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Identifying suitable sites for sheltering outside in Long Beach, California

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Identifying suitable sites for sheltering outside in Long Beach, California

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Content Identifying Suitable Sites for Sheltering Outside in Long Beach, California
by
Brian M. Fuller
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 2024
Copyright © 2024 Brian M. Fuller

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To a special person, my lovely wife, Natalie

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Acknowledgements
First and foremost, I wish to acknowledge Dr. Ruddell who has been a dutiful coach and mentor.
His guidance and perseverance have been most welcomed and kept me moving forward. I wish
to thank the Long Beach Multi Service Center, particularly Alvin Teng, who provided me
cornerstone data. And a special shout out to Dr. Osborne who helped me put my thoughts and
work to coherent, written form. The help she has provided to me, I appreciate!

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Table of Contents
Acknowledgements........................................................................................................................iii
List of Tables ................................................................................................................................. vi
List of Figures............................................................................................................................... vii
Abbreviations................................................................................................................................. ix
Abstract........................................................................................................................................... x
Chapter 1 Introduction .................................................................................................................... 1
1.1 Motivation........................................................................................................................... 3
1.2 Study Area .......................................................................................................................... 7
1.3 Research Objectives............................................................................................................ 9
1.4 Structure of Thesis............................................................................................................ 10
Chapter 2 Literature Review......................................................................................................... 11
2.1 Existing Outdoor Housing Solutions................................................................................ 11
2.2 Divergent Perspectives and Policy Constraints ................................................................ 18
2.3 Needs of Unsheltered Persons .......................................................................................... 21
2.4 Spatial Negotiation and Participatory Planning................................................................ 23
Chapter 3 Data and Methodology................................................................................................. 29
3.1 Data Sources and Data Preparation................................................................................... 29
3.1.1 Homeless Survey Areas (HSA) ............................................................................... 30
3.1.2 Parcels...................................................................................................................... 31
3.1.3 Food Assistance ....................................................................................................... 33
3.1.4 Metro Stations.......................................................................................................... 34
3.1.5 Shelters and Services ............................................................................................... 35
3.1.6 Hospitals .................................................................................................................. 36
3.1.7 Health Clinics........................................................................................................... 37
3.1.8 Schools..................................................................................................................... 38
3.1.9 Parks......................................................................................................................... 39
3.2 Site Suitability Analysis.................................................................................................... 40
3.2.1 Filtering Parcels....................................................................................................... 41
3.2.2 Spatially Join HSA Visual Count to Parcels............................................................ 42
3.2.3 : Proximity to Services............................................................................................. 43
3.2.3.1 Proximity to Food Assistance ......................................................................... 44
3.2.3.2 Proximity to Health Clinics ............................................................................ 44
3.2.3.3 Proximity to Hospitals.................................................................................... 45
3.2.3.4 Proximity to Metro Stations............................................................................ 45
3.2.3.5 Proximity to Shelters and Services................................................................. 46
3.2.4 Re-classification....................................................................................................... 47
3.2.5 Weighted Overlay Method....................................................................................... 48

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3.2.6 Sensitivity Analysis to account for legal constraints............................................... 51
Chapter 4 Results.......................................................................................................................... 54
4.1 Filtering of Parcels............................................................................................................ 54
4.2 Site Suitability Results...................................................................................................... 55
4.2.1 Identifying top five most suitable sites.................................................................... 60
4.2.2 Disqualifying features for otherwise highly ranked parcels.................................... 61
4.2.3 AIN 7209022900, 1827 Pacific Avenue.................................................................. 62
4.2.4 AIN 7436005905, 1426 W. 12th St., cluster of three parcels................................... 63
4.2.5 AIN 7436004918, 7436004909, 1355 W. 11th St. ................................................... 65
4.2.6 AIN 7436007916, 1564 W. 9th St. ........................................................................... 67
4.2.7 AIN 7271011902, 1501 San Francisco Avenue river-facing parcel........................ 68
4.3 Sensitivity Analysis .......................................................................................................... 69
4.3.1 AIN 7207004271, 7207004272, 2990 Atlantic Avenue .......................................... 72
Chapter 5 Conclusions and Discussion......................................................................................... 74
5.1 Conclusions....................................................................................................................... 74
5.1.1 Preferred Sites.......................................................................................................... 76
5.2 Future Work and Considerations...................................................................................... 77
References..................................................................................................................................... 81

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List of Tables
Table 1. Data Sources....................................................................................................... 29
Table 2. January 2022 PIT Visual Count within Homeless Survey Areas (HSA) ........... 31
Table 3. School Parcels within Long Beach ..................................................................... 39
Table 4: Classification of Parcel Values for Variables..................................................... 48
Table 5. Weights for Model.............................................................................................. 50
Table 6. Results of Parcel Suitability by Class................................................................. 57
Table 7. Most Suitable Class of Parcels............................................................................ 58
Table 8. Most Suitable Parcels Qualified, Sensitivity Analysis ....................................... 70

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List of Figures
Figure 1: City of Long Beach, CA by Council Districts (2022)......................................... 9
Figure 2: City of Long Beach, CA homeowner rates, shelters, and council districts....... 25
Figure 3. Vacant parcels in Long Beach........................................................................... 33
Figure 4. Food assistance centers in Long Beach Area .................................................... 34
Figure 5. Metro Stations in Long Beach Area .................................................................. 35
Figure 6. Shelters and Services......................................................................................... 36
Figure 7. Hospitals............................................................................................................ 37
Figure 8. Health Clinics.................................................................................................... 38
Figure 9. Workflow for the LongBeachParcels layer....................................................... 41
Figure 10: February 2022 PIT count, services.................................................................. 43
Figure 11. Workflow for the Parcels Distance to Food Assistance layer......................... 44
Figure 12: Workflow for the Parcels Distance to Health Clinics layer ............................ 45
Figure 13. Workflow for the Parcels Distance to Hospitals layer .................................... 45
Figure 14. Workflow for the Parcels Distance to Metro Stations layer............................ 46
Figure 15. Workflow for the Parcels Distance to Shelters and Services layer ................. 46
Figure 16: Workflow for Schools with 2000 ft buffer in Long Beach ............................. 52
Figure 17: Workflow for Parks with Playgrounds Buffer 2000 ft.................................... 52
Figure 18: 2000 ft buffer around parks and schools......................................................... 53
Figure 19. 2021 Parcels Meeting Analysis Criteria of Vacant, no Waterways; N=327 ... 55
Figure 20. Weighted Overlay Results............................................................................... 56
Figure 21. Distribution of Weighted Overlay Values....................................................... 57
Figure 22. AIN 7207004272, Seaside Park ...................................................................... 61

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Figure 23. AIN 726901902, 1545 Long Beach Blvd........................................................ 62
Figure 24. AIN 726901902, 1545 Long Beach Blvd........................................................ 63
Figure 25. AIN 7436005905, 7436003902, 7436005918................................................. 64
Figure 26. AIN 7436004918, 7436004909, 1355 W. 11th St............................................ 65
Figure 27. Google Street View imagery, February 2023, 1355 W. 11th St...................... 66
Figure 28. AIN 7436007916, 1564 W. 9th St................................................................... 67
Figure 29. AIN 7271011902, 1501 San Francisco Avenue .............................................. 68
Figure 30. 2,000 ft buffer around Seaside Park ................................................................ 71
Figure 31. AIN 7436005905, 7436003902, 7436005918 outside 2000 ft. buffers........... 71
Figure 32. AIN 72017004271, 7207004272, 2990 Atlantic Avenue................................ 72

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Abbreviations
AIN Assessor Identification Number
CoC Continuum of Care
GIS Geographic information system
GISci Geographic information science
HF Housing First
HR Housing Readiness
HUD Department of Housing and Urban Development
HSA Homeless Survey Areas
LBC Long Beach, California
LBMSC Long Beach Multi Service Center
LULU Local Unwanted Land Use
NIMBY Not in My Backyard
PEH People Experiencing Homelessness
PIT Point in Time
SES Socio-economic Status
SSI Spatial Sciences Institute
USC University of Southern California

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Abstract
The rate of homelessness in the U.S. has steadily risen since 2016, prompting a focused effort to
eradicate this crisis primarily through indoor shelters and permanent, affordable housing
solutions. However, many unhoused individuals continue to camp nightly in various self-selected
locations, lacking the basic necessities for habitation and doing so contrary to official public
policy. Despite the inherent dangers and discomfort of outdoor living, some chronically
unhoused individuals prefer it to traditional housing options. Emergency shelters present barriers
to entry based on lifestyle, often don’t meet the desire of unhoused individuals for a sense of
community and belonging, and have proven inadequate in meeting public health mandates, such
as those required during the COVID-19 pandemic. As an alternative, various forms of outdoor
housing encampments for chronically unhoused adults have emerged, particularly in U.S. cities
on the West Coast. This project focuses on identifying suitable sites within Long Beach,
California for such an encampment, capable of providing potential residents with access to basic
necessities including potable water and sanitation. Sites within walking distance of essential
services (e.g., food assistance, health clinics) are evaluated for their suitability using a method of
analysis known as weighted overlay where the weights are based on the preferences of the
unhoused population, supported by empirical studies for justification. Additionally, a sensitivity
analysis is conducted to account for parcels within 2,000 feet of schools and parks that are
subject to heightened scrutiny due to legal and safety concerns. The project must balance
community norms with the needs of the unhoused population. The "Not in My Backyard"
(NIMBY) mindset often opposes initiatives that disrupt established norms or introduce locally
undesirable land uses (LULUs). By re-imagining outdoor sheltering options and incorporating

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insights from community dynamics, this project aims to offer more effective and compassionate
solutions for the unhoused in Long Beach, California.

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Chapter 1 Introduction
The number of homeless individuals, particularly the chronically unhoused, has been increasing
annually since 2016. The 2020 Annual Report from the Department of Housing and Urban
Development (HUD) revealed, “On a single night in 2020, nearly four in ten [unhoused persons]
were in unsheltered locations such as on the street, in abandoned buildings or in other places not
suitable for human habitation.” Proposals for alternative solutions are needed as this national
crisis continues unabated. Both the unhoused and housed citizens of communities across the U.S.
are impacted by the crisis.
Despite gargantuan efforts to address the homelessness crisis, options for chronically
unsheltered adults in the city of Long Beach, California (LBC) and the greater Los Angeles
County region are insufficient. Traditional approaches (e.g., shelters, housing first) are unable to
meet the demand for options. The reasons that persons remain unhoused range from a shortage of
shelter beds and affordable housing options to the personal preferences, needs, and
characteristics of unhoused individuals. When seeking to re-imagine outdoor housing
alternatives, it is essential that the aforementioned reasons be considered in developing solutions
that are most likely to be voluntarily accessed by unhoused adults.
To address the crisis at hand, this project pursues a fresh perspective where analysis in
geographic information science (GISci) yields parcels of land most suitable for outdoor
alternative housing intended for use by a population of chronically unhoused adults within the
City of Long Beach. The intended social purpose of such an endeavor is to provide the
population in question, who have been unable or unwilling to receive traditional services, a more
livable, dignified option in lieu of ad hoc encampments where they may currently reside.
Suitable sites would have access to potable water, sanitation, and other essential services.

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Specifically, this analysis will focus on the chronically unhoused adult population and potential
sites within the geographic area of LBC. As of January 2020, LBC is home to nearly half a
million residents with an unhoused population of approximately 1,600 adults. The main objective
of this project is to identify and assess potential public and private parcels of land that may serve
as suitable sites within LBC based on factors such as location preference of unhoused adults
currently sheltering outdoors in LBC, site proximity to community resources currently serving
unhoused adults in LBC, essential services and availability of utilities.
The primary audience of such an analysis ostensibly are the leaders of Long Beach who
through advocacy, ordinances and budget allocation may be able to realize this project. In
particular, the Long Beach Homeless Services Advisory Committee, a body directly reporting to
the city council, is currently exploring the possibility of accommodating the un-housed in
sanctioned encampments. Monthly meetings are underway to address this matter where the
committee is seeking ideas from the public. Beyond Long Beach, other cities may wish to adopt
this approach to serve their unhoused constituents.
This analysis is not without a notable limiting factor: climate. Long Beach is blessed with
arguably the best weather [228 perfect days] in a state, California, that already is heralded for its
Mediterranean climate. A success in Long Beach may be easier to replicate in nearby, balmy Los
Angeles, but prove more problematic in four season, Rockies-adjacent Denver. Mitigating
measures in such climes would need to be explored. Depending on the severity of the weather
extremes, the cost to mitigate may or may not challenge the viability of a project in a similarminded city to Long Beach, but without the benefit of a coastal, temperate climate.
The federal government is leading the charge for communities to address the crisis of
homelessness. In fact, policy from the U.S. Department of Housing and Urban Development

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(HUD) calls for “community-wide commitment to the goal of ending homelessness.” HUD’s
Continuum of Care program allocates funding for non-profit providers, states and local
governments to assess the needs of the unhoused, evaluate the currently available services and
housing options, and encourage use of resources to develop future approaches. Regional
planning bodies collaborate in administering the program locally. These planning bodies, also
known individually as Continuum of Care (CoC) generally follow geographic areas. Within Los
Angeles County, the City of Los Angeles CoC administers on behalf of most of the county
except for Glendale, Pasadena and Long Beach who have their own CoCs. It is fortuitous for this
project, that Long Beach has its own CoC where researchers may be able to work with a more
manageable microcosm of what the greater Los Angeles area and the state of California face.
Due to its diversity and size, this project will be able to compare and contrast LBC with
other cities on the West Coast of U.S. of similar population: Fresno, CA (545K); Sacramento,
CA (528K); Portland, OR (635K) and Seattle, WA (749K). Demographically, Long Beach is
majority-minority, with nearly half a million residents across a wide swath of socio-economic
strata. Economically, the city is home to one of the busiest ports in the world and has a sizeable
business district in its downtown. Geographically, Long Beach, as its name aptly implies, has
beaches fronting its downtown. Additionally, it encompasses rolling hills and flatlands through
its suburbs, generally bordered between two significant waterways, the Los Angeles River and
San Gabriel River.
1.1 Motivation
Hundreds of thousands of Americans face night after night without shelter in conditions
unfit for habitation. The quantity of available shelters beds and permanent housing units is
insufficient (Solensten and Willits 2019, 935). Despite the danger, discomfort and scarcity of

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resources they face when sheltering outdoors, and even when other housing options or
emergency shelter beds are available, a multitude of chronically unhoused adults continue to
prefer to shelter outdoors and decline programs seeking to move them into permanent housing
options (Stuart 2014, 1917).
Beyond quantity, there are attributes of traditional shelters and housing options that
create barriers to entry (e.g., partners, pets, possessions) for a segment of the chronically
unhoused adult population (Loftus-Farren 2011, 1076). Most adults desire to exercise selfdetermination. Many chronically unhoused adults are not willing or able to live within the rigid
schedules, hours of operation, rules, regulations, and behavioral expectations that exist in
traditional shelter and housing options (Stuart 2014, 1913). Unhoused adults have expressed that
these environments are too demanding and intrusive (Jost and Levitt 2010, 246). Additionally,
unhoused adults are often seeking a sense of community and belonging that is not a hallmark of
the shelter experience. The reality is that shelters may be a place of physical refuge, but they are
not a “home”.
There is a pressing need for innovative shelter options addressing the needs and
preferences of the group in question. Research extending beyond conventional indoor options for
sheltering the unhoused is warranted. Such research will allow communities, policy makers and
service providers to better understand the needs and preferences of chronically unhoused adults.
Thus, opening the door for communities to re-imagine the longer-term possibilities for those
already voluntarily sheltering outdoors in the 21st century.
Two major approaches to housing people experiencing homelessness (PEH) have been
employed in the last few decades: “Housing Readiness” (HR) and “Housing First” (HF). In the
HR approach, PEH must first achieve sobriety to qualify for housing. Conversely, HF seeks first

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to place PEH into affordable housing while simultaneously pursuing treatment for mental illness
and substance abuse (Osborne 2019, 402). HF originated in Los Angeles in 1988 by an
organization, Beyond Shelter, that successfully re-housed homeless families (Waegemakers
Schiff and Schiff 2014, 83). Years later, Pathways to Housing out of New York, founded by Sam
Tsemberis, further pushed the concept where PEH struggling with mental illness and addiction
are integrated into the community in a “scattered-site” manner by means of rent subsidies for
privately-owned units (Kohut and Patterson 2022, 62).
HF has significantly impacted the vision and values around approaches to homelessness
in the U.S. The foundational belief behind HF is that everyone has a right to a home regardless of
circumstances. Transitional spaces (e.g. shelters, encampments) are discouraged in an HF
framework in favor of the more permanent and traditional option of affordable housing. Deemed
successful, HF has been adopted by municipalities (e.g. Seattle) throughout North America
where cities have put forth “ten year plans” to end homelessness (Evans and Masuda 2020, 503).
In spite of efforts and motivation on the part of HF advocates and the communities who
adopted the HF framework, homelessness has not been eradicated. Research is showing that a
sizeable number of HF clients are returning to their former unhoused lives (Kohut and Patterson
2022, 65). A shortage of affordable housing is at the crux of the problem for advocates of HF and
public administrators must determine who amongst the unhoused are the most worthy (Osborne
2019). That, in itself, is contradictory to the ethos of HF where personal circumstances are not
expected to drive decision-making. Where the mere state of being unhoused should be the sole
qualifier, shortages force service providers to prioritize applicants (Evans and Masuda 2020
513). Consequently, it has encouraged applicants to embellish or outright lie about their struggles
in order to gain higher consideration (Kohut and Patterson 2022, 67). The “scattered-site”

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method of interspersing PEF throughout municipalities where affordable housing is available,
rather than where it is desired, has negatively affected individuals’ sense of belonging.
Loneliness and social isolation are often cited (Speer 2017, 530).
As with emergency shelters, the HF framework may attempt to house every PEH, but that
does not equate to making a home. PEH have diverse needs and preferences that traditional
housing options cannot meet with a one size fits all approach. A home ideally offers privacy,
autonomy and a place to have personal possessions. A home is the familiar place where friends
and family may be welcomed, where a person may cohabitate with their partner and own pets.
To have a home in a neighborhood or community provides an opportunity for a sense of
belongings and connections outside the immediate living space. Those sheltering outdoors have
found ways to create a sense of home and community for themselves, outside the confines of
traditional housing options (Sparks 2017, 89).
It is impossible to ignore the risks to public health when persons are sheltering in densely
populated, poor conditions, both indoors and outdoors, with little ability to socially distance.
With the increased realization since the Covid-19 pandemic, that future pandemics or more
localized public health crises could be on the horizon, the need for innovation in housing options
is more pressing than ever. Covid-19 demonstrated that dense or congregate housing solutions
are high risk zones for the spread of infectious disease. Also, in the vein of public health,
individuals and the community at large are at risk when large numbers of persons are living
without access to potable water, basic hygiene and restroom facilities. The vast majority of those
currently sheltering outdoors have little to no access to these utilities considered necessities of
life for the average American. Access to transportation and other resources such as healthcare
facilities are also essential to public health.

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Any solution that involves identifying a site suitable for shelter outdoors, must consider
access to utilities, site safety from various factors including risk for natural disasters such as fire
and flood, as well as access to transportation and essential services. Because an outdoor
alternative housing site does not readily exist within the city of Long Beach, the use of GIS will
be an essential tool in identifying a suitable site. Through the use of site suitability analysis
methods such as weighted overlay, the city may be able to find a site that could accommodate
chronically unhoused adults.
Advocates for the betterment of the chronically unhoused, particularly those seeking only
affordable housing options, may frown upon the suggestion of identifying locations for outdoor
shelter options for chronically un-housed adults. It may be viewed as accepting a substandard or
inhumane way of living and giving up on the vision of ending homelessness all together. It may
also be criticized as being unfavorable to the interests of the community’s citizens, economy and
reputation. However, this project seeks to take into account the preferences and barriers to entry
faced by those already sheltering outdoors and to explore options where conditions are more fit
for human habitation, accepting the fact that there are those of the chronically unhoused adult
population who prefer sheltering outdoors over accessing shelters or permanent housing. When
the voices of those who are sheltering outdoors are elevated and they are given an opportunity to
exercise self-determination, it is possible to re-imagine alternatives that would suit their needs
and preferences while also supporting the needs and interests of the community at large.
1.2 Study Area
Long Beach, California (LBC), incorporated as a charter city in 1897, is located in the
southern part of Los Angeles County, abutting neighboring Orange County to its south. The total
area of the city is 77.84 square miles of which 50.72 is land. Topographically, it is mainly flat in

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the northern and central areas, with a notable exception of aptly described Signal Hill, an
enclaved city that is situated roughly centrally within LBC. Major waterways, Los Angeles River
and San Gabriel River, crisscross LBC on its western and eastern borders, respectively. Adjacent
to the Los Angeles River is Terminal Island, shared with City of Los Angeles, where the two
municipalities have the Los Angeles-Long Beach port, the busiest in the U.S. Downtown LBC is
on the shores of the Pacific Ocean abutting the Los Angeles River to its west. High socioeconomic status (SES) neighborhoods of Belmont Shores and Naples are located to the east
southeast of downtown on the shoreline. Another high SES neighborhood, Bixby Knolls,
centered on Atlantic Avenue, is due northwest of Long Beach Airport. Low SES neighborhoods
are found in North Long Beach and Eastside (misnomer, as it refers to east bank of Los Angeles
River, which is on the western side of LBC). Transportation wise, Long Beach is served by
major freeways, Long Beach Freeway (Interstate 710), San Diego Freeway (Interstate 405), San
Gabriel River Freeway (Interstate 605) and Artesia Freeway (California State Highway 91).
Long Beach Transit is the municipal bus line serving connections to the Metro light rail and
other public transport agencies. Metro A line formerly Blue line originates from downtown Los
Angeles terminating in Long Beach.
Demographically speaking, Long Beach has 466,742 inhabitants according to the 2020
Census. The city is ethnically diverse with Hispanics or Latinos making a plurality at 43.9%
followed by Whites (27.8%), Asians (13%), Blacks or African Americans (12.1%), Two or more
races (8.7%), Native Hawaiians and other Pacific Islanders (5%) and American Indians and
Alaska Natives (1%).
Point in Time (PIT) count of the unhoused within Long Beach is conducted every year.
The city is divided into fifty-two homeless survey areas (HSA) where teams of three to five

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volunteers conduct visual counts during the twilight hours of a night in January and sometimes
February. Findings for 2022 PIT report 3,447 experiencing homelessness. Of these, 71% are
unsheltered. More than half report experiencing homelessness for the first time, while 38%
report being chronically homeless. Two out of three unhoused adults are male. One out of ten
are veterans. Racial breakdown shows that African Americans are disproportionately more likely
to be homeless than the general population of Long Beach: 30.2% rather than 12.1%. Figure 1
shows the City of Long Beach with nine districts representing its city council.
Figure 1: City of Long Beach, CA by Council Districts (2022)
1.3 Research Objectives
This thesis aims to address the needs of the unhoused population by conducting a site
suitability analysis to identify potential vacant land parcels suitable for establishing a sanctioned

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encampment. A primary objective is to assess the importance of various services, such as
shelters, public transportation (metro stations), food assistance locations, and hospitals, to the
community. Walking distances from each parcel to the services will be classified and used in a
weighted overlay method. The concentration of unhoused individuals in homeless survey areas
(HSA) will also be incorporated into the weights for the method. This approach may help yield
suitable parcels. Additionally, an alternative model citing empirical studies will use different
weights for each of the services to determine if there is any significant difference. Furthermore,
legal constraints (buffers around schools and parks) will be taken into account, as they may
complicate the identification of suitable parcels and influence public policy decisions regarding
the unhoused.
1.4 Structure of Thesis
This thesis consists of five chapters. Chapter 1 provides an introduction to the topic of
investigation and motivation for this work along with a description of the study area. Chapter 2
presents a literature review examining the current drivers, challenges, and opportunities of the
unhoused and where there are enterprising developments that are worthy of pursuit in the study
area. Chapter 3 provides a summary and description of the data sources and methodology
employed in this project. A summary of results and research findings follows in Chapter 4. The
thesis is concluded in Chapter 5, which includes a discussion of research limitations and
potential future avenues for exploration.

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Chapter 2 Literature Review
Policy makers, government agencies, private entities, religious groups, academics and advocates
are scrambling to develop and assess potential solutions to the growing crisis of homelessness in
the U.S. Studies have shown that one must grapple with diverse perspectives and policy
constraints that impact the support for and feasibility of alternative living options for unhoused
adults. A review of the literature demonstrates there are benefits to alternative outdoor housing
options for unhoused adults, including minimal barriers to entry, increased self-determination,
stability and sense of community. In identifying and assessing sites suitable for an alternative
outdoor housing option in LBC, this project has the potential to increase options for unhoused
adults and affect changes in local public policy.
2.1 Existing Outdoor Housing Solutions
Across the US and around the world, un-housed adults are setting up camp in a range of
self-selected locations, without permission and without basic necessities to make those locations
fit for human habitation. The race to eradicate homelessness has focused almost entirely on
indoor shelters and permanent, affordable housing. Few have dared to consider outdoor housing
solutions. One reason for this is climate considerations that limit such discussion to locations
with predominantly mild weather throughout the year. Another reason is society’s impetus to
eliminate the problems that come with unhoused adults who are camping in inconvenient and
unsafe locations by simply pushing them out of town or bringing them indoors and out of sight.
Many cities, particularly those on the West Coast, have become more tolerant and even
cooperative with organized encampments as options to address the sheer number of unhoused
adults (Przybylinski 2021, 434). Organized encampments typically refer to a designated place

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where multiple unhoused adults may sleep outdoors for one or more nights, with or without tents
or other temporary structures. They may provide amenities such as food, restrooms and other
services and are likely to have some level of rules and regulations. Some organized
encampments are in long-term sites while others may move periodically.
One such organized encampment is Right 2 Dream Too (R2DT) located in Portland,
Oregon. R2DT operates as a low-barrier encampment where 70 residents at a time may find a
safer place to sleep within a community of like-minded persons, (Przybylinski 2021, 426).
Founded in 2011 by and for the unhoused, R2DT was initially set up on a private plot of leased
land within the Old Town Portland neighborhood. This was an area where a number of the
unhoused in Portland already preferred to camp. Service centers were densely clustered near the
site and thus provided convenient proximity to the residents of R2DT.
As one might expect, the presence of a somewhat large, organized encampment in the
heart of Portland, brought legal challenges from the City. One legal challenge was whether
R2DT was a permissible encampment per city land use laws. The question arose as to what
R2DT actually is: a recreational campsite or transitional housing accommodation? The city
argued it was a recreational campsite in its citations but R2DT counter-argued that it was a
transitional housing accommodation which is permissible under Oregon land use laws,
(Przybylinski 2021, 427). A stalemate ensued and the City ultimately offered another site for use
by R2DT plus a waiving of fines incurred during the challenge.
While the City may have acquiesced, Portland business groups and a developer continued
to be hostile to the existence of the organized encampment. This is not surprising as concerns
about the economic impact of visible homeless encampments on local business is commonplace
in communities of all sizes. Despite efforts to undermine R2DT, and in spite of a forced change

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in location, the organized encampment continues to exist. It is noted that the substitute site
provided by the city is still within walking distance of essential services for the unhoused but did
not take into account the preferences of the unhoused, as this project aims to do.
Another encampment in Portland, Dignity Village, has a similar story albeit with
different tactics. Born as a political movement in December 2000, Dignity Village deliberately
occupied a parcel of city-owned land within the core center of Portland underneath the Broadway
Bridge. Within days the police swept through and did so multiple times thereafter. Rather than
accept repeated displacements by the authorities and scatter as individuals throughout the city,
they chose not to disband. Instead, as a means of attracting public attention and shaming the
progressive-conscious city, every time a displacement action occurs, they move en masse in a
shopping cart parade to another area of the city. After a large parade took place in 2010, Mayor
Vera Katz and Housing Commissioner, Erik Sten, chose to negotiate with the community
(Farrington, 2023, 10).
However, the city would not accept the sight of Dignity Village nor its site under the
Broadway Bridge. It convinced the community to first move to a less visible location under the
Fremont Bridge before ultimately seeking to have it relocate to a parcel seven miles north,
adjacent to the international airport, a leaf composting facility and a corrections facility.
Banished to the urban periphery, beyond the reasonable reach of services in central Portland,
adjacent to local unwanted land uses (LULU), many within the community objected to the site.
Unfortunately for Dignity Village, it is a LULU itself, and consequently, the city decided
accordingly. The encampment, though initially fractured in response to the city’s terms, came to
accept the site known as Sunderland as their new home. In exchange for collecting data on
residents, limiting residency to two years, and cooperating with local service providers, Dignity

14
Village has been given the city’s blessing as a sanctioned encampment. A self-governed
community, it now serves houseless individuals in transition to more permanent housing
(Farrington, 2023, 11).
Further north, in Seattle, Washington, where the term “Skid Row” originated, multiple
organized encampments have been established. The road to acceptance of such encampments as
long-term solution to addresses homelessness in Seattle has been a rocky one. One of Seattle’s
organized encampments, aptly named “Tent City,” was scorned for years and even demolished
by the City of Seattle before it eventually came into acceptance years later. The city was
determined to eradicate the need for tent cities. In 2005, Seattle put forth the Ten-Year Plan to
End Homelessness. The objective was to mitigate homelessness, and where prevention was not
feasible, to facilitate swift transitions for unhoused persons from indoor shelters to permanent
housing options. But, by 2014, news of the tragic death of an unhoused man camping in a
precarious location above a freeway was just one incident that highlighted the fact that
homelessness was still a significant issue in Seattle and the Ten-Year Plan had not put an end to
the problem. The City has since accepted that encampments on public property are here to stay,
(Sparks 2017, 86).
Over the years, the original “Tent City” encampment in Seattle has morphed and cloned
into additional sites. Each site has some flexibility to operate differently. At a site known as
“Tent City 3,” the encampment is self-managed, and residents of the site have created a
community unto themselves. Each resident nominates another for a task, and each is duty bound
to perform it. Violating the community’s rules may lead to reprimands, including expulsion. For
the safety of the community, security assignments are a regular task. Maintaining order at Tent
City 3 is key, as one of the residents notes, it helps to keep the “riff raff out”, (Sparks 2017, 98).

15
Keeping the “riff raff” out suggests that this particular outdoor housing option, may have some
barriers to entry. As many organized encampments do, Tent City 3, has various regulations
including prohibitions on drugs and weapons, and requires segregation of men and women in
tents, (Sparks 2017, 97). Prohibition of drug use and rules that prevent couples from sharing a
tent are a non-starter for many would-be campers who might avoid sheltering options that are too
strict and limit their freedom to use drugs or share sleeping space with who they choose.
However, Tent City 3 residents have reported that rules are not strictly enforced.
Reputation as a “good camper” allows greater leeway with infractions, whereas those considered
disruptive or “lazy” may suffer expulsion, (Sparks 2017, 98). It is suggested that this flexibility
in exercising discretion provides consideration and perhaps shows humanity that otherwise
would be absent in more regimented operations. For example, a new camper had the misfortune
of having her husband fail to show up for his assigned security duty, an infraction that calls for
expulsion. However, the EC on duty stated that he was not going to write it up, turning a blind
eye and stating that this never happened, (Sparks 2017, 99).
Seattle’s approach to organized encampments involves oversight by the city’s Human
Services Department and local non-profit service entities whose regulations that limit their
autonomy. While Tent City 3 implements some form of self-management, it is also under
sponsorship of an agency named SHARE/WHEEL that has been registered with the city. The
city’s human services department authorizes SHARE/WHEEL to oversee encampments allowing
their existence for a year at a time. Curiously, though, Tent City 3 is not stationary for that
yearlong period. Rather, the encampment must move to a new location every ninety days.
In contrast to the express aim of this project to assess the suitability of a site, Seattle’s
insistence that the encampments keep moving demonstrates a lack of intention to consider the

16
suitability of the encampment site in terms of location preference of the unhoused, stability, or
proximity of services. Perhaps this requirement is intended to keep the visibility of the organized
encampment to a minimum. It could also be intended to inhibit an encampment from becoming a
long-term norm for the unhoused. It appears Seattle may not have fully accepted that
encampments as anything other than a stop-gap emergency housing solution for the unhoused
that must be tolerated until a better solution is realized.
Another alternative to meeting the needs of the un-housed is the “campground” approach
found in New Zealand. Kearns et al. argue that a campground is a viable solution addressing, in
part, the severe housing affordability crisis that is engulfing metropolitan Auckland, New
Zealand, (Kearns et al. 2019, 299). Superficially reminiscent of trailer parks in North America,
the campgrounds identified in the article cater to the following guests: tourists, long-term
residents, and a combination of both (i.e., mixed). A significant benefit to campgrounds is that
the chronically unhoused may enjoy a sense of community along with the enhanced dignity and
increased quality of life provided by access to utilities, sanitation and amenities like those often
found in recreational campgrounds in North America. The authors also showcase the concept of
the campground including a service hub. These are “clusters of low-cost housing and social
support services” such as, literacy programs, support groups and care centers that address health
and mental health needs.
Surveys of the campground’s guests show the attitudes and feelings about living in a
campground have been positive for the long-term residents who are able to avail themselves of a
variety of services brought in by charitable groups and public agencies. However, surveys of the
campground’s guests and managers demonstrate that there are differences of opinion amongst
the guests staying as tourists and those who are long-term residents. For example, long-term

17
residents have taken to identifying communal swimming pools as “theirs” and tourists, according
to a resident, tend to view the long-term residents negatively and think “[they] are unemployed
or in gangs.” One approach to maintaining the peace has been separation of the two populations
in order to minimize mistrust and fear, (Kearns et al. 2019, 306).
The challenges of housing insecurity are still ever present in the New Zealand
campgrounds. Changes in ownership, regulations and rising property values have residents in
these campgrounds feeling anxious. One resident expressed, “The hardest thing is the
uncertainty; will it close? We want to know… not wondering, being in limbo. We don’t know if
we will be booted out, that’s what sucks.” (Kearns et al. 2019, 307). This resident’s fear is real
as some campgrounds are closing. One result of such closures is casting campground residents to
locations further away from the metropolitan center which is undesirable for many campers. Yet,
the campground concept remains despite the uncertainty (Kearns et al. 2019, 308).
The campground solution described by Kearns is one that has merit for implementation in
North America. Campgrounds have the potential to provide a long-term housing solution for
chronically unhoused persons that might prefer to live outdoors. Campers may benefit from a
reduced social stigma as they that are viewed as “guests” at the campground and reside in a sites
that may share space with temporary/tourist guests. Campgrounds on larger parcels of land or
outside the city center may allow for increased access to privacy and to the benefits of access to
nature.
There are lessons to be learned from each of these existing outdoor housing solutions
discussed in the literature: organized encampments and campgrounds. Auckland, New Zealand’s
campgrounds are generally the most relatable solution for this project’s proposed Long Beach
site because they are designed as a service hub to the residents with access to utilities and some

18
amenities. In both Portland and Seattle’s organized encampments, resident campers have
primarily desired to be located within the city’s urban center. The proposed research will
consider both public and private lands as possible sites for an outdoor sheltering solution.
Placement on private property may challenge security of the land for indefinite use. The
examples of organized encampments in Portland are primarily self-managed, while Seattle is
partnering with non-profit organizations to manage their organized encampments to a greater
degree. Finding a balance between the two approaches will be one area of consideration of the
best approach to implementation of an organizational structure for the proposed Long Beach site
that provides the greatest sense of autonomy and community while also providing security and
stability.
2.2 Divergent Perspectives and Policy Constraints
Local governments grapple with a range of perspectives while addressing homelessness
within their jurisdictions. Numerous factors contribute to this diversity of viewpoints. Evidence
indicates that certain policy changes have been influenced by innovative approaches aimed at
meeting the needs and preferences of the unhoused. Homelessness is a longstanding issue,
prompting the implementation of various policies—both old and new—with the primary goal of
reducing homelessness and its visibility.
Historically, Sacramento, California has intermittently experienced sizeable
encampments. During the Gold Rush era, Forty-niners set up tents, followed by the emergence of
Hooverville shanties during the Great Depression. More recently, during the Great Recession of
2008-2009, a modern iteration known as the Wasteland appeared (Parker 2020, 340). The
presence of unhoused individuals in Sacramento has persisted over time. As long as they

19
remained inconspicuous, there was little need for intervention. However, when homelessness
becomes highly visible, the city has responded with punitive measures toward encampments,
such as enacting anti-camping laws. Sacramento city government’s actions demonstrate it
believes it is better to scatter the unhoused rather than allow them to gather and become a highly
visible presence, which could embarrass the city and necessitate remedial action.
For example, the rise of the Wasteland came about when the police directed campers
living near a service center, Union Gospel Mission, to move to an expansive brownfield,
formerly a dump between train tracks, on the other side of a plant processing almonds, (Parker
2020, 329). It seemed to be out of the way and out of sight from the rest of Sacramento. The
encampment became a community where residents self-regulated their behavior, managed waste
disposal, and availed themselves of potable, drinking water. Its seemingly successful
management attracted increasing interest from homeless services and even that of a local
graduate program seeking to test a prototype eco-toilet, (Parker 2020, 339). Due to national
media focusing on the impact of the Great Recession, news outlets descended upon the
Wasteland encampment. They erroneously concluded that the residents were victims of the
housing market collapse, rather than the chronically unhoused population that had been shuffled
around Sacramento by authorities for years, (Parker 2020, 330). The city could no longer sustain
its previous stance of benign neglect, as the embarrassing public scrutiny of the site demanded a
change. Consequently, the city moved to disband the encampment.
A few hundred miles south of Sacramento, the city of Fresno, California has adopted the
tent city approach. Tent cities in Fresno are not the type self-managed by unhoused campers. In
this way, it differs from the approach sought for the proposed site in Long Beach, and those in

20
cities such as Portland and Seattle. Instead, Fresno’s approach has been derided as providing
“tent wards,” reminiscent of incarceration (Speer 2017, 160). Initially, it appears that the
approach by Fresno to re-zone a property as a campground is concurrent with what is sought for
Long Beach. However, Fresno’s approach differs in many aspects including the lack of running
water and sanitation, restrictions on the keeping of pets, persons being subject to random
searches, residents being forced to vacate in the morning, and restrictions on couples (Speer
2017, 163). These restrictions are reminiscent of what is found in shelter programs and known to
be barriers for the un-housed to participate voluntarily.
The proposed site for Long Beach aims to provide a refuge for chronically unhoused
individuals, allowing them to reside in a sanctioned encampment. Like the housing first concept,
which prioritizes shelter over sobriety, this approach aims to accommodate individuals who may
have been rejected from other facilities, such as shelters, due to stigmatized behaviors or vices.
Where it may differ is that housing first seeks permanent housing and social activists for that
approach generally frown upon the suggested encampments proposed, deeming them to be
inadequate and improper. In other words from a progressive perspective, housing first
emphasizes the aforementioned permanent housing, the low barriers to entry on behavior, and
providing long-term support. Conversely, it incorporates methods that are neoliberal oriented:
clearing of streets, fiscal necessity, and addresses not all forms of homelessness, but rather the
chronically un-housed, (Baker and Evans 2016, 31).
A dichotomy becomes evident, where there's an insistence that humans should reside
within traditional four walls and a roof, despite resistance from the affected population (i.e.
chronically unhoused) and the daunting challenge of meeting all housing needs with available

21
resources. Homeless advocates such as Parker (2020) frown upon the presence of the un-housed
living on brownfields, lots formerly used by industry that need environmental remediation and
are zoned for industrial purposes. This could pose a challenge for such an implementation in
LBC as brownfields may be a worthy consideration for a development to be used by chronically
un-housed adults. Parker (2020) cites the establishment of sanctioned tent cities as “managed
marginality” (Parker 2020, 341). He sees them as allowing the city to hide their un-housed in out
of the way areas, while simultaneously providing the un-housed a safe place to shelter. With
limited resources available, it may take tradeoffs such as these to provide the latter.
2.3 Needs of Unsheltered Persons
Where resources are limited, namely money and space, pragmatic considerations must be
pursued. Consequently, the need for informal housing emerges. “Tent Cities: An Interim
Solution to Homelessness and Affordable Housing Shortages in the United States” by Zoe
Loftus-Farren eloquently posits that such an informal housing, while not ideal, is suitable where
no other reasonable option exists. Therein, she identifies common themes found in successful
informal housing: community and autonomy, self-governance, advocacy and assistance, and
stability and security.
Both a sense of community and autonomy attracts certain unhoused adults to outdoor
housing solutions. Community is where shared experiences and shared needs can consolidate and
congregate. Being a part of a group brings forth value to oneself and to the community. For some
unhoused adults, this sense of community is more likely found in an encampment environment
than in a shelter setting. A resident in a tent city in Rhode Island describes the community as his
‘family’ and expresses contentment being part of the group (Loftus-Farren 2011, 1050). Further
expressing the familial bond is that this kind of informal housing allows for romantic

22
relationships which are expressly forbidden in the shelters. Shelters not only limit who one may
physically be with during the night, but they limit where you can be and what you can do
throughout the day. This impacts an unhoused person’s sense of personal freedom and
autonomy.
Self-governance is an appealing component to the success of informal housing solutions.
Unlike them traditional shelters, which provide no direct opportunity for residents to impact the
way operations are conducted, self-governed informal housing communities give voice to the
desires of their inhabitants. The community is best served at the direction of its inhabitants.
Where a shelter may also be a place to receive a handout, that kind of approach is anathema to
those who strongly prefer not to depend on public assistance, (Loftus-Farren 2011, 1051).
Generally self-governed encampments operate with the values of mutual respect, participation in
its operation, and developing a set of reasonable rules with the goal to maintain safety and
harmony within the community. This has the potential to minimize the sense that one is
exceedingly dependent or controlled. It also gives those participating in self-governance a sense
that they have a stake in the success of the community and in their own destiny.
Informal housing solutions that provide for various types of advocacy and assistance
contribute to positive outcomes for unhoused adults. Advocacy can come in the form of
providing a voice for the concerns and needs of an individual with regard to social service
agencies that provide benefits such as food stamps, unemployment, Medicaid or Social Security,
immigration services, Housing and Urban Development, DMV and court systems, or NGO’s that
provide substance abuse treatment, and victims of crime services or other legal aid services.

23
Finally, there is the need for stability and security among the unhoused. Both formal and
informal housing solutions contribute to a sense of anxiety about the future. One factor that
contributes to a sense of stability and security is having a secure location to keep personal
belongings that are important to the unhoused individual. Shelters often do not allow overnight
guests to bring personal belongings inside and unsanctioned encampments are often cleaned up
by city authorities, causing personal belongings and even important documents to be destroyed
or disposed. Personal safety of unhoused individuals is another significant source of security
concerns. Deaths of unhoused adults and crimes against unhoused adults are breaking records in
cities across the U.S. An encampment with mutual security measures offers a degree of solace to
unhoused adults, assuring them that their possessions will be intact upon their return and that
they can rest safely. Additionally, formal and informal housing solutions that require a person to
check out daily or move to a new location every few months, contribute to an ongoing cycle of
chronic homelessness. Reduced stress and concern about such issues may enable an unhoused
adult to prioritize self-improvement efforts.
2.4 Spatial Negotiation and Participatory Planning
Within the microcosm of an encampment, harmony, enhanced self-determination and
autonomy may be achieved. Encampments that provide security, stability, a sense of community
and a stake in ownership are more likely to meet the needs of their inhabitants and allow them to
thrive. However, just outside the boundaries of an encampment, there is an impact on the
citizens adjacent areas. These citizens may have real or imagined concerns about how the very
visual presence or actions of the encampment’s inhabitants will impact anything from the
community’s safety, sanitation, and health to its economy, property values, reputation and view.
Their needs differ from the encampments’ inhabitants, as do their values.

24
Within a municipality such as Long Beach, the distinct needs and values of these two
groups prompt a spatial negotiation. This process of navigating and managing physical space,
particularly in situations where multiple parties have interests or needs that intersect in that
space, is crucial for the planning of a site like an encampment for unhoused adults. Spatial
negotiation often involves finding compromises, reaching agreements, or resolving conflicts
related to the use, access, or allocation of physical spaces. Equitable spatial distribution is a
crucial aspect of spatial negotiation, encompassing the fair and just allocation of resources,
opportunities, and services across various geographical areas within a region or community. Its
emphasis lies in guaranteeing that every individual, irrespective of their geographic location,
enjoys equal access to fundamental services, amenities, and opportunities.
As is the case with both affordable housing sites and organized encampments, both result
in externalities or consequences that are spatially concentrated in the immediate surrounding area
and beyond. While not identical to the organized encampment concept described herein,
affordable housing sites are an occupancy type that has been referred to as a locally unwanted
land use (LULU), (Hankinson 2018). Other examples of LULUs are energy production sites,
drug addiction treatment centers, and water treatment facilities. Generally speaking, there is a
societal need for such uses. Yet, the not in my backyard (NIMBY) phenomenon occurs as
residents in a surrounding area tend to oppose a particular land use project as undesirable, unfair
or inappropriate. The voices of citizens should be heard and taken into consideration as land use
projects that are intended for long-term use, also present long-term externalities.
NIMBYism can be seen in the way citizens use their voices and their votes to influence
spatial matters, such as where unhoused persons receive services and find options for shelter.
Specifically, locations of homeless shelters in Long Beach illustrate NIMBYism in play. Figure

25
2 below, depicts a citywide map of Long Beach, which is divided into nine city council districts,
each identified with its respective district number. Within each district, there are census tracts of
varying sizes, shaded in a gradient from red to green. These colors indicate levels of home
ownership, with red representing the lowest and green indicating the highest. Additionally,
scattered across the map are blue shelter icons, representing approximately a dozen homeless
shelters. These shelters are dispersed throughout the city, including areas outside the official city
limits of Long Beach.
Figure 2: City of Long Beach, CA homeowner rates, shelters, and council districts
A noticeable pattern emerges in Figure 2: areas with lower rates of home ownership,
particularly downtown Long Beach, tend to have a higher concentration of homeless shelters.

26
Conversely, in eastern Long Beach, especially the northeast region where home ownership rates
are highest, 90-100%, there are no homeless shelters within the city limits. The one exception
that appears on the map, is a single shelter located in an enclave of unincorporated Los Angeles
County, outside the jurisdiction of Long Beach voters. Similarly, in the northwest of Long
Beach, there are no shelters within the city limits, but three are situated just beyond its borders.
Historically speaking, communities much like the City of Long Beach have concentrated
LULUs within areas without much political agency or clout as zoning and land use have been
primarily under the aegis of the local municipalities. Hence, their presence may remedy or
reinforce existing spatial representation (Hankinson 2023). In an effort to mitigate such
discrimination, socially conscious legislation (e.g., California Voting Rights Act of 2001)
entreats municipalities to dispense with at large (spatially diffuse) voting in favor of district
(spatially concentrated) voting. The desired outcome is to enable minorities, who might
constitute a majority within a district, to elect their own representatives to a city where they
typically would not have that opportunity. The outcome sought has been realized where minority
representation has markedly increased. However, an unintended consequence of what is arguably
well-intentioned is that LULUs such as affordable housing are encountering greater resistance
(Hankinson 2023).
Council members elected within districts are beholden to interests spatially concentrated
therein, rather than from afar, and thus are recalcitrant in accommodating immediately proximate
LULUs that may jeopardize their electoral success. In other words, NIMBY is apt in its
description where a voter may be indifferent or even favor a use such as encampments for the
unhoused within the city, yet downright vocal and oppositional if it were to be within their
immediate neighborhood. This sentiment holds undeniable truth when the voter is a homeowner.

27
Suburban homeowners and growth-oriented elites wield significant influence (Hankinson, 2018).
Likewise, urban residents who have invested in their homes traditionally hold both property
equity and a stake in the city’s decision-making processes.
As decision-making is dominated by individuals with ownership stakes, the unhoused are
consequently excluded from influencing matters that could impact them. Powerless, they reside
on the outskirts of society, existing in a vulnerable position on the margins. Their voices are
diminished or dismissed as inconsequential. One path toward elevating and including the voices,
opinions and values of the unhoused is participatory planning, known as an approach to decisionmaking and governance that involves actively engaging a broad range of stakeholders, including
community members, local residents, interest groups, and other relevant parties, in the planning
and decision-making processes that affect their lives and communities.
In an effort to learn more the daily activities of the unhoused, Greg Townley et al. (2016)
sought to understand the activity spaces of unhoused youth in Portland, Oregon. Rather than
conduct the research from their own perspective alone, they solicited homeless youth to
participate in sharing their own spatial knowledge through participatory mapping. By having
maps drawn by the youth, researchers gained valuable insights into the resources and activities
that held significance. Assumptions were challenged. One such instance was the researchers’
surprise that the youth did not include in their maps a large health clinic located in downtown
Portland, known to be accessed by the unhoused population at large. Perspectives from the
subjects offered unique insights that researchers had not considered (Townley et al, 2016).
The findings also highlighted that participants felt empowered and gained a sense of
competence and authority through their involvement in the mapping process. Engaging
participants in mapping their activity spaces could potentially lead to a broader integration of

28
their activities beyond the typical realms of homeless life, such as shelters, service centers and
food banks. This could facilitate the realization that their activities may include school,
employment, or hobbies, thereby offering a pathway towards transitioning into a stable,
mainstream lifestyle (Townley et al., 2016). Such insights are essential if public policy endeavors
to achieve the goal of reintegrating the unhoused into mainstream life.
Participatory planning serves as a vital mechanism not only for enabling individuals to
actively participate in processes from which they might otherwise be excluded, while also
fostering comprehensive engagement across all stakeholders and interests involved in addressing
complex issues such as homelessness. By involving diverse perspectives and interests in the
planning process, particularly when devising alternative housing options, a broad spectrum of
thoughts and emotions inevitably emerges. This inclusive approach ensures that various housing
alternatives are thoroughly considered and that resulting outcomes contribute to advancing
spatial equity within the entire community.

29
Chapter 3 Data and Methodology
The key goals of this project are to identify parcels of land within the City of Long Beach that
may be set aside for the chronically un-housed to take up residence in what may described as a
sanctioned encampment. In the previous chapter, research identifies how other locales (e.g.,
Portland, Seattle) attempt to provide similar accommodations. While the aforementioned cities’
approach might seem ad-hoc in confirming current encampments, this study attempts to identify
parcels of land to support both present and future needs. This chapter discusses the data and
methods used in this thesis project.
3.1 Data Sources and Data Preparation
This section introduces the data used for this study and how it will be used for the site
suitability method: weighted overlay. Table 1 below, lists the datasets and their sources to be
used in this thesis. The datasets were downloaded directly from the sources noted. Where
appropriate and necessary, datasets used are the most recent available.
Table 1. Data Sources
Dataset Type Purpose Date Published Source
City Boundary Polygon
Shapefile
Clip, Mask May 20, 2021 City of Long Beach
DataLB
Countywide Parks
and Open Space
Polygon
Shapefile
Buffer, Erase August 3, 2023 Los Angeles County
GIS Portal
Food Assistance Point
Shapefile
Weighted Overlay Nov 5, 2020 Los Angeles County
GIS Portal

30
Health Clinics Point
Shapefile
Weighted Overlay Nov 9, 2020 Los Angeles County
GIS Portal
Homeless Shelters
and Services
Point
Shapefile
Weighted Overlay Nov 5, 2020 Los Angeles County
GIS Portal
Homeless
Survey Areas
Polygon
Shapefile
Weighted Overlay January 2022 City of Long Beach
Multi Service Center
Hospitals and
Medical Centers
Point
Shapefile
Weighted Overlay Nov 9, 2020 Los Angeles County
GIS Portal
Metro Stations Point
Shapefile
Weighted Overlay Nov 5, 2020 Los Angeles County
GIS Portal
Parcels Polygon
Shapefile
Weighted Overlay Aug 19, 2021 Los Angeles County
Assessor
Schools Polygon
Shapefile
Buffer, Erase June 19, 2023 Los Angeles County
GIS Portal
3.1.1 Homeless Survey Areas (HSA)
An annual count of homeless known as a point in time (PIT) is conducted within Los
Angeles County with notable exceptions: Glendale, Long Beach and Pasadena. These three
municipalities have their own Continuum of Care districts and thus conduct their own count
apart from the rest of the county. City of Long Beach Human Services through its Multi Service
Center administers a count every year in January but occasionally it occurs in February. Sent out
in the twilight hours, teams of three to five trained volunteers conduct an in-person count in one
of fifty-two HSAs.

31
The importance of this data is to identify where current homeless populations congregate.
As it is assumed that individuals who are unhoused seek the most suitable environments, their
proximity to existing services such as healthcare, shelters, and food assistance may be able to
help identify vacant parcels that match similar distances to such services. Table 2 below shows a
January 2022 point in time (PIT) visual count of unhoused persons conducted by fifty-two teams
of volunteers assigned by Long Beach’s Multi Service Center to their respective HSAs.
Table 2. January 2022 PIT Visual Count within Homeless Survey Areas (HSA)
HSA Visual
Count HSA Visual
Count HSA Visual
Count HSA Visual
Count HSA Visual
Count
TEAM 1 79 TEAM 12 21 TEAM 20 08 TEAM 30 42 TEAM 40 07
TEAM 2 24 TEAM 13 05 TEAM 21 23 TEAM 31 06 TEAM 41 35
TEAM 3 07 TEAM 14A 07 TEAM 22 01 TEAM 32 16 TEAM 42 03
TEAM 4 11 TEAM 14B 19 TEAM 23 04 TEAM 33 05 TEAM 43 10
TEAM 5 16 TEAM 15A 04 TEAM 24 02 TEAM 34 08 TEAM 44 02
TEAM 6 52 TEAM 15B 26 TEAM 25 03 TEAM 35 01 TEAM 45 05
TEAM 7 04 TEAM 16 03 TEAM 26 26 TEAM 36 14 TEAM 46 04
TEAM 8 02 TEAM 17 06 TEAM 27 01 TEAM 37 02 TEAM 47 10
TEAM 9 15 TEAM 18 13 TEAM 28 02 TEAM 38 19 TEAM 48 13
TEAM 10 17 TEAM 19A 26 TEAM 29 33 TEAM 39 04 LAC 10
TEAM 11 42 TEAM 19B 11
3.1.2 Parcels
As the thesis seeks to identify suitable parcels for the unhoused, this dataset is central to
analysis. This project obtained parcel data from the County of Los Angeles Assessor’s Office
from the year 2021. Among the over five million parcels within Los Angeles County, 107,920
have been identified as within the City of Long Beach. The parcel dataset includes use, zoning,
land value and other descriptions of each parcel.

32
A key field in the dataset is the use code that encompasses zoning and its many
subcategories. The use code is a four-character code where the first digit is more general and the
latter is more specific. Conveniently, the common marker for vacant land is the letter “V” in the
last digit. By using this descriptor, the data may be filtered to only show vacant parcels
regardless of zoning.
Zoning, however, is a consideration to not completely overlook. As noted in Chapter 2,
other stakeholders in the community, particularly single family homeowners, are wary of zoning
changes that may negatively impact them. Thus, final analysis will provide information of the
zones of the suitable parcels identified. Zones are commercial, government, industrial and
residential. Below is Figure 3 showing the 1,779 vacant parcels of land within the City of Long
Beach.

33
Figure 3. Vacant parcels in Long Beach
3.1.3 Food Assistance
The availability and proximity of food is to be considered for site suitability as discussed
in Chapter 2. This project acquired locations of food assistance centers from the County of Los
Angeles GIS Portal. Unlike the Parcels dataset where only entries within Long Beach are
allowed, service datasets such as food assistance are not to be clipped in same manner. As the
project deems services within a mile to be reasonable, locations on the outside periphery of Long
Beach within that walking distance will impact findings. See Figure 4 for locations of food
assistance centers in the greater Long Beach area.

34
Figure 4. Food assistance centers in Long Beach Area
3.1.4 Metro Stations
Transportation, particularly public transit such as the Metro light rail system, is to be
considered, particularly in terms of how parcels are within walking distance. As this mode of
transportation addresses trips that can be greater than walking distance, its proximity to parcels
will be significant in determining overall suitability. A points shapefile, Metro Station,
originating from the Los Angeles County GIS Portal will be used accordingly. Figure 5 below
shows the stations of the Metro A line, formerly the Blue line.

35
Figure 5. Metro Stations in Long Beach Area
3.1.5 Shelters and Services
While this study aims to identify a complementing alternative for the primary purpose of
a shelter (i.e. a place of refuge), it acknowledges that shelters are part of the geographic context
of the unhoused. These locations serve as existing points of interaction where the unhoused can
access services (e.g., clothing, emergency food) and are within the reach of social advocates.
Like the other datasets mentioned earlier, this one also pertains to proximity. Data as points are
furnished by the County of Los Angeles GIS Portal. Much like the Food Assistance dataset,
which encompasses locations beyond Long Beach, the same principle applies to Shelters and
Services. Their suitability as options is not confined to city limits but rather to being within

36
walking distance of a potential parcel within Long Beach. See Figure 6 for locations of shelters
and services in the greater Long Beach area.
Figure 6. Shelters and Services
3.1.6 Hospitals
Hospitals are to be considered. The proximity for the unhoused as clientele coupled with
the reachability of the professionals therein are important factors. The presence of emergency
room facilities is also of paramount need for the unhoused whose lifestyle is inherently more
dangerous. Three hospitals are located within the city limits and an additional three are on the
city’s periphery to the north and northwest. The dataset, Hospitals and Medical Centers, is

37
provided by Los Angeles County GIS Portal. See Figure 7 where hospitals and health clinics
under the grouping of healthcare facilities are found in greater Long Beach.
Figure 7. Hospitals
3.1.7 Health Clinics
Additional healthcare facilities namely health clinics are to be considered in this study.
Again, the services need not be within Long Beach to be viable options for the unhoused. They
may be found in adjacent cities of Lakewood, Hawaiian Gardens and Los Angeles (i.e.
Wilmington neighborhood). Services encompass a gamut of medical needs from general to
reproductive. Dataset, Health Clinics, originates from Los Angeles County GIS Portal. See
Figure 8 for locations of health clinics marked in yellow and those that cater to the unhoused
marked in red in the greater Long Beach area.

38
Figure 8. Health Clinics
3.1.8 Schools
Schools within the City of Long Beach are included in this study for the application of
excluding parcels due to potential legal constraints. The dataset consists of parcels as polygons
and originates from the Los Angeles County GIS Portal. The dataset is broad in its reach where
administration, adult education and college join expected entries from elementary, middle and
high school. Further refinements and filters are employed to address the legal considerations.
Legal considerations are namely restricting the presence of registered sex offenders
within two thousand feet of a school where minors are present. Thus, the dataset, Schools, will
be refined to exclude parcels that are identified as college/universities, adult education and

39
administration. It is understood that minors are enrolled as students at local colleges as early
entrants and also may be concurrently enrolled while also attending high school. As the numbers
of these students in these situations are deemed to be small for the purposes of this study, the
colleges will be regarded as sites where children under 18 are not present. See Table 3
identifying 143 school parcels parsed out by type and whether or not minors are present.
Table 3. School Parcels within Long Beach
Type of School Parcel Count Children under 18
Administration 4 no
Elementary 85 yes
Middle School 15 yes
High School 23 yes
Junior and Senior High School 5 yes
K-12 2 yes
College/University 6 no, primarily
Adult Education 3 no
3.1.9 Parks
Included in this thesis is a dataset, Countywide Parks and Open Spaces, for the purpose
much like Schools to address potential legal challenges. The dataset also consists of parcels as
polygons and originates from the Los Angeles County GIS Portal. As the title of the dataset
suggests, it is broad in its reach where open spaces join parks as a group. Expected entries for
playgrounds, beaches and fields accompany nuanced ones such skate parks, swimming pools,
and dog parks. To address legal considerations further filters and refinements are employed.

40
Much like the aforementioned Schools dataset, the legal considerations in play also apply
for the dataset involving parks. As they are varied in use and the demographics they attract,
filtering is needed for entries that are primarily of interest to children.
As the parks are open to all including children, theoretically, all parks will have children
present. However, for purposes of this study, parks that have playgrounds will be filtered.
Additional recreational sites and facilities such as skate parks and swimming pools are also
included as they attract children under 18. Unlike the Schools dataset where parcels are
predominantly distinct in their use (e.g., elementary, college/university), parks with swimming
pools, splash pads and skate setups are located with playgrounds. Thus, the only determining
factor is whether a park has a playground or not. Within the City of Long Beach there are
seventy-one parks with playgrounds.
3.2 Site Suitability Analysis
This section describes the methods used for site suitability analysis. Initially, it discusses
the filtering process and how not all parcels will be considered. Then, it describes how data on
the number of unhoused individuals within each homeless survey area (HSA) is linked spatially
to parcels within those areas. This data is used to create a raster, which is then employed in the
weighted overlay method to assess site suitability. Following this, additional rasters are
generated based on the proximity of services (such as distance to food assistance) to the parcels
within the HSAs. These additional rasters are overlaid onto the previously created HSA parcel
raster. Next, values in each raster are reclassified to ensure consistency for the weighted overlay
method. All rasters are then integrated into the weighted overlay process, with each raster
assigned different weights based on empirical studies. This process results in a final raster that
depicts parcels with varying levels of suitability for the project, which can then be reviewed and

41
considered for further action. Finally, a sensitivity analysis is conducted to assess how legal
constraints may affect the suitability of sites initially identified as most suitable.
3.2.1 Filtering Parcels
Parcel data is sourced from the County of Los Angeles Assessor where it is updated
monthly. This dataset is known as LACounty_Parcels. As the study area is within the City of
Long Beach a vast majority of the 2.4 million parcels identified in the county will not be
applicable. Hence before any further filtering on other factors such as zoning and vacant land,
parcels must be located within city limits. As the target audience is the city council, their impact
is greatest within the city they govern.
As the LACounty_Parcels dataset is larger than necessary, the City Boundary dataset will
be used to clip it. The polygon within the latter dataset is used to extract parcels from
LACounty_Parcels that fall within its boundaries. A daughter dataset is created:
LongBeach_Parcels. Of the 2.4 million parcels in the county, approximately 106,000 have been
identified within Long Beach. Figure 9 is a diagram explaining the workflow.
Figure 9. Workflow for the LongBeachParcels layer

42
Further refinements are sought as this thesis seeks vacant parcels rather than those that
have standing structures. It is an important consideration as the need for vacant land to
accommodate encampments is key.
Discussion about placement of encampments within residential, commercial and
industrial zones undoubtedly will encounter resistance (i.e. NIMBYism). As there is identifiable
resistance from stakeholders as cited in Chapter 2, choosing one zone over another may not be
feasible. Rather, identifying vacant parcels regardless of zoning is sufficient. For the purposes of
this thesis, sites will be sought within the aforementioned three zones and also government.
3.2.2 Spatially Join HSA Visual Count to Parcels
Due to privacy concerns, pinpoint location of the 729 unhoused individuals identified
during the PIT is not available for this study to pursue. Rather, the Long Beach Multi Service
provides in a coarser spatial resolution the visual count of unhoused within the fifty-two
designated HSAs.
To help illustrate, Figure 10 below presents the PIT amongst the fifty-two HSAs. Each
HSA polygon is color-coded into five classes to represent visual counts, with Long Beach's
downtown exhibiting higher numbers in deeper, darker shades on a buff to dark ochre
continuum. Corresponding services are likewise depicted as self-evident points, reflecting their
respective locations throughout the city, notably downtown.

43
Figure 10: February 2022 PIT count, services
To ensure optimal service for the unhoused, it's crucial to consider where they currently
gather. Therefore, parcels situated within HSAs with higher population densities may initially be
seen as most suitable, without considering additional factors.
To incorporate this consideration into the site suitability analysis, each parcel within
every HSA will be spatially joined, allowing the visual count (i.e., the number of unhoused
individuals) to become one of its attributes.
3.2.3 : Proximity to Services
With parcels filtered to a manageable number and the visual counts within HSAs
spatially joined to them, the distances from the parcels to the nearest member of said services
will be recorded.

44
3.2.3.1 Proximity to Food Assistance
Food assistance centers are located within and on the perimeter of Long Beach.
Identifying a parcel of land that is as close as possible to such a center would be considered
advantageous for the success of an encampment as pursued in this thesis. Within ArcGIS, the
Near function provides the distance from a candidate parcel to the closest food assistance center.
Figure 11 is a diagram explaining the workflow.
Figure 11. Workflow for the Parcels Distance to Food Assistance layer
3.2.3.2 Proximity to Health Clinics
Health clinics are situated both within and around Long Beach. Finding a parcel of land
in close proximity to these clinics would be beneficial for the success of the encampment being
studied in this thesis as they provide free to low-cost medical care for the indigent. Further
dataset refinements are required, as certain health clinics in Long Beach are tailored to the
unhoused population, evident from their mission statements on respective websites. As a result,
health clinics not serving the unhoused are removed from the dataset. The near function in
ArcGIS calculates the distance from a potential parcel to the nearest health clinic. Figure 12
illustrates the workflow.

45
Figure 12: Workflow for the Parcels Distance to Health Clinics layer
3.2.3.3 Proximity to Hospitals
Hospitals are located within and on the perimeter of Long Beach. Identifying a parcel of
land that is as close as possible would be considered advantageous for the success of an
encampment as pursued in this thesis as they are the primary locations for emergency care.
Within ArcGIS, the near function provides the distance from a candidate parcel to the closest
hospital. Figure 13 is a diagram explaining the workflow.
Figure 13. Workflow for the Parcels Distance to Hospitals layer
3.2.3.4 Proximity to Metro Stations
There are eight metro stations situated within the City of Long Beach along the A line,
previously known as the Blue line. In this thesis, it is deemed beneficial for the success of an
encampment to identify a parcel of land in close proximity to one of these stations. Within

46
ArcGIS, the Near function calculates the distance from a potential parcel to the nearest station.
Diagram in Figure 14 illustrates this workflow.
Figure 14. Workflow for the Parcels Distance to Metro Stations layer
3.2.3.5 Proximity to Shelters and Services
Shelters and services are situated both within and around the perimeter of Long Beach. In
the pursuit of this thesis, finding a parcel of land in close proximity to these centers would be
deemed advantageous for the success of an encampment. The Near function within ArcGIS
calculates the distance from a potential parcel to the nearest shelter and service center. Figure 15
presents a diagram illustrating this workflow.
Figure 15. Workflow for the Parcels Distance to Shelters and Services layer

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3.2.4 Re-classification
To execute the weighted overlay method, the values for each dataset are reclassified. In
this study, all variables are organized into five classes.
For determining the classes based on the visual count, the Jenks natural breaks
classification method is used. Its aim is to minimize deviation within each class's mean while
maximizing deviation from the means of other classes (Chen et al, 2013, 47).
However, for the services involved, the Jenks method is not suitable because not all
distances are equally important. Walking distance is the primary factor, and thus anything longer
than that may be classified with the smallest value. Determining though what walking distance is
for classification purposes is not definitive as the value is not a universal constant. It is subjective
where one able-bodied individual may be able to traverse a mile in twenty minutes but others in
similar physical condition may wish not to expend five minutes to go no more than a quarter of
that distance.
A particular study states that a quarter of a mile is regarded as walking distance for
research in the U.S. However, the study’s survey of respondents shows that more than half of
walking trips exceed that value, with nearly twenty percent exceeding a mile. Of all the
respondents, a near unanimous did not have walking trips exceed two miles (Yang and DiezRoux, 2012, 14). Based on those findings, this project concludes that a median value of one mile
is well-justified for walking distance.
The classification of distances into classes is not evenly spaced but follows a somewhat
geometric progression. Distances of less than a quarter mile are assigned a value of 5.
Subsequent values generally increase at a greater rate, where a value of 2 is assigned to distances
ranging from 1.25 to 2 miles. Finally, any distances over 2 miles are classified as 1.

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Once the walking distance parameters are set, the five proximity to service variables
(food assistance centers, health clinics, homeless shelters and services, hospitals, and metro
stations) may complement the primary measure of population density, as determined by the
visual count within the homeless survey areas (HSA). This count pinpoints the current locations
of unhoused individuals and, by gauging the differing population densities across the fifty-two
HSA, offers insight into which parcels would be most suitable. See Table 4.
Table 4: Classification of Parcel Values for Variables
Homeless Survey Areas (HSA)
Visual Count
Walking Distance from Services (food
assistance, health clinics, homeless shelters
and services, hospitals, metro stations)
Parcel Value 5 = (64 – 79) 5 = (0 – .25 mi)
4 = (49 – 63) 4 = (.25 – .75 mi)
3 = (33 – 48) 3 = (.75 – 1.25 mi)
2 = (18 – 32) 2 = (1.25 – 2 mi)
1 = (0 – 17) 1 = ( > 2 mi)
While establishing a scale of 1 to 5 for the input rasters, it is acknowledged that the
output raster may not yield optimal results if confined to such a small range, particularly
considering the large number of parcels under consideration. Therefore, to allow for greater
nuance and differentiation in distinct values from the raster, the output raster will be scaled from
1 to 100, providing a broader range of outcomes for the assessment of suitable sites.
3.2.5 Weighted Overlay Method
After reclassifying the rasters, the weighted overlay method can be applied. Since the
total weight percentages must equal 100 and the weights must be integers, the six variable
weights may not be equal. For example, dividing 100 by 6 yields 16.667, which is not an integer.
Given that five of the six variables pertain to parcel distance to services, an initial equal value of

49
16 is assigned to each of these five variables, totaling 80. The remaining 20 is then allocated to
the sixth variable, which measures density among HSA. This adjustment ensures that all weights
are integers while reflecting the relative importance of each variable.
In this study, the HSA data indicates a preference for services among the unhoused, as
evidenced by higher visual counts near services clustered in downtown Long Beach. Therefore,
the initial values must be adjusted to account for these preferences. However, the challenge lies
in the heterogeneity of these services and the difficulty in determining which specific services
attract the unhoused the most.
To address this challenge, empirical data from similar circumstances involving unhoused
populations can be helpful in determining the weights for each service. For example, a study
conducted in Boston with formerly unhoused adults ranked transportation and grocery stores as
the highest priority services, followed by hospitals and community health centers (CHC), with
parks and libraries ranked lower (Chan et al, 2014, 147). Another study in Fort Worth, Texas,
which used GPS tracking and interviews with unhoused participants, returned similar results,
with finding food being the leading reason for travel (North et al, 2017, 669).
With these studies offering empirical justifications for varying preferences towards
services, adjustments must be made reasonably. Studies cited above have identified
transportation and grocery stores as the most highly preferred services. Given that metro stations
and food assistance centers are the closest equivalents, their weights in this model are increased
from sixteen to twenty. By elevating these variable weights, others inevitably need to be
decreased to maintain a total of one hundred percent for the method to be viable. Since the
studies also indicate a moderate interest in analogs to health clinics (community health centers)
and hospitals, adjustments for these are minimal, rounded to fifteen each. The remaining value of

50
ten is allocated to the last variable, homeless shelters and services. See Table 5 below. This
reduction is justified considering the thesis's objective is to identify a suitable site for an outdoor
sanctioned encampment, thus making the primary purpose of a shelter moot. Its need is minimal
and thus its weight is reduced. However, it's important to acknowledge that the dataset for
shelters also encompasses homeless services that are of interest to the unhoused and thus the
handicap imposed on this variable is not greater. Finally, although the studies provide assurance
that the adjustments are justified, they remain conservative because larger increases or decreases
could amplify errors, potentially leading to inaccurate conclusions.
Table 5. Weights for Model
Variable Initial Weight Adjusted Weight Reason for adjustment
Food Assistance 16 20 Chan and North studies show
greatest interest
Health Clinics 16 15 Chan study shows moderate
interest in CHC, a direct analog
to health clinics
Homeless Shelters
and Services
16 10 Encampment makes need for
shelter moot
Hospitals 16 15 Chan study shows moderate interest
Metro Stations 16 20 Chan and North studies show
great interest
Visual Count 20 20 Initial value remains constant
While establishing a scale of 1 to 5 for the input rasters, it is acknowledged that this
limited range might not yield optimal results given the large number of parcels under
consideration. To allow for greater nuance and differentiation, the output raster will be scaled
from 1 to 100. This broader range provides more detailed outcomes for assessing suitable sites.

51
Since the weighted overlay method only allows integer values, rescaling is necessary to
preserve granularity. For example, a parcel with a potential score of 3.1 would be treated the
same as one with a score of 3.9, both truncated to an integer of 3. On a scale of 1 to 5, many
results would fall within a narrow range, causing important differences to be lost. By adjusting
the scale to 1 to 100, fractional scores are converted into whole numbers, ensuring that finer
distinctions are maintained in the analysis.
3.2.6 Sensitivity Analysis to account for legal constraints
Results derived from the site suitability analysis may be deemed complete if not for legal
considerations. Despite court rulings that have curtailed enforcement of them, state laws namely
Jessica’s Law (2006) and Megan’s Law (1996) have restrictions on where registered sex
offenders may reside. They may not reside within 2,000 feet of a school or playground where
children are known to be present. As the population of the unhoused is not without offenders or
the potential to be, a site may be best found that is beyond those buffers.
Consequently, the results of site selection models may be further refined through the
exclusion of parcels lying within 2000 feet of a school or park. As earlier noted in Chapter 3,
datasets for schools and parks are refined to entries that reflect the presence of children. For each
dataset, Schools and Parks, a buffer polygon of 2000 ft is created around each feature. See
Figures 16 and 17 for workflows for Schools and Parks, respectively.

52
Figure 16: Workflow for Schools with 2000 ft buffer in Long Beach
Figure 17: Workflow for Parks with Playgrounds Buffer 2000 ft.
The results of every site selection model are then processed through the Erase tool where
parcels that are found within the buffers for parks and schools are erased from the final results.
See Figure 18 illustrating the 2000 ft buffer zones around park and school parcels in Long
Beach.

53
Figure 18: 2000 ft buffer around parks and schools

54
Chapter 4 Results
This chapter presents findings identifying the most suitable sites for the City of Long Beach to
allocate as sanctioned encampments for the unhoused. Initially, a vast number of parcels are
winnowed down to a more manageable selection. Subsequently, the preferences of the unhoused,
inferred from their reported location and proximity to services, are analyzed. The filtered parcels
and preference data are then processed using site suitability method, weighted overlay. Finally, a
sensitivity analysis is conducted on the results to ascertain if the recommendations adhere to
legal constraints, such as proximity to parks and schools. Parcels that meet these restrictions are
additionally presented as alternatives in such cases.
4.1 Filtering of Parcels
The Los Angeles County Office of the Assessor in 2021 recorded nearly five million
parcels. Narrowing down this count to the study area of the City of Long Beach results in
107,920 parcels. As discussed in Chapter 3, parcels are then refined by identifying zones with a
"V" designation (e.g., 100V), indicating vacant land. The number of 2021 parcels identified as
vacant were to 1,779. Further refinement, which excludes waterways, reduces the count of
potential sites to 327. Figure 19 displays parcels meeting these criteria, marked in purple.

55
Figure 19. 2021 Parcels Meeting Analysis Criteria of Vacant, no Waterways; N=327
4.2 Site Suitability Results
Results of the weighted overlay show that 327 parcels located in close proximity to
services report a higher cumulative score. No parcel achieved a perfect score of 100 where each
and every service variable is within a quarter mile and is located in an HSA that has the highest
density of unhoused. Where there is a diverse selection of services in a dense area such as the
downtown district in Long Beach, parcels are deemed more favorable. Figure 20 illustrates
broadly citywide and in greater detail the suitability from Low Suitability (Red) to High
Suitability (Green). Where services are scant in East Long Beach, parcels return low scores in

56
the teens. Conversely, a plethora of services in downtown Long Beach have nearby parcels
easily reaching highs of seventies or more in their scores.
Figure 20. Weighted Overlay Results
The results for the parcels are separated into five classes using the Jenks natural breaks
method. Since the results as seen in Figure 21 exhibit a bimodal distribution, with peaks at high
and low values and fewer in the middle, a standard deviation classification would not be
appropriate. Standard deviation classification assumes a normal distribution with a single central
peak, which does not accurately represent the bimodal nature of the data. Using Jenks natural
breaks allows for a more accurate representation of the data's inherent structure, ensuring that the
classification reflects the true distribution of parcel suitability.

57
Figure 21. Distribution of Weighted Overlay Values
Maximum value returned from the analysis reported a score of 83 whereas the minimum
score reported was 12. The mean score reported was 46.66 and the median score was 50.
The study aims to identify the most suitable sites for accommodating the unhoused based
on the six variables of interest. From the analysis, 68 parcels from the most suitable class, shown
in Dark Green in Figure 20 above, were selected for further review. Table 6 summarizes the
number of parcels in each Suitability Class and reports the range of results. Next, Table 7
summarizes critical information on each of the 68 parcels identified in the Most Suitable class.
Table 6. Results of Parcel Suitability by Class
Mean : 46.65806
Median : 50
12 26.2 40.4 54.6 68.8 83
Value
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
Count
Suitability Class Range N
Most Suitable 83 - 68 68
Somewhat Suitable 67 - 52 86
Neutral 51 - 36 25
Somewhat Unsuitable 35 - 23 70
Least Unsuitable 22 - 12 78

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Table 7. Most Suitable Class of Parcels
AIN Address Area Weighted
Overlay
Score
HSA
Visual
Count
Food
Assist
Distance
Health
Clinic
Distance
Homeless
Shelters
Distance
Hospital
Distance
Metro
Station
Distance
7269040909 1421 Chestnut Ave 0.08 83 4 5 4 5 4 4
7209022900 1827 Pacific Ave 0.37 79 4 5 4 5 3 4
7436005905 1426 W. 12th St 0.66 78 5 4 5 5 3 3
7436003902 1430 W. Anaheim St 0.48 78 5 4 5 5 3 3
7436007915 1470 W. 9th St 0.13 78 5 4 5 5 3 3
7436005907 1400 W. 10th St 0.29 78 5 4 5 5 3 3
7436004918 1355 W 11th St 0.22 78 5 4 5 5 3 3
7436005915 1557 W 9th St 0.28 78 5 4 5 5 3 3
7436004909 1152 Harbor Ave 0.11 78 5 4 5 5 3 3
7436007914 1470 W. 9th St 0.26 78 5 4 5 5 3 3
7269017902 1545 Long Beach Blvd 1.95 78 4 5 4 5 4 5
7271014003 1645 Daisy Ave 1.09 76 4 5 4 4 3 4
7269032906 1535 Atlantic Ave 0.56 75 4 4 4 4 4 4
7278016911 541 Golden Ave 0.11 75 3 5 5 4 3 4
7278016909 550 San Francisco Ave 0.11 75 3 5 5 4 3 4
7278016915 555 Golden Ave 0.11 75 3 5 5 4 3 4
7278016901 525 Golden Ave 0.11 75 3 5 5 4 3 4
7278016912 547 Golden Ave 0.11 75 3 5 5 4 3 4
7278016902 515 Golden Ave 0.12 75 3 5 5 4 3 4
7436005918 1530 W 12th St 0.55 73 5 4 5 5 3 2
7269030904 549 E 14th St 0.16 73 4 4 4 5 4 5
7269030905 1411 Atlantic Ave 0.24 73 4 4 4 5 4 5
7436008902 700 Pico Ave 0.61 72 5 4 4 4 3 3
7436007916 1564 W 9th St 0.26 72 5 4 4 4 3 3
7271011902 1501 San Francisco Ave 1.8 72 4 5 4 4 3 3
7210013900 925 E PCH Hwy 0.12 71 4 4 3 4 4 4
7209011900 2023 Pasadena Ave 0.14 71 4 4 4 4 3 4
7268006908 1725 Atlantic Ave 0.73 71 4 4 3 4 4 4
7268006913 1790 Atlantic Ave 0.03 71 4 4 3 4 4 4
7267006904 1199 E. 11th St 0.1 71 4 4 3 4 4 4
7268003913 998 E PCH Hwy 0.25 71 4 4 3 4 4 4
7268006916 1777 Atlantic Ave 0.04 71 4 4 3 4 4 4
7268006914 1777 Atlantic Ave 0.07 71 4 4 3 4 4 4
7268006915 1777 Atlantic Ave 0.07 71 4 4 3 4 4 4

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AIN Address Area Weighted
Overlay
Score
HSA
Visual
Count
Food
Assist
Distance
Health
Clinic
Distance
Homeless
Shelters
Distance
Hospital
Distance
Metro
Station
Distance
7402023903 1900 Cota Ave 2.47 71 3 5 5 3 5 2
7268003912 848 E PCH Hwy 1.81 71 4 4 3 4 4 4
7432006915 1555 Santa Fe Ave 0.47 70 5 4 4 4 4 2
7269020900 333 E Esther St 0.16 70 4 4 4 4 4 5
7278023905 321 Golden Ave 0.14 70 3 4 5 4 3 4
7278023907 0.09 70 3 4 5 4 3 4
7278024905 415 Golden Ave 0.03 70 3 4 5 4 3 4
7278018913 0.09 70 3 4 5 4 3 4
7278023902 0.07 70 3 4 5 4 3 4
7278024903 801 W 4th St 0.03 70 3 4 5 4 3 4
7278024909 817 W 4th St 0.23 70 3 4 5 4 3 4
7278016905 0.09 70 3 4 5 4 3 4
7278023900 815 W 3rd St 0.11 70 3 4 5 4 3 4
7278023908 0.06 70 3 4 5 4 3 4
7278023909 0.09 70 3 4 5 4 3 4
7278023910 0.06 70 3 4 5 4 3 4
7278016903 522 San Francisco Ave 0.27 70 3 4 5 4 3 4
7278016906 0.12 70 3 4 5 4 3 4
7278024906 423 Golden Ave 0.07 70 3 4 5 4 3 4
7278024904 413 Golden Ave 0.04 70 3 4 5 4 3 4
7278024908 813 W 4th St 0.23 70 3 4 5 4 3 4
7278023911 333 Golden Ave 0.08 70 3 4 5 4 3 4
7278023903 0.09 70 3 4 5 4 3 4
7278024907 0.03 70 3 4 5 4 3 4
7278018903 247 Golden Ave 0.08 70 3 4 5 4 3 4
7273024900 0.06 69 3 4 5 4 4 5
7278018902 0.05 69 3 4 5 3 3 4
7278018901 201 Golden Ave 0.08 68 3 4 5 3 3 4
7278018907 821 W Broadway 0.07 68 3 4 5 3 3 4
7278018909 817 W Broadway 0.02 68 3 4 5 3 3 4
7278018911 217 Golden Ave 0.06 68 3 4 5 3 3 4
7278018908 819 W Broadway 0.02 68 3 4 5 3 3 4
7278018910 221 Golden Ave 0.05 68 3 4 5 3 3 4
7278018912 213 Golden Ave 0.05 68 3 4 5 3 3 4

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Table 7 provides detailed information about each parcel, organized by column. The
columns include:
• AIN (Assessor’s Identification Number): A unique identifier for the parcel, similar to a
primary key used in database tables.
• Address: The location of the parcel. Some parcels do not have a listed address in records.
• Area (acreage): The size of the parcel measured in acres, a common unit in the U.S.
• Weighted Overlay: Scores rescaled 1 to 100 to maintain distinctiveness.
• HSA (Homeless Survey Area) Visual Count
• Food Assistance Distance
• Health Clinic Distance
• Homeless Shelters Distance
• Hospital Distance
• Metro Station Distance
Parcels are sorted from highest to lowest using their weighted overlay scores.
4.2.1 Identifying top five most suitable sites
The weighted overlay method has identified 68 parcels as most suitable for further
review. These parcels have received high scores due to their excellent proximity to services
needed by the unhoused population. The project aims to narrow these down to the top five sites.
Each site, which may consist of a single parcel or a cluster of spatially close parcels, is evaluated
based on its score, its total size (which must exceed a quarter of an acre), and the accuracy of its
vacant status as verified by satellite imagery.

61
4.2.2 Disqualifying features for otherwise highly ranked parcels
The highest-rated parcel, AIN 7269040909, located at 1421 Chestnut Avenue, received a
score of 83, making it the most suitable site for an encampment according to the weighted
overlay model. This parcel is less than a quarter mile from food assistance and homeless
services, earning a perfect score of 5 for each of these variables. The remaining variables scored
a 4, as they are within three-quarters of a mile.
Figure 22. AIN 7207004272, Seaside Park
However, further details, as shown in Figure 22, reveal that this parcel is not ideal for an
encampment. For instance, parcel AIN 7207004272 is only 0.08 acres, which is too small. If
adjacent parcels with a use code ending in 'V' for vacant had been identified, the size issue might
be mitigated. However, the adjacent parcels are not identified as vacant, suggesting that this
parcel may have been incorrectly marked as such. Even if the size and vacant use code issues are
resolved, this parcel would still be excluded in the sensitivity analysis due to its location within a
park or within two thousand feet of one, which is an immediate disqualifier.

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When the size criterion is met, other challenges arise. For instance, parcel AIN
7269017902 at 1545 Long Beach Blvd. spans nearly two acres. It also has a very high weighted
overlay score of 78. The parcel appears to be most ideal. Unfortunately, as shown in Figure 23,
the imagery reveals that this parcel is fully developed rather than vacant. If that weren’t already
disqualifying, the fact that the site is a school, would disqualify it in the sensitivity analysis.
Figure 23. AIN 726901902, 1545 Long Beach Blvd.
4.2.3 AIN 7209022900, 1827 Pacific Avenue
AIN 7209022900, located at 1827 Pacific Avenue and shown in Figure 24, spans a little
over a third of an acre and has the second-highest weighted overlay score of 79. It excels in
proximity to food assistance and homeless services, each scoring a perfect 5. Additionally, it is
within half a mile of both a health clinic and a metro station. Its proximity to a hospital, scoring a
3, indicates it is about a mile away from such services. Satellite imagery confirms that the parcel
is fully contiguous with no structures or developments present.

63
Figure 24. AIN 726901902, 1545 Long Beach Blvd.
The parcel is situated in a mixed-use neighborhood, with high-density residential housing
towards the rear and commercial retail along Pacific Avenue and nearby Pacific Coast Highway.
Given that the parcel is less than a quarter of a mile from existing homeless services, acceptable
tolerance for an encampment potentially exists. However, this is not guaranteed, and therefore,
additional sites need to be considered as viable alternatives.
4.2.4 AIN 7436005905, 1426 W. 12th St., cluster of three parcels
The third highest score of 78 for AIN 7436005905 at 1426 W. 12th St. is promising. It
amounts to more than half an acre and is adjacent to other top-ranking parcels, 7436003902 and
7436005918, as shown in Figure 25. Two of these parcels, 7436005905 and 7436003902, score
an impressive 78, with mostly fours and fives, except for a three for metro station proximity. The
third parcel (7436005918) scores a two for the same variable, but it is only about 60 yards from
the other two, which earned a three. Distance is no more than a mile and a quarter to the nearest
metro station, which is within reasonable walking distance.

64
Figure 25. AIN 7436005905, 7436003902, 7436005918
Located a short distance from the Port of Long Beach, these three parcels in aggregate
come in a generous 1.7 acres. Of the three parcels, two are zoned for industrial use and the
remaining one for government use. The latter designation may be incorrect, though, as the
imagery suggests its use is identical to the other two.
Other encouraging details about the parcels are also present. They are well-lit, as
evidenced by the imagery showing light posts over the parking lot. Being already paved, they are
more suitable than other vacant dirt lots for setting up tents for the encampment. Perhaps most
importantly, the Long Beach Multi Service Center (LBMSC), the department overseeing the
city’s homeless services, is headquartered just one-tenth of a mile away and has an onsite health
clinic. This proximity may help provide direct oversight and political support for a site that might
be considered a LULU.
Considering that the site would be viewed as a LULU (locally unwanted land use) in
other areas of the city, its close proximity to another LULU in the industrial area, the Long
Beach Multi Service Center itself, could potentially alleviate objections. The LBMSC already

65
exists and thus has set a precedent for establishing such a presence. Nevertheless, locating the
encampment away from Long Beach’s core districts may inadvertently reinforce the perception
that the unhoused population is unwelcome and marginalized, both literally and figuratively.
4.2.5 AIN 7436004918, 7436004909, 1355 W. 11th St.
In the same area as the Long Beach Multi-Service Center (LBMSC) lies a cluster of two
parcels situated at 1355 W. 11th St., identified as AIN 7436004918 and 7436004909 as seen in
Figure 25. Together, these parcels cover a third of an acre, one block south of the LBMSC.
Although their combined size is smaller than the 1426 W. 12th St. site, which spans half an acre,
these two parcels are contiguous, unlike the three spatially close but separate parcels of the other
site. Additionally, the two parcels have a weighted overlay score of 78, similar to the previous
site. Their proximity to the health clinic and homeless services at the LBMSC earns them a score
of 5 for each service.
Figure 26. AIN 7436004918, 7436004909, 1355 W. 11th St.

66
Imagery reveals that this site is not completely vacant, as there are dwellings present.
Initially, this might suggest the site is inappropriate due to existing development and an
erroneous vacant categorization. However, further examination shows that these dwellings
resemble cottages. Figure 27, featuring Google Street View imagery dated February 2023,
indicates that these cottages are equipped with air conditioner units, suggesting they have been
used for habitation. Currently, they do not appear to be actively occupied and haven't been for
several years, as evidenced by past Google Street View captures. These structures could
potentially be repurposed as tiny homes, adding value to the site.
Figure 27. Google Street View imagery, February 2023, 1355 W. 11th St.
Despite the promising amenities, the site's location in the Port of Long Beach area, where
industrial activity is prevalent, raises concerns. Although the LBMSC is already established in
this area, there is a risk that continuing to use this site may perpetuate the marginalization of the
unhoused population.
.

67
4.2.6 AIN 7436007916, 1564 W. 9th St.
Abutting railroad tracks in the Port of Long Beach, AIN 7436007916, as shown in Figure
28, is completely vacant. There is no development on its quarter-acre of land. Although it has a
weighted overlay score of 72, which is lower than the previously mentioned sites, it is still
among the 68 parcels identified as most suitable. None of the essential services are within a
quarter of a mile. However, most are within half a mile, except for the metro station and hospital,
which are about a mile away.
Figure 28. AIN 7436007916, 1564 W. 9th St.
Despite its high score, the location raises concerns about warehousing and hiding the
unhoused population, as it is well within the port area with constant views of railyards and
shipping containers. If other sites face opposition due to NIMBYism, this site might serve as a
last resort.

68
4.2.7 AIN 7271011902, 1501 San Francisco Avenue river-facing parcel
Where parcels with higher rankings have failed due to not factually being vacant or not
meeting a minimum size, AIN 7271011902, located at 1501 San Francisco Avenue, qualifies
easily. The parcel is quite sizeable at nearly two acres. Imagery shows it to be undeveloped
vacant land with a minor flagpole salient providing entry from the street. It also abuts the Los
Angeles River, as seen in Figure 29.
Figure 29. AIN 7271011902, 1501 San Francisco Avenue
Although this parcel does not rank in the top ten of the most suitable parcels, it is still
within the select category of most suitable with a score of 72. Furthermore, as an individual site,
it ranks among the top five qualified. Additionally, walking distance to services is well within
reason where most services are within half a mile.
Looking closely at the imagery of AIN 7271011902 in Figure 29 once more shows a
curious detail: the east bank of the Los Angeles River, immediately adjacent to the parcel, is
dotted with ad hoc encampments of the unhoused. This visual finding is prima facie evidence

69
complementing the findings that this potential site for a sanctioned encampment would be looked
upon favorably by the unhoused without much effort.
The location sits on the side of Long Beach's downtown, rather than the facing Port of
Long Beach, thus mitigating to a degree the suggestion that the site is on the margins.
Additionally, its discreet entrance, set back from another parcel, helps avoid unnecessary
attention, positive or negative. The scenic view of the Los Angeles River softens its industrial
surroundings, and its adjacency to the Los Angeles River Bikeway provides convenient access
for potential residents to come and go by bicycle.
While 1501 San Francisco Avenue appears ideal due to its significant size, undeveloped,
and proximity to the unhoused already camping nearby, its closeness to a park or school might
pose a challenge that could be difficult to overcome.
4.3 Sensitivity Analysis
A total of 327 parcels within Long Beach underwent analysis using weighted overlay to
determine their suitability for a sanctioned encampment. From this pool, 68 of those parcels
emerged as the most suitable following a five-classification breakdown using the Jenks natural
breaks method. Further refinement was undertaken to adhere to legal considerations, resulting in
the disqualification of parcels located within 2,000 feet of parks and schools. This criterion
significantly reduced the number of viable parcels to ten, as detailed in Table 8. These remaining
parcels primarily comprise three main sites (1426 W. 12th St., 1355 W. 11th St., 1564 W. 9th
St.), along with some parcels that, although categorized as vacant, contain disqualifying
structures.

70
Table 8. Most Suitable Parcels Qualified, Sensitivity Analysis
AIN Address Area Weighted Overlay
Score
Site
7436005905 1426 W. 12th St 0.66 78 1426 W. 12th St
7436003902 1430 W. Anaheim St 0.48 78 1426 W. 12th St
7436007915 1470 W. 9th St 0.13 78 structure
7436005907 1400 W. 10th St 0.29 78 structure
7436004918 1355 W. 11th St 0.22 78 1355 W. 11th St
7436005915 1557 W. 9th St 0.28 78 structure
7436004909 1152 Harbor Ave 0.11 78 1355 W. 11th St
7436007914 1470 W. 9th St 0.26 78 structure
7436005918 1530 W. 12th St 0.55 73 1426 W. 12th St
7436007916 1564 W. 9th St 0.26 72 1564 W. 9th St
Among the disqualified sites are AIN 7209022900 at 1827 Pacific Avenue, the second
best-ranked site, and AIN 7271011902 at 1501 San Francisco Avenue. Despite both sites having
undeveloped lots in the core of Long Beach, their proximity to parks disqualifies them.
Specifically, the 1.7-acre vacant lot at 1501 San Francisco Avenue, which abuts the waterfront,
could not meet the required buffer distance from Seaside Park as illustrated in Figure 30.

71
Figure 30. 2,000 ft buffer around Seaside Park
Parcels situated in predominantly industrial areas, particularly around the Port of Long
Beach and its immediate environs, emerge as viable options beyond the buffers of parks and
schools. The three sites depicted in Figure 31 are located in one of the few areas of Long Beach
not constrained by proximity to parks or schools..
Figure 31. AIN 7436005905, 7436003902, 7436005918 outside 2000 ft. buffers

72
This may explain why the conveniently located Long Beach Multi Service Center is
outside these restricted areas. However, while these sites qualify under these legal constraints,
they arguably perpetuate the marginalization of the unhoused to the city's periphery, where park
and school zones become de facto exclusion zones. Given this concern, considering an additional
site beyond the class of most suitable parcels is warranted.
4.3.1 AIN 7207004271, 7207004272, 2990 Atlantic Avenue
Reviewing parcels for size and confirming they are without structures, AIN 7207004271
and the adjacent parcel 7207004272 are suitable. They are located at 2990 Atlantic Avenue, on
the city limits with the independent enclave of Signal Hill. Additionally, as shown in Figure 32,
the parcels are just outside the buffer for schools. The buffer for parks is closer and in fact grazes
the southwest corner of parcel 7207004271.
Figure 32. AIN 72017004271, 7207004272, 2990 Atlantic Avenue

73
Both parcels received scores of 65, placing them within the highest level of the
Somewhat Suitable classification range of 67 - 52. Although these scores may suggest
inferiority, the underlying factors indicate appropriate suitability. Each parcel is within a quarter
mile of food assistance and a hospital, specifically near the Salvation Army and Long Beach
MemorialCare Medical Center, respectively. Additionally, the Willow Street Metro Station is
less than half a mile away, providing transportation to services that might not be within walking
distance.
Homeless services are nearly two miles away, but this may become less significant if an
encampment is established. One factor contributing to the lower overall score is that the parcels
are not located in a high-density area for the unhoused, with a score of 2 for the Homeless
Survey Area (HSA) Visual Count. However, this may be less critical, as establishing an
encampment in a location with necessary nearby services might outweigh the need to be in an
area with a high density of unhoused individuals.

74
Chapter 5 Conclusions and Discussion
The purpose of this study was to identify a parcel of land within the City of Long Beach most
suitable for the use of chronically unhoused individuals to reside in sanctioned encampments. In
further identifying such a parcel, the study ranks parcels using a site suitability method known as
weighted overlay to determine their proximity to services used by the unhoused. The study also
aims to select a site that considers the population's preferences. The weighted overlay method
employs a differing weights supported by empirical studies, incorporating a density metric. This
chapter will explore the study's findings and their potential to guide the city in addressing the
issue. The results are first discussed, followed by the methodology and study details, and finally,
suggestions for future work to improve the process and outcomes are presented.
5.1 Conclusions
As stated in Chapter 1, the rate of homelessness, particularly for the chronically
unsheltered, has continued to rise to unprecedented levels. On a single night in 2020 in the U.S.,
nearly four in ten unhoused persons were in unsheltered locations such as on the street, in
abandoned buildings, or in other places not suitable for human habitation. Municipalities
throughout the country, especially on the West Coast (e.g., Seattle, Portland, Sacramento,
Fresno, Los Angeles), have been attempting various methods and ideas: shelters, housing first,
and tent encampments.
The approach presented in this study argues to accept that encampments for the
chronically unhoused are not a complete solution but can be part of a multi-pronged strategy to
address homelessness. This study seeks to determine the viability of parcels for establishing

75
sanctioned encampments by using site suitability method, weighted overlay, to assess proximity
to essential services (e.g., food assistance). Unlike most efforts that have often been indifferent to
the needs and preferences of the affected populace, this study aims to give greater consideration
to parcels that are closer to where the unhoused are currently congregating.
The initial filtering of parcels yielded mostly straightforward results, identifying those
within the Long Beach city limits and marked as vacant in their use code. However, further
refinements were necessary to address illogical situations. For instance, bodies of water like the
Los Angeles River have parcels recorded as 400V, Government vacant land, which are clearly
unsuitable for potential sites. These parcels were immediately disqualified. Parcels below a
reasonable size, such as a quarter of an acre, were not automatically excluded. This is because
clusters of adjacent parcels might collectively exceed that size and qualify as potential sites.
Filtering too early could inadvertently remove suitable locations among these clusters. After
filtering to a more manageable number, 327, the parcels were processed through site suitability
method: weighted overlay. Following this, a manual review of the sites was conducted.
The suitability analysis used weighted overlay with weights adjusted based on empirical
data reflecting the preferences of unhoused individuals in similar studies. Raw values are reclassified from 1 to 5, where higher numbers indicated closer walking distances from the parcel
to the service.
Since the weighted overlay method is restricted to integers, fractional numbers in the
analysis would be lost. To mitigate this, the output values were rescaled from 1 to 5 to 1 to 100.
This rescaling preserved distinctions between values such as 3.1 and 3.9, which would otherwise
both be seen as 3, but are more accurately represented as 62 and 78 on the rescaled scale.

76
The study returned the top-ranked parcel, AIN 7269040909, with a score of 83. Despite
its proximity to services within a quarter mile, manual review revealed that it poorly qualifies as
an encampment site. It is too small at .08 acres and lacks adjacent vacant parcels for clustering.
Imagery indicates that it is not a vacant lot but rather a developed section of a city park. Likely, a
misclassification of the parcel’s use code as vacant led to its erroneous inclusion for
consideration.
Misclassification is common among the entries, despite monthly updates by the Los
Angeles County Assessor. Records are not uniformly corrected, making it challenging to pursue
valid vacant alternatives to the top-ranked but disqualifying parcel at Seaside Park. Many entries
scored well but were ultimately deemed unsuitable due to contradicting imagery.
5.1.1 Preferred Sites
Imagery at 1827 Pacific Avenue was true to its categorization as vacant. Scoring the
second highest at 79, the parcel AIN 7209022900, is vacant. It boasts perfect scores of 5 for
proximity to food assistance and homeless services, and is also within half a mile of a health
clinic and metro station. Located in a mixed-use neighborhood with high-density residential
housing and commercial retail, it lies less than a quarter of a mile from existing homeless
services, suggesting potential tolerance for an encampment. The site is well within the core of
Long Beach thus minimizing concerns for marginalization that may arise in placement on the
periphery of the city.
Despite concerns about further marginalization due to their proximity to the port, sites in
the industrial area of Long Beach do comply fully with legal constraints. Among these, 1355 W.
11th St. stands out as particularly promising. Its proximity to the Long Beach Multi-Service
Center (LBMSC) matches that of the site at 1426 W. 12th St., but with the added advantage of

77
having two contiguous parcels. Additionally, the presence of cottages that could be occupied by
the unhoused is a unique benefit not found at other sites. This detail is significant. Given that
1426 W. 12th St. and 1355 W. 11th St. both have equal scores of 78, ancillary features like the
cottages could make 1355 W. 11th St. the preferred choice.
5.2 Future Work and Considerations
Numerous parcels documented by the Los Angeles County Assessor have been filtered
and processed in this study. First, parcels outside the city limits of Long Beach were eliminated,
and then, more importantly, those marked as vacant were identified. The presence of many
parcels listed as vacant but not actually being vacant is troubling. Future work involving the
dataset from the County Assessor will need to account for this error rate. Relying solely on the
County Assessor for accurate descriptions will not suffice. Any future work will benefit from
incorporating datasets from private sources that are motivated to provide excellent data for profit
and maintaining their reputation. Sources catering to the real estate sector, particularly
developers, come to mind.
Where data may be not accurate for the parcels, data for the human factor is too coarse.
In an effort ostensibly to protect privacy of individuals, Long Beach’s Multi Service Center
declines to share geographic coordinates, points, or addresses of where interviews take place
during a Point in Time (PIT) exercise. Instead, data is aggregated into counts of individuals
interviewed within each PIT team's assigned Homeless Service Area (HSA). Consequently, a
loss of spatial resolution occurs. Details of individuals' backgrounds, such as race, mental health,
and length without ideal shelter, are blurred into a general consensus for the HSA where they
reside.

78
Using point data instead of polygon data in this study would have been more versatile to
manipulate and use. Counts of individuals easily exceed double digits in each of the fifty-two
PIT areas, yielding a potential record count exceeding thirteen hundred. With these numbers,
other methods of analysis, such as geographic weighted regression, may be pursued.
Understanding your target market, in this case the chronically unhoused, involves more
than just gathering biographical information. Details about a population's race, gender, and
health have been documented alongside the Point in Time (PIT) count each year. However, there
is a lack of data on what unhoused individuals desire in a place to call home. The Long Beach
Multi Service Center could benefit everyone by conducting thorough surveys of the unhoused
during the PIT session. If these surveys are already being conducted, the data should be made
available to the public in a reasonable manner, preferably detailing specific points rather than
generalized areas where the unhoused congregate.
A fundamental detail of the encampment envisioned is that it is a place for the
chronically unhoused to find refuge where other remedies such as affordable housing and
shelters cannot. The latter impose constraints on what is permissible such as abstaining from
drugs and alcohol, prohibiting pets, imposing limits on personal property and restricting
relationships with significant others. However, allowances can only go so far. Should the
encampment adopt a laizzez-faire approach, it may jeopardize its integrity and purpose. If taken
to its logical extreme, members of the chronically unhoused who are registered sex offenders
may be welcomed but their very presence would endanger the encampment’s existence due to
legal reasons.
Laws such as Megan’s Law (1996) and Jessica’s Law (2006) have many restrictions for
registered sex offenders such as prohibition from living within 2,000 feet of any school or park

79
located within the state. Furthermore, a jurisdiction such as the City of Long Beach is required to
notify the public about offenders, particularly high risk. Thus, implementation of an encampment
as envisioned in this study will need to consider whether it will restrict itself to locations
unencumbered or adopt rules, such as single gender, no narcotics, no alcohol, akin to those found
in existing solutions, namely shelters.
A conceivable, unintended consequence of legislation aimed at registering sex offenders
and their whereabouts is that willful ignorance may be more insidiously desirable than full
awareness. If the City of Long Beach pursues and sanctions an encampment for the chronically
unhoused, it becomes necessary to determine if occupants are residents after thirty days. If so,
laws such as those regarding sex offenders are more applicable where notification requirements
are in play. Municipalities may not wish to have the legal responsibility or liability that
accompanies. Where the onus is primarily on the individual with such a requirement, the liability
shifts to a municipality who is responsible for public safety. Hence, if a municipality is aware
and fails to inform, it is culpable particularly if a tragedy unfolds.
The driving motivation for this study is to identify a parcel of land where chronically
unhoused may take up residence thus perhaps reducing the presence of illegal encampments
throughout the city. If the city is to take up such a solution it will tacitly acknowledge the desires
of the populace it wishes to aid and comfort. A challenge though for the city is that an
encampment envisioned, arguably, is a LULU and NIMBYism will likely emerge. Where
currently the unhoused are diffused or situated in areas where public opposition has not
coalesced, establishing a pointedly, visible site for unhoused may have politicians elected
hesitant to pursue it. Nevertheless, the solution may be inevitable as the cries for the unhoused to
“not be in my backyard” may be already too late. The unhoused are in everyone’s backyard if not

80
already in the front yard on the sidewalks. A solution such as one proposed in this study is
warranted.

81
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Abstract (if available)

Abstract The rate of homelessness in the U.S. has steadily risen since 2016, prompting a focused effort to eradicate this crisis primarily through indoor shelters and permanent, affordable housing solutions. However, many unhoused individuals continue to camp nightly in various self-selected locations, lacking the basic necessities for habitation and doing so contrary to official public policy. Despite the inherent dangers and discomfort of outdoor living, some chronically unhoused individuals prefer it to traditional housing options. Emergency shelters present barriers to entry based on lifestyle, often don’t meet the desire of unhoused individuals for a sense of community and belonging, and have proven inadequate in meeting public health mandates, such as those required during the COVID-19 pandemic. As an alternative, various forms of outdoor housing encampments for chronically unhoused adults have emerged, particularly in U.S. cities on the West Coast. This project focuses on identifying suitable sites within Long Beach, California for such an encampment, capable of providing potential residents with access to basic necessities including potable water and sanitation. Sites within walking distance of essential services (e.g., food assistance, health clinics) are evaluated for their suitability using a method of analysis known as weighted overlay where the weights are based on the preferences of the unhoused population, supported by empirical studies for justification. Additionally, a sensitivity analysis is conducted to account for parcels within 2,000 feet of schools and parks that are subject to heightened scrutiny due to legal and safety concerns. The project must balance community norms with the needs of the unhoused population. The "Not in My Backyard" (NIMBY) mindset often opposes initiatives that disrupt established norms or introduce locally undesirable land uses (LULUs). By re-imagining outdoor sheltering options and incorporating insights from community dynamics, this project aims to offer more effective and compassionate solutions for the unhoused in Long Beach, California.

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Asset Metadata

Creator Fuller, Brian Michael (author)

Core Title Identifying suitable sites for sheltering outside in Long Beach, California

School College of Letters, Arts and Sciences

Degree Master of Science

Degree Program Geographic Information Science and Technology

Degree Conferral Date 2024-05

Publication Date 06/12/2024

Defense Date 04/25/2024

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag encampments,GIS,homeless,long beach,LULU,NIMBYism,OAI-PMH Harvest,sheltering,site suitability,unhoused,weighted overlay

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Ruddell, Darren (committee chair), Lester, Katherine (committee member), Vos, Robert (committee member)

Creator Email bmfuller@gmail.com,bmfuller@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC11399617B

Unique identifier UC11399617B

Identifier etd-FullerBria-13085.pdf (filename)

Legacy Identifier etd-FullerBria-13085

Document Type Thesis

Format theses (aat)

Rights Fuller, Brian Michael

Internet Media Type application/pdf

Type texts

Source 20240612-usctheses-batch-1167 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright.

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA

Repository Email cisadmin@lib.usc.edu