a spatial analysis of property tax revenue and fire...
TRANSCRIPT
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
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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
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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 County.
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-
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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
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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.
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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.
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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 ……………..……… 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
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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 ……………………………………………………………. 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
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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
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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 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
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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 county- and 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
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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
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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
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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
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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
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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 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 area’s vulnerability to wildfires as well as another piece of
evidence that human factors contribute to producing this vulnerability.
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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,
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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 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 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,
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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 south-
east, 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
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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
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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.
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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 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
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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
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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 .
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Figure 1.5 Illustration of the division between county- and 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.
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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
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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, the 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)
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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?
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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
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
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
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
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
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
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
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
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
24
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
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
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
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
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
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
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
"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/Non-
WUI and within the VHFHSZ/Non-VHFHSZ); (c) The year the structure was last
32
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
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 field named “GisJoin”.
Layer Source Original ProjectionCounty 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
* * 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
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
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.
37
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” + TaxEx: OaklandTax
- Joins and Relates >> Join (joined tax dataset to the “City” layer using the field “GisJoin”.- Export the layer
City outline, parcels and tax information.
c“Name of city” + WUIEx: 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” + NONWUIEx: 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” + VHFHSZEx: 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”+ NONVHFHSZEx: 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.
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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 under- or over-
paying 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
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
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
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 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
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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
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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
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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
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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).
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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
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.
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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.
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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 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.
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
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.
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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’.
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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
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
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
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).
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 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.
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 (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 (new- reassess 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
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
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
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).
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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
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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
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.
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
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 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
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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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APPENDIX A
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Property Assessment Information
Code Description00 – 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 Industrial5000 – 5999 Rural6000 – 6999 Institutional7000 – 7999 Multiple Residential, 5 or more units 8000 – 8999 Improved Commercial 9000 – 9999 Improved Commercial
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Description of Single Family Categories
1000
1000
Single Family Residential
Vacant residential land, zoned 4 units or less1040 Vacant residential land, R&T 402.11100 Single1101 Medical-Residential1120 Residential1130 Residential1140 Single family residential home, R&T 402.11150 Historical1190 Single1200 Single1300 Single1400 Single1420 Single Family Res - Duet Style, First Sale1430 Single Family Res - Duet Style, R&T 402.1, First Sale1440 Single Family Res - Duet Style, R&T 402.11500 Townhouse1505 Townhouse1520 Townhouse - Planned Development, First Sale1525 Townhouse Style - Condominium, First Sale1530 Townhouse - Planned Development, R&T 402.1, First Sale1535 Townhouse Style - Condominium, R&T 402.1, First Sale1540 Townhouse - Planned Development, R&T 402.11545 Townhouse1590 Townhouse - Planned Development, Common Area or use1595 Townhouse Style - Condominium, Common Area or use1600 SFR1620 SFR Detached Site Condominium, First Sale1630 SFR Detached Site Condominium, R&T 402.1, First Sale1640 SFR Detached Site Condominium, R&T 402.11690 SFR Detached Site Condominium , Common Area or use1700 Single1800 SFR1820 SFR - Planned Development Tract, First Sale1830 SFR - Planned Development Tract, R&T 402.1, First Sale1840 SFR - Planned Development Tract, R&T 402.11890 SFR - Planned Development Tract, Common Area or use1900 Single1901 Single
APPENDIX B City Primary TRA Secondary TRA Tax Rate
Alameda Island21 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
Emeryville14 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
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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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
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