.0935 23, 43, 59, 62, 68, 462 1.1879 27 1.2107 40 1.1147 66 1.0866 800, 821 1.1604 77