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University of Southern California Dissertations and Theses
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Suitable California Opportunity Zone (COZ) locations for affordable housing development in the cities of Bakersfield, Los Angeles, and Palmdale
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Suitable California Opportunity Zone (COZ) locations for affordable housing development in the cities of Bakersfield, Los Angeles, and Palmdale
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Content
Suitable California Opportunity Zone (COZ) Locations for Affordable Housing Development in
the Cities of Bakersfield, Los Angeles, and Palmdale
by
Andre Charles McClure
A Thesis Presented to the
FACULTY OF THE USC DORNSIFE COLLEGE OF LETTERS, ARTS AND SCIENCES
University of Southern California
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(GEOGRAPHIC INFORMATION SCIENCE AND TECHNOLOGY)
May 2021
Copyright © 2021 Andre Charles McClure
ii
Dedication
Dedication to my parents from whom I received my drive and dedication.
iii
Acknowledgements
I would like to acknowledge Professor Bernstein for her direction, insight, and patience as well
as the other committee members for their input during this thesis process. Furthermore, I would
like to thank the Military Intelligence community for providing me with the knowledge to
develop a passion for Geospatial Information Science.
iv
Table of Contents
Dedication ii
Acknowledgements iii
List of Tables vi
List of Figures vii
Abbreviations viii
Abstract ix
Chapter 1 Introduction 1
1.1. Addressing the Housing Burden Affecting the Low-Income Population 3
1.2. COZs and Suitable AH Locations 4
1.3. Motivation and Research Objectives 5
1.4. Thesis Structure 6
Chapter 2 Background and Related Work 8
2.1. Social Housing Designations 8
2.2. Decrease in Number of Affordable Housing Units 8
2.3. The Affordable Housing Crisis in the City of Los Angeles 9
2.4. State of California 9
2.5. California Opportunity Zones (COZs) 10
2.6. The Role of Public Transit 11
2.7. The Role of the U.S. Department of Housing and Urban Development 12
2.8. Role of Income 13
2.9. The Role of the Rent Burden 13
2.10. Summary 13
Chapter 3 Research Methods and Data 16
3.1. Geospatial Data 16
3.2. Hard Criterion 17
3.3. Soft Criteria 18
Median Income 19
Census tracks 19
3.4. GIS Analysis and Modeling 20
v
Chapter 4 Results 23
4.1. Current COZ Locations in Three Study Cities 23
4.2. Conceptualization of Specification of Criteria Used to Find Candidate AH Areas 23
4.3. Final Weighted Overlays 24
Chapter 5 Discussion and Conclusions 30
5.1. Weighted Overlay Findings 30
5.2. Limitations 31
5.3. Recommendation for Future Study Enhancements 31
vi
List of Tables
Table 1. Feature Data Source Information 17
Table 2. Feature Metrics Criteria 19
Table 3. Model Builder Processing Tools 21
vii
List of Figures
Figure 1. Study Area Overview Map 2
Figure 2. Percentage of California residents seriously considering moving because of housing
costs. Source: PPIC (2017) 4
Figure 3. California Opportunity Zone (COZ) maps for the cities of Bakersfield, Los Angeles
and Palmdale 18
Figure 4. Analysis Combined with Model Builder to Produce Weighted Overlay 20
Figure 5. Criteria Feature Calculation for the City of Bakersfield 24
Figure 6. Weighted Overlay Results for the Cities of Bakersfield, Los Angeles, and Palmdale 25
Figure 7. AH Opportunities in the City of Bakersfield 27
Figure 8. AH Opportunities in the City of Palmdale 28
Figure 9. Weighted Overlay Results for the city of Los Angeles 29
viii
Abbreviations
AEI Administrative Enforcement Initiative
AH Affordable Housing
AOI Area of Interest
AVTA Antelope Valley Transit Authority
CADRG Compressed ARC Digitized Raster Graphics
COZ California Opportunity Zone
EOI Education and Outreach Initiative
EDD Employment Development Department
FHIP Fair Housing Initiatives Program
FHOI Fair Housing Organizations Initiative
FIPS Federal Information Processing Standards
GIS Geographic Information System
HUD U.S. Department of Housing and Urban Development
HSRT High- Speed Rail Terminal
LIHTC Low-Income Housing Tax Credit
NAD North American Datum
PEI Private Enforcement Initiative
PPIC Public Policy Institute of California
TRN Transit Rich Neighborhoods
VMT Vehicle Miles Traveled
ix
Abstract
California Opportunity Zones (COZs) provide tax incentives to investors and developers who are
interested to build housing units containing affordable housing (AH). The population in
California continues to increase while the cost of housing has increased significantly due to high
demand. Low-income populations lack access to AH and this contributes to the financial burdens
of residents who are working but cannot afford where they live. The cost of homes and rent is
rising faster than the wages earned by those who work full time at minimum wage. This thesis
analyzes demographic data from the U.S. Census and other sources using geospatial and
statistical methods to propose new COZs in the cities of Bakersfield, Los Angeles, and Palmdale.
The ideal locations for newly designated COZs would have lower population densities than
much of the city of Los Angeles and labor opportunities that do not require higher education or
training and that can be accessed via public transportation. The geographic placement of AH is
critical to the potential positive impact on low income communities. A weighted overlay model
was used to determine site suitability within each city based on features related to desirable
characteristics. The new zones will provide economic opportunities for residents, alleviate
problems related to population density and overcrowding, and improve the quality of life for not
only low income populations but also the cities as a whole.
1
Chapter 1 Introduction
Affordable Housing (AH) is designed to provide medium to low-income individuals with access
to housing commensurate with their income. The U.S. Department of Housing and Urban
Development (HUD) sets income limits to determine eligibility for assisted housing. “For
extremely low-income households (those earning 30% of area median income or less), the
housing choices were even more limited. In 2013, 11.2 million extremely low-income
households competed for only 7.3 million affordable units, implying a significant supply and
demand imbalance” (Colburn and Allen 2018, 228). This leaves many people who are employed
but in poverty without a stable home to live in or homeless. The California State Government
recognizes the importance of AH, and in 2017 Governor Brown signed 15 Bills into law such as
Assembly Bill 73 and Senate Bill 540 which provide incentives to cities who plan new
development and designate 20% of the dwelling units to middle and low-income residents. These
bills were designed to fund new construction and restoration projects that provide low-income
housing. Even with new regulations and funding provided by the state and certified by the
Secretary of the U.S Treasury in April 2018, there is still a lack of AH (Kimberlin 2017). The
dilemma that persists for developers and government officials is that real estate values are too
high and new locations for developing AH are minimal in the city of Los Angeles (Tax Policy
Center, 2020).
This thesis provides a Geographic Information System (GIS) analysis of potential low-
income housing development locations in the cities of Bakersfield, Los Angeles, and Palmdale
(Figure 1). These three cities were chosen based in part on their proximity to each other and their
need for AH. The supply of AH within the city of Los Angeles, California cannot accommodate
the thousands of eligible recipients. The 2017 laws designated selected census tracts as
2
California Opportunity Zones (COZs). These COZs are defined by the Internal Revenue Service
(IRS) as economically distressed communities where new development and revitalization are
eligible for preferential treatment via IRS Code Section 45D(e) (Tax Policy Center, 2020). The
dilemma that persists for developers and government officials is that real estate values continue
to rise and new locations to develop low income housing are limited in the city of Los Angeles
and surrounding cities such as Bakersfield and Palmdale. In addition, AH cannot be forced on
property owners of high-value land and some of the working residents in large cities such as Los
Angeles end up homeless and destitute.
Figure 1. Study Area Overview Map
3
The need for AH is prevalent and acknowledged by the citizens of California. Based on
the Public Policy Institute of California (PPIC) Statewide survey taken in 2017, 60% voted in
favor of changing California’s environmental regulations and permitting processes to make
housing more affordable for those in need.
The use of land in opportunity zones designated by the state of California influences
society’s potential for growth and development by offering tax incentives to build AH in these
locations (Wardrip et al. 2011). The planning, design, and construction of AH can potentially
improve the lives of residents and the people who live in surrounding areas. The high demand for
AH and the financial benefit for developers could spur economic growth, so long as the AH is
located in areas that can sustain low income populations currently living and working in small
(Bakersfield and Palmdale) and large (Los Angeles) cities.
1.1. Addressing the Housing Burden Affecting the Low-Income Population
HUD defines AH as a dwelling that is designated for those who are in the low to medium
income bracket for their region (HUD Public Affairs, 2020). The low-income dwelling can be
obtained for 30 percent or less of a low-income worker’s salary. Accessibility to AH is a major
topic in Los Angeles, as there is a high demand for low-income homes. The cities of Bakersfield
and Palmdale can sustain more AH at a lower cost and provide access to long-term employment.
A high cost of living causes those who are not homeless to suffer financial burdens,
rendering them unable to break out of increasing debt. A survey conducted by PPIC (2017)
suggests that nearly one-in-three renter households spend at least half of their income on rent.
The survey further shows that because of their status, many of those who are older or who
support family members cannot relocate easily (Figure 2).
4
Figure 2. Percentage of California residents seriously considering moving because of housing
costs. Source: PPIC (2017)
While Figure 2 represents people potentially leaving the state, this is not always an option
for those living in low-income housing. The survey results show attitudes and potential moves.
This study provides an in-state solution for development of AH so that low-income populations
can maintain residence in California but in alternative locations where more affordable housing
and employment opportunities exist. The low-income homeless population has access to shelters
and social services in the city of Los Angeles. Large cities also provide employment
opportunities, but the high cost of living can quickly offset the opportunities for gainful
employment (PPIC 2017). The chart reproduced in Figure 2 shows the strain that housing cost
has on different age groups. Without greater opportunities for employment outside of major
cities or reliable transportation over short and long distances on a daily basis, low-income
communities will struggle financially.
1.2. COZs and Suitable AH Locations
This thesis determines the accessibility of AH in two cities near Los Angeles. The cities
of Bakersfield and Palmdale provide potential locations where AH can be developed to
accommodate those who are working but unable to rise above extreme poverty. Public
transportation in these cities may support low-income populations working locally or commuting
5
to urban areas like Los Angeles for work while maintaining residences in nearby cities that have
a more affordable cost-of-living.
COZs are designated to encourage developers to build new AH developments to address
and assist disadvantaged low-income communities. COZs not only provide tax incentives for
AH, but they also allow the city to receive new tax revenue and revitalize distressed areas within
the COZs. Developers and investors are encouraged to build and refurbish housing in these
locations to spur economic growth and provide AH. According to the Tax Cuts and Jobs Act of
2017, the reinvestment of capital gains from investors and sizable tax incentives are used to
improve distressed neighborhoods in opportunity zones. In California, opportunity zone real
estate has successfully seen a boost in investment and this increased investment has extended to
even the most distressed areas of the state (Miller, 2019). A number of financial lenders and
developers in California contribute to potential development within COZs. These organizations
focus on economic, social, and environmental impacts as they develop AH and other types of
infrastructure in these zones.
1.3. Motivation and Research Objectives
AH is a major issue in Los Angeles, California because of the high demand for low cost
housing. This thesis project is important because it addresses the basic need for housing and
shelter. The motivation for this study is to explore possible locations for low-income populations
to live, work, and build community. Other states could utilize the model presented in this thesis
project and apply it to their cities in order to increase AH accessibility. The AH crisis is
detrimental to the low income community in Los Angeles who are mired in poverty and may
become homeless. The rent burden may lead to low income communities spending less money
on basic necessities such as food and health care (Colburn and Allen 2018).
6
This thesis sought to determine possible locations where AH can be provided to those
who need it, with access to transportation in order to find and maintain a job in one or more of
the cities of Bakersfield, Los Angeles, and Palmdale. Given this goal, the thesis tackles three
questions:
1. Where are the existing COZs in the cities of Los Angeles, Palmdale and
Bakersfield?
2. What criteria should be used to determine suitable locations for AH?
3. What areas provide the most suitable AH based on the aforementioned criteria
and are some of those locations located outside the existing COZs?
Based on a thorough review of the literature, which will be discussed in more depth in
Chapter 2, a number of features were identified to determine the suitability of a location for AH.
These criteria include variables related to median income, public housing and transportation. It is
expected that areas with the highest suitability score based on these features are ideal locations
for potential AH development. It is argued that AH development in these locations would help
alleviate issues of overpopulation and homelessness in the Los Angeles area. The site suitability
of locations is conducted using a weighted overlay model. This suitability model’s objective was
to identify locations for AH development that are not part of the existing COZs. The cities may
want to promote AH in these areas by asking the state to designate these as new COZs since this
would provide tax incentives for developers and increase the availability of AH.
1.4. Thesis Structure
The remainder of the thesis consists of four chapters. The second chapter provides
additional background and reviews related work. The third chapter describes the methods and
data used. The fourth chapter presents the results. The fifth and final chapter summarizes the
7
major findings and suggestions for future work on affordable housing opportunities in California
and other parts of the country.
8
Chapter 2 Background and Related Work
This chapter reviews findings from other studies and articles related to site suitability analysis as
it relates to the placement of COZs and AH. The sections which follow review conditions of
people in low income communities, the problems faced by the developers of AH and possible
solutions that have been developed to overcome these issues.
2.1. Social Housing Designations
The term AH refers to rentals which can be privately owned, managed by the state, non-
profits organizations, and/or developers. The LIHTC which was created under the Tax Reform
Act of 1986, provides tax credits for the development of AH (Tax Policy Center 2020). The
COZs are designated by the Governor of the state of California and certified by the Secretary of
the U.S. Treasury. COZs provide developers of AH with tax incentives. HUD housing locations
are also often placed within the COZ designations.
2.2. Decrease in Number of Affordable Housing Units
In Los Angeles County, state funding decreased 15% while federal funding increased
68% for housing production and preservation from FY 2008-2009 to FY 2018-2019. However,
nearly half a million low-income renter households in the county do not have access to an
affordable housing (Schwartz 2020). Many neighborhoods in the city of Los Angeles, for
example, that once housed low-income residents, have undergone gentrification and
revitalization. These changes caused AH unit decreases as well as adverse effects on the cost of
living of many residents. Many households experience rent burdened based on the rising cost of
living. The U.S. Federal Government and state of California have enacted new laws aimed at
financial developers and city planners. Under the Federal Tax Cuts and Jobs Act, for example
9
COZs, can be designated to help provide a solution to the AH crisis. Their numbers and locations
are a key part of this study.
2.3. The Affordable Housing Crisis in the City of Los Angeles
Access to AH in the city of Los Angeles and surrounding areas has become a pressing
issue. In California, state legislators have created policies to combat the problem. Large
corporations such as Apple have contributed $2.5 billion to build AH throughout California.
Apple has also contributed $1 billion to first-time home buyers (Lee 2019). Industry not only
provides new employment opportunities, but also helps states in the funding of new AH
developments.
2.4. State of California
The State of California is the most populous state in the U.S., with approximately 39
million people. With an estimated population of four million, Los Angeles is the second largest
city in the country. The population density in the city of Los Angeles is 8,515 people per square
mile (U.S. Census Bureau 2017). In 2017, over 20% of the city’s population was living below
the federally designated poverty threshold and one-in-four homeless individuals was located in
downtown Los Angeles. The occupancy numbers for single and multi-family homes is 92%.
Nearly 34% percent of Los Angeles residents are unemployed, showing the dire need for AH
(World Population Review 2019).
The city’s population growth has caused an increase in housing and rental prices, which
creates problems and financial hardship for the 20% of the city population whose income falls
below the federal poverty threshold.
10
2.5. California Opportunity Zones (COZs)
The state of California has argued that COZs offer a new tool for community
development. Established in the Tax Cuts and Jobs Act of 2017, COZs provide tax incentives for
investment in designated census tracts. California Opportunity Zones can support investments in
environmental justice, sustainability, climate change, and affordable housing” (State of
California 2020). In addition, the California State Density Bonus Law 65915-18 financially
incentivizes housing developers to produce affordable housing by granting density bonuses to
those who designate a percentage of the total units for low or moderate-income households
(Ryan and Enderle 2012). This law encourages the development of AH, benefiting low income
and homeless populations across the state.
A census tract is eligible to serve as a COZ if either the median household income in the
tract is < 80% of the area’s median household income, or if the tract has a federally designated
poverty rate greater >20% (State of California 2020). The opportunity zone incentive is intended
to enhance the economic performance of specific geographic areas. The law imposes few
restrictions on qualifying investment type or purpose, allowing investment across a variety of
asset classes to encourage capital flows to the designated zones (Lester et al. 2018). Despite
potential challenges with the implementation of the policy, the incentives provided by COZs
present an opportunity to redirect wealth to benefit low income areas in California's small and
large cities.
There are 879 COZs today that span 57 counties and house an estimated 3 million California
residents (State of California 2020). On June 30, 2020, over $40 million was granted to promote
fair housing across the U.S., including $475,000 that was granted to the city of Los Angeles and
$360,000 that was granted to Greater Bakersfield Legal Assistance, Inc. The Fair Housing
11
Initiatives Program (FHIP) has four parts: (1) the Fair Housing Organizations Initiative (FHOI);
(2) the Private Enforcement Initiative (PEI); (3) the Education and Outreach Initiative (EOI); and
(4) the Administrative Enforcement Initiative (AEI). The EOI “offers a comprehensive range of
support for fair housing activities, providing funding to State and local government agencies and
non-profit organizations for initiatives that educate the public and housing providers about equal
opportunity in housing and compliance with the fair housing laws” (HUD Public Affairs, 2020,
1).
2.6. The Role of Public Transit
Low-income residents often rely on reliable public transportation to provide access to
employment opportunities (Wang and Woo 2017). Access to transportation is therefore an
important feature for locating potential areas for AH development because these services allow
AH residents access to employment opportunities in surrounding areas. Access to public
transportation also improves overall quality of living and mobility as many AH residents do not
own cars. This is a long-standing problem:
“Getting to work, keeping appointments, and taking advantage of employment
support services require suitable transportation. Many low-income Californians
do not own cars and, outside of large metropolitan areas, public transit services
are often sparse or non-existent, making it difficult for jobless individuals to make
the transition from welfare-to-work” (Cervero et al. 2002, 1).
There may be additional advantages as well. Some recent studies, for example, have found “that
location-efficient affordable housing is an effective climate strategy” and that “developing
parcels for lower-income households in location efficient areas is likely to lead to higher
12
reductions in vehicle miles traveled (VMT) than developing those parcels for higher-income
populations” (Newmark and Hass 2015, 22).
Wang and Woo (2017) examined the importance of decentralizing poverty and its
relationship to the transportation patterns of low income communities living in suburban regions.
The authors found that the “trend toward decentralized poverty has led to increased demand for
transit investment in suburban areas … and that … the decentralization of poverty is likely to
increase the transit ridership of low-income populations in suburban Transit Rich Neighborhoods
(TRNs)” (Wang and Woo 2017, 194). Similarly, Barton and Gibbons (2015) examined the
difference in transit patterns between low and higher income households and found that lower
income populations were more likely to use buses. Thus, based on the literature, bus stops were
included as a key feature for AH development as they are more commonly used by low income
populations.
2.7. The Role of the U.S. Department of Housing and Urban Development
The U.S. Department of Housing and Urban Development (HUD), created in 1965, noted
the housing hardships that many low-income Americans were facing and created programs to
improve the housing conditions. The HUD programs are federally funded but it is up to
individual states to provide adequate homes for those who apply for AH. HUD defines AH as a
dwelling that is designated for those who are in the low to median income bracket for their
region. The average low-income rent in the city of Los Angeles is $2,182 per month. The income
needed to afford the average asking rent is $7,273. The minimum wage should increase or the
cost of living should be less than 30% of the salaries of low-income workers (Schwartz 2020).
The materials used for AH dwellings are often of higher quality given that federal
housing is built to be cost efficient to minimize the expenses incurred by taxpayers. AH also can
13
be owned by private, public and not-for-profit entities who receive tax incentives to rent their
properties to low-income populations.
2.8. Role of Income
Median household income divides the income distribution into two equal parts below and
above the median value. For households and families, the median income is based on the
distribution of the total number of households and families including those with no income (U.S.
Census Bureau, 2020). As previously addressed, studies have found that decentralized poverty
leads to increased demand for transit investment in suburban areas (Wang and Woo 2017).
Albright et al. (2013) observed the potential negative externalities of impoverished people living
in suburban areas or nicer neighborhoods, testing the idea that low-income people would tarnish
the area. This was deemed to be a false narrative because access to improved opportunities such
as better schools, transportation and employment, can provide an escape from systemic poverty.
2.9. The Role of the Rent Burden
The term rent burden describes those who pay more than 30% of their monthly income
on rent (HUD Public Affairs 2020). The number of households in poverty has increased
following the Recession of 2007-2008, particularly for large households. Studies on rent burden
also reveal that renters have experienced increased financial stress related to their housing
compared to home owners (Colburn and Allen 2018). The PPIC Statewide Survey found that
47% of Californians say housing costs place a financial strain on themselves and their families
(PPIC 2017).
2.10. Summary
The results of this review shows how the economic features of potential locations of AH
development influence the affordability of housing. Without appropriate employment
14
opportunities, AH residents are at greater risk of being rent burdened and spending a significant
percentage of their income on housing costs and other basic necessities. Households are
“moderately- and severely-burdened households paying more than 30 and 50% of their income,
respectively, on residential rent” (Gabriel and Painter 2020, 3). As of 2014, approximately 90%
of city of Los Angeles residents making less than $15,000 per year were rent burdened while
approximately 80% of residents making $30,000 to $44,999 were rent burdened (Gabriel and
Painter 2020).
Gabriel and Painter (2020) noted that adverse congestion, pollution, public health, and
like externalities have been associated with lack of adequate affordable housing supply within
proximity of jobs. The authors also identify how outcomes for individuals and families are
inferior when rents increase faster than income and suggest that rising rent burdens may reduce
the economic potential of metropolitan areas (Gabriel and Painter 2020). The COVID-19
pandemic that swept across the nation during the past nine months may exacerbate these negative
consequences.
There may be a spatial element to the efforts to lift people out of poverty as well. Wang
and Woo (2017), for example, examined the importance of decentralizing poverty and its
relationship to the transportation patterns of low-income communities in suburban areas.
Albright et al. (2013), on the other hand, examined the affordable housing based on “Place”
theory which links aspects of affordable housing design to levels of social disorganization that
are not conducive to improving the social and economic stability of low income communities.
These authors referenced Wilson’s (1987) social isolation hypothesis which argues that
“concentrated poverty produces social disorganization by isolating poor residents from
15
“mainstream” society, concentrating crime ‐ prone people spatially to produce a social
environment that perpetuates criminality” (Albright et al. 2013, 3).
16
Chapter 3 Research Methods and Data
This chapter describes the research methods and data used to determine suitable areas for the
development of AH based on income, public transit, housing costs and HUD low income
housing tax credit (LIHTC) areas in the cities of Bakersfield, Los Angeles, and Palmdale. The
data, existing COZs, the soft criteria used to rank suitability, and the GIS analysis conducted to
calculate their rankings are described in separate sections below.
3.1. Geospatial Data
Table 1 lists each of the features included in the study’s weighted overlay analysis. The
data was sourced from ArcGIS Online and by request from the Antelope Valley Transit
Authority (AVTA) in California. The various features in these datasets were used to conduct site
suitability analyses within the chosen cities. The second column lists hard and soft criteria
because suitability was calculated for areas outside the COZs (which served then as a hard
criterion) and the soft criteria were used along with ranked condition rasters and weights to
calculate a suitability index. The third data source column points to the owners and locations of
the individual datasets. The data used ranged from October 2016 to January 2020 and therefore
provide accurate and current content. The geometry type lists the types of features used for the
source geospatial data. The points and polygons in these datasets were projected to NAD 1983
State Plane California V FIPS 0405 US Feet within ArcGIS to align them with a Compressed
Arc Digitized Raster Graphics (CADRG) map. The weighted influence column lists the weights
(expressed here as percentages) given to the ranked features that is explained in more detail in
Section 3.4.
17
Table 1. Feature Data Source Information
Feature
Type of
Criteria
Data Source
Geometry
Type
Weight
Influence
1 COZs Hard California Opportunity Zones
(3/18/2019)
https://services7.arcgis.com/lpTX3280
urZ21frb/arcgis/rest/services/Opportuni
tyZones_CA/FeatureServer
Polygon N/A
2 Bus Stops Soft AVTA (7/30/2020) – Requested and
received by email from the transit
organization
Point 40
3 Median
Household
Income (last
12 months)
Soft Low Income and Disadvantaged Tracts
ArcGIS Online (2016)
https://services1.arcgis.com/jUJYIo9tS
A7EHvfZ/arcgis/rest/services/LowInco
meAndDisadvantaged/FeatureServer
Polygon 30
4 Rent Burden
(30% spent
on living
costs)
Housing
Soft Employment Development
Department, State of California (2020)
https://services1.arcgis.com/4yjifSiIG1
7X0gW4/arcgis/rest/services/LongCom
mutes_Income_HousingBurden_byCA
Tract/FeatureServer
Polygon 20
5 LIHTC-HUD Soft LIHTC Housing (10/18/2018)
https://services7.arcgis.com/7mumd837
TsKeePXs/arcgis/rest/services/LIHTC_
Housing/FeatureServer
Point 10
3.2. Hard Criterion
The COZs referred to in the first row of Table 1 provide tax incentives for the
development of AH in the state of California and served as a hard criterion to exclude these areas
from further study. However, the best areas to develop AH may be located outside of COZs and
this study will present state officials and developers with possible locations for additional COZs
designations. Figure 3 shows the locations of the current placement of COZs in the three cities of
interest.
18
Figure 3. California Opportunity Zone (COZ) maps for the cities of Bakersfield, Los Angeles
and Palmdale
The COZ designated locations as seen in Figure 3 are designated by the state and local
governments for the purposes of pre-development, acquisition, renovation, and new residential
development.
3.3. Soft Criteria
The final four themes listed in Table 2 provided the soft criteria used in the weighted
overlay analysis. The soft criteria were assigned values from 1 to 5 indicating their suitability for
AH (see Table 2 for additional details).
Bus stops represent access to public transportation. A multiple ring buffer was used to
measure walking distance to the bus stops themselves and assign suitability ranks accordingly.
19
Table 2. Feature Metrics Criteria
Feature
Geographic
measureme
nt
1 2 3 4 5
Bus Stops
Buffer
Distance
Rings
(Feet)
> 1,321 ft
1,320 ft
Quarter
mile
990 ft 660 ft 330 ft
Median
Income
Census
tracks
0-30K 30-60K 60-90K 120-180K
90-120K
More
Suitable
Rent
Burden
>30%
Census
tracts
50% 40% 30% 20% 10%
LIHTC -
HUD
Buffer
Distance
Rings
(Feet)
1 ft 330 ft 660 ft 990 ft 1,320 ft
Color Scale
Defined Suitability Poor
Below
Average
Average
Above
Average
Excellent
Median household income was used to represent income by census tract. The suitability
scores favored moderate income levels versus low and high median household income so that the
candidate areas for AH avoided the poorest and most affluent neighborhoods.
Rent burden was employed in this study to identify census tracts in which households pay
more than 30 percent of their income to housing expenses. This attribute points to low-income
areas in which poverty is concentrated and an effort was made in this work to avoid these areas
so as not to make this problem worse.
The LIHTC sites funded by HUD support low-income communities as well. Although the
LIHTC-HUD program provides much needed housing, it also encourages the spatial
concentration of poverty and may have negative impacts on surrounding communities.
20
3.4. GIS Analysis and Modeling
The Model Builder tool strings geospatial processes together in a graphical interface used
to combine existing sequences of data in order to produce the calculated result. The model
structure for this study was developed to produce a Weighted Overlay model that uses a set of
reclassified ranked condition rasters and weights to calculate a suitability index (Price 2016).
The Model Builder interface within ArcMap 10 was used to perform different
calculations on the datasets within the study to produce the weighted overlay results as shown in
Figure 4.
Figure 4. Analysis Combined with Model Builder to Produce Weighted Overlay
The GIS modeling process illustrated in Figure 4 encompassed the GIS methods described in
more detail in Table 3. The model in Figure 4 depicts the process used to determine COZ site
suitability for AH development based on the data collected for the AOIs. The four soft criteria
were scored and assigned weights as follows: Rent Burden was given a weight of 20, Median
21
Table 3. Model Builder Processing Tools
Processes Definitions
Project Mathematical transformation that converts spherical units of latitude and longitude to a
planar x-y coordinate system
Clip Remove feature and portions of features that lie outside of the features of another layer
Polygon to
Raster
Any feature class (geodatabase, shapefile, or coverage) containing polygon features can
be converted to a raster dataset. The input field type determines the type of output
raster. If the field is integer, the output raster will be integer; if it is floating point, the
output will be floating point.
Reclassify Replace stress ranges of values in a raster with different sets of ranges of values
Euclidean
Distance
The straight-line distance between two points
Weighted
Overlay
An analysis that uses a set of reclassified ranked condition rasters and weights to
calculate a suitability index
Raster to
Polygon
The input raster is a floating-point raster, you must use the Map Algebra Expression
parameter to convert it to an integer raster.
Multiple Ring
Buffer
The generation of several buffers at set distances. Multiple ring buffers can have
overlapping or non-overlapping rings
Source: Price 2016
Income was given a weight of 30, LIHTC-HUD was given a weight of 10, and Distance to Bus
Stop was given a weight of 40.
The weights for AH development were chosen using the weighted overlay and pairwise
comparison methods. Bus stops were assigned the largest weights followed by median income.
Both of these criteria were treated as positive influences on AH suitability, whereas the high rent
burden and LIHTC-HUD regions were assigned lesser weights and treated as negative
influences. Pairwise comparison is the general process of comparing elements of data in pairs
(Esri 2020), and this approach was used in this study to determine to calculate the final AH
suitability scores.
Additional work was required to calculate the weighted overlay because this function
used a set of reclassified ranked condition rasters and weights to calculate a suitability index.
This requirement explains why the second column reproduced in Figure 4 shows the need to
convert the polygon datasets to rasters. These reassigned values of the polygon features were
22
converted to a single dimensionless scoring range from 1 to 5 using the ranges listed in Table 3
as well. The darker the color, the more suitable it is to be designated a COZ for AH to be built.
The polygon and feature to raster operations used the cell centers to decide the value of each
raster pixel.
23
Chapter 4 Results
To help address the needs of the approximately 2 million low-income households in California
who either lack a permanent residence or are severely cost burdened, more COZs to encourage
the development of AH will need to be established. The results of this study suggest high priority
areas for AH based on the model criteria set forward in Chapter 3. The three sections which
follow endeavor to answer the three main questions that were specified in Chapter 1:
1. Where are the COZs in the cities of Bakersfield, Los Angeles, and Palmdale?
2. What criteria should be used to determine suitable locations for AH?
3. What areas provide the most suitable AH opportunities based on the criteria and are
some of those areas located outside of the existing COZs?
The thesis argues that areas with the highest suitability scores are ideal. These areas are
located outside of the existing COZs given the methodology chosen for this work and therefore
the case can be made for each of the three cities – Bakersfield, Los Angeles, and Palmdale – to
provide developers with tax incentives to promote AH development.
4.1. Current COZ Locations in Three Study Cities
The maps reproduced in Figure 3 show the locations of the existing COZs in the cities of
Bakersfield, Los Angeles, and Palmdale. This study assumed that these COZs do not provide
sufficient opportunities (i.e. locations) for AH development and sought to delineate new areas
based on a series of criteria that would provide low-income communities with public
transportation and economic opportunities moving forward.
4.2. Conceptualization of Specification of Criteria Used to Find Candidate AH Areas
Four criteria – proximity to public transportation, neighborhoods with median incomes,
avoiding areas with high housing costs (i.e. rent burden), and avoiding locations that already
24
make use of LIHTC-HUD benefits – were used for the site suitability analysis presented in
Section 4.3. The derivation of these criteria was provided in Section 3.3 and the results captured
in Figure 5 show how these criteria were calculated in a small part of Bakersfield, California.
Figure 5. Criteria Feature Calculation for the City of Bakersfield
The polygons displayed in the maps reproduced in Figure 5 were later transformed into
rasters to produce the final weighted overlays presented in Section 4.3 below.
4.3. Final Weighted Overlays
The results presented in Figure 6 answer the question: What areas provide the most
suitable AH opportunities based on the criteria and are those locations within COZs? Locations
designated in dark blue have a suitability score of 5 and represent excellent candidate locations
for future AH development. There are extensive areas that run north-south in the western half of
25
Bakersfield (Figure 6a) and a series of scattered areas in Los Angeles and Palmdale (Figures 6b
and c) that produced suitability scores of 5 and large areas in all three cities with suitability
scores of >3 (Figure 6).
Figure 6. Weighted Overlay Results for the Cities of Bakersfield, Los Angeles, and Palmdale
Comparing the results in Figures 3 and 6, it is clear that the most suitable locations for
AH development within the cities of Bakersfield and Palmdale are not located within existing
COZs. The COZ locations for the cities of Bakersfield, Los Angeles and Palmdale are still viable
locations for AH, but the results in Figure 6 show that many additional areas could be designated
as COZs to incentivize AH development in locations with good access to public transportation
and employment opportunities.
26
The opportunities in Bakersfield and Palmdale can be further illustrated by zooming into
examples of neighborhoods in each city with suitability scores of 5. Figure 7, for example, shows
a candidate area in the city of Bakersfield which could be designated as a new COZ. The first
map in Figure 7a shows a Compressed ARC Digitized Raster Graphics (CADRG) with the
weighted overlay results layer. The COZs, bus stops, and LIHTC-HUD are shown on this map.
The close-up map reproduced in Figure 7b depicts areas that have been assessed to be the most
suitable regions where COZ designations can be established. The region is located in the
northwest quadrant of the city. The satellite image view reproduced in Figure 7c shows areas that
have yet to be developed. This image shows a highway, buildings, and suburban homes, and
these are all positive factors that can contribute towards a suitable environment for AH to be
developed.
The Palmdale weighted overlay analysis results map in Figure 8 display similar AH
opportunities and neighborhoods in which additional AH areas could be designated. The first
map in Figure 8a shows a CADRG with the weighted overlay results layer. The COZs, bus stops,
and LIHTC-HUD sites are shown on this map as well. There are fewer HUD sites and this allows
for more flexibility in COZ designations. The close-up map reproduced in Figure 8b depicts
areas that would be acceptable or excellent for AH according to Table 3. This region is located in
the northwest part of the city of Palmdale. The satellite image view reproduced in Figure 8b
depicts areas that have yet to be developed. This image shows a highway, buildings, and
suburban homes. These are all positive factors that would contribute towards a suitable
environment for AH to be developed.
27
Figure 7. AH Opportunities in the city of Bakersfield
The weighted overlay results for the city of Los Angeles reproduced in Figure 9 show
how difficult it is to find suitable locations for additional COZ designations here due to the high
cost of living and existing development. The majority of the COZ locations within this map have
a high number of LIHTC-HUD housing units. The lack of AH in Los Angeles for low-income
communities provided the initial motivation for this thesis project. The results for Bakersfield
and to a lesser extent Palmdale suggest that better opportunities for building AH can be found in
other cities in southern California.
28
Figure 8. AH Opportunities in the city of Palmdale
29
Figure 9. Weighted Overlay Results for the city of Los Angeles
30
Chapter 5 Discussion and Conclusions
This chapter provides a summary of results and some concluding thoughts. The findings for each
city are discussed and policy recommendations are provided to address the lack of AH
development and designate new COZs. Next, limitations based on the feature suitability criteria
are addressed and some possible future enhancements of this study are provided. The last section
of the chapter offers recommendations for future research that can build upon and enhance this
study.
5.1. Weighted Overlay Findings
The results of this study confirmed the hypotheses that were initially proposed at the
beginning of the study. Ultimately, the current COZs in the three cities are not sufficient to
address the need for low income housing in southern California. The weighted overlay analysis
results point to some additional areas that would provide suitable COZs to develop additional
AH.
According to this study, the city of Bakersfield can support AH development in several
neighborhoods that would provide low-income communities with public transportation and
employment opportunities. There are similar but fewer such opportunities in the city of
Palmdale. In addition, Palmdale is closer to Los Angeles than Bakersfield and this proximity
would allow residents to commute to and from Los Angeles for employment as well. The
commuter rail provider, Metrolink, runs regular services between the cities of Lancaster and
Palmdale and Union Station in the city of Los Angeles for example. The city of Los Angeles, on
the other hand, contains relatively few viable options for additional COZs or AH development
due to escalating home prices, the high cost of living, large numbers of rent burdened residents,
and large numbers of LIHTC-HUD sites spread throughout the city.
31
5.2. Limitations
The limitations are at least three. The first is the limited number of inputs used for the
weighted overlay model and the likelihood that more inputs might provide a more nuanced
assessment of the candidate AH neighborhoods in the three cities considered in this thesis
project. The second is the potential to use more refined measures for the variables used here. For
example, one could consider more than the locations of the bus stops to assess public transit
accessibility. One possibility would be to consider the headways and the areas that could be
reached in a certain time from each bus stop to provide more refined measures of mobility. The
third is the reliance on census tracts and the likelihood that this relatively coarse resolution
provided a relatively blunt instrument for the identification of areas that would be suitable sites
for the designation of new COZs to promote AH in the three cities. Census block groups would
provide better geospatial specificity but these units were not used because some of the datasets
were not available at this level.
5.3. Recommendation for Future Study Enhancements
Future studies could build upon this research by including current housing costs and
considering additional factors such as the cost of living beyond the rent burden indicator. The
California High-Speed Rail project may connect Bakersfield with Los Angeles in the future and
allow low-income residents living in AH in Bakersfield to commute to Los Angeles for work.
This thesis project provides a replicable and generalizable geospatial analysis workflow
for determining suitable locations for COZs and AH development. This model could be
implemented to analyze COZs and AH development opportunities in other California cities.
Using geospatial analysis and census data to determine suitable locations for AH development,
this study provides low-income residents the opportunity to find more sustainable housing.
32
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Asset Metadata
Creator
McClure, Andre Charles
(author)
Core Title
Suitable California Opportunity Zone (COZ) locations for affordable housing development in the cities of Bakersfield, Los Angeles, and Palmdale
School
College of Letters, Arts and Sciences
Degree
Master of Science
Degree Program
Geographic Information Science and Technology
Publication Date
02/17/2021
Defense Date
01/07/2021
Publisher
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Tag
affordable housing,Bakersfield,California,developer,employment development department,fair housing,high-speed rail,HUD,Los Angeles,low-income,OAI-PMH Harvest,opportunity zone,Palmdale,Poverty,rent burden
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