Evaluation of Local Comprehensive Plans to Vacancy Issue in a Growing and Shrinking City

Abstract

Vacant and/or abandoned properties exist in every city regardless of whether they are growing or shrinking, and the properties are not always a bad thing, and all underutilized land does not have to be developed. Some types of vacant land are unused but can be productive. Some may have natural resource value for inhabitants and provide green space such as parks space or green infrastructure. Once a city has too much vacant land, it may reflect a long cycle of depopulation and economic downturn. So, a lot of vacant lots is of concern in shrinking cities to change them into a valued commodity. In contrast, insufficient vacant land might hinder future growth and development. Since the vacant land can be a potential opportunity or threat to spur economic development, it is critical to understand vacancy pattern and its drivers and create appropriate policies for each city. By doing so, it would be possible to find the most effective land supply usage for cities having different characteristics and patterns of vacancy. Therefore, this study compares the pattern primary factors of vacancy of a growing city, Fort Worth and shrinking city, Chicago and evaluate whether each city has established planning policies for reducing negative effects and increasing efficient usages. The findings show that transportation and physical factors are strong determinants of the vacancy in a shrinking city, while socioeconomic conditions tend to influence more powerful on increasing vacant properties in a growing city. Furthermore, the outcomes of plan evaluation indicate that the vacancy pattern and its primary factors are grasped and handled firmly in Fort Worth.

1. Introduction

Today, the world is steadily becoming more urban as a growing number of people move to cities and a large number of structures was built in the areas. While only two percent of the world’s population lived in cities in 1800, the urban population is expected to reach 60 percent in 2030. However, the trend of urbanization is not distributed evenly, as not every city absorbs the rapid urbanization. While rapid population growth and urbanization has been a serious issue in developing cities, many former manufacturing industrial cities in developed countries have experienced serious depopulation, job loss, and economic decline in recent decades. Since vacant properties can be a critical theme to measure a collapse of economy and depopulation, the shrinking cities have been concerned for why some cities are declining more than others, and how the vacant properties in the shrinking cities can be regenerated effectively. Of course, vacant properties exist in growing cities as well. In growing cities, vacant properties can be increased at urban fringes for future growth in population and size to improve the scale of economies and urban services by a large scale of annexation. Despite these different characteristics, however, most cities regardless of whether they are growing or shrinking have pursued growth-oriented development strategies due, partially, to their inability to accurately predict future urban growth/decline patterns and establish proper vacancy related policies [1].

In this regard, this study reviews the potential role of the comprehensive plan—That describes the future developments of the communities—in reducing the vacancy issues in a growing city, Fort Worth and a shrinking city, Chicago as follow-up research. In precedent researches, three studies were conducted to (1) predict future possible vacancy scenarios for City of Fort Worth, Texas (which represents a growing city) [2] and (2) predicting City of Chicago, Illinois (a shrinking city) using Land Transformation Model [3] and (3) identifying the principal causal mechanisms affecting vacancy trends by quantifying determinants of vacancy [4]. These three previous studies found that the primary vacancy determinants are different between a shrinking city and a growing city. While market conditions and economic statuses such as housing value, unemployment rate, and income are the most influential variables affecting vacant land transformation in Fort Worth, transportation systems and physical conditions such as proximity to highway and year structure was built play a larger role in Chicago. However, how well the planning interventions and policies contribute to ease the vacant issues was limited. The outcome of this study is expected to set up the right direction in future plans for the reduction of urban vacancy and its consequences.

Understanding local urban issues precisely and suggesting suitable planning policies is an important role of planners and decision-makers. To understand whether planning mechanisms have been sufficiently implemented in practice, this study suggests a newly developed plan evaluation protocol based on the future possible vacancy scenarios.

2. Literature Review

2.1. Growing Cities and Shrinking Cities

While the term about urban growth has been widely discussed, the definitions, measurements, and symptoms have been categorized quite differently, depending on the time, space and communities. Thus, it is difficult to identify both growing and shrinking cities with a single general concept.

A growing city is often recognized as a city experiencing rapid population and economic growth and increase in neighborhood quality [3,5,6,7]. Generally, since growing economies induce with increasing the demand and supply of both works and consumers, the economic growth is strongly associated with population growth. Therefore, most planning and economic literature define a growing city as a city experiencing population and employment growth for a certain time period, while shrinking cities as the opposite.

The population is also the most popular tool in defining and identifying the shrinking city. Schilling and Logan (2008) defined a shrinking city as older industrial city losing population more than 25% over the last 40 years, and the Shrinking Cities International Research Network (SCIRN) also defined shrinking cities as an urban area with more than 10,000 residents that have experienced depopulation for more than two years and the consequential economic crisis [8,9]. Among cities in the U.S. with populations of at least 50,000, the list of the 10 fastest shrinking and growing cities between 2014 and 2016 was announced by the U.S Census Bureau. The Census Bureau noted that the fastest shrinking cities were scattered around the Midwest and South, while the fastest growing cities were predominately in Texas. This report also identifies the urban growth trends between 2000 and 2010 with population growth by cities with more than 250,000 population. Among 62 cities having at least 250,000 population in 2000 in the U.S., Fort Worth recorded the largest population growth, 206,512 people for a decade, while Detroit and Chicago lost over 200,000 people Chicago between 2000 and 2010.

Depopulation itself would not be an issue to a city, or an indicator of unhealthiness of a city [10], if a city is planned right, but negative consequences such as a reduction of tax revenue, a decrease of urban vitality, or an increase of vacant homes [11,12].

2.2. Vacant Land

Every city makes efforts to promote economic growth using a number of resources. Among those resources, land plays an important role, especially vacant land [13]. However, there is a multitude of ways to define and measure vacant properties; it can be defined by the situation, municipality, function of the parcel, and/or duration of vacancy (see

Table 1. Definition and Description of Vacant Land in Previous Literature.

Author (s)	Year	Definition/Description
Niedercorn & Hearle	1964	● Land uses which are undeveloped and are not underwater
Northam	1971	● Remnant parcels, unbuildable parcels with physical limitations, corporate reserve parcels, parcels held for speculation, institutional reserve parcels
Greenberg et al.	1990	● TOADS: Temporarily Obsolete Abandoned Derelict Sites
Accordino & Johnson	2000	● Vacant and abandoned buildings or lots that have been vacant for two years or more
Pagano & Bowman	2000	● Unused or abandoned land or land that once had structures on it, but also the land that supports structures that have been abandoned, derelict, boarded up, partially destroyed, or razed
Davidson & Dolnick	2004	● Lands or buildings that are not actively used for any purpose
		● A lot or parcel of land on which no improvements have been constructed
NVPC	2005	● Not only under-performing industrial buildings and lots (brownfield) but also residential and commercial properties (greyfield) that have been unoccupied or beyond repair over a year
Nemeth & Langhorst	2014	● Land where no structure exists and is not currently used by human
		● Underutilized parcels or lots that function below their functional or capital-producing capacity
		● Property with abandoned/unoccupied structures for the long term

). Sometimes, only urban properties deemed difficult to develop are considered as vacant land, while abandoned or brownfields parcels including industrial, commercial or residential sites/buildings are also designated as vacant land in some cases. Furthermore, open space with particular natural resource value such as park and farm sites are also included as the vacancy in some studies.

The National Vacant Properties Campaign (NVPC) defines vacant properties if one or both of the following characteristics was met: “The site poses a threat to public”, and/or “the owners or managers neglect the fundamental duties of property ownership (e.g., they fail to pay taxes or utility bills, default on mortgages, or carry liens against the property.)” [14] p. 1. Based on the literature, vacant land includes not only underperforming or empty properties but also neglected and abandoned residential, commercial and industrial buildings/properties that have been beyond repair over a year to threaten a public safety. The latter vacant properties would be a concern for planners, particularly in shrinking cities.

The depopulation could be occurred by different sorts of causes such as suburbanization, the demographic cliff, natural hazard, or inner-city decline and suburbanization, which eventually resulted in an increase of unoccupied vacant homes and structures. These abandoned structures would be a concern of shrinking cities with less capacity to reuse these abandoned properties than growing cities. Aesthetic quality and properties around these abandoned structures might decrease. Increased crime and arson would harm the whole community. The outmigration of neighbors could sabotage the capital of community. Government, community members, and planners had added great efforts to tackle the urban vacancy. Some cities, like Detroit, have attempted to bring big enterprise to the downtown as an anchor for urban regeneration. But this kind of effort cannot always be successful, especially in small shrinking cities with fewer resources. Rather, cities took the simple and temporary approaches such as demolition, refurbishment, or a conversion to community garden, while waiting the city would get sufficient capacity to regenerate the whole area. After then, policy and government-driven interventions were found. Chicago established Cook County Land Bank and attempted to redevelop and remodel vacant homes through Neighborhood Stabilization Program [15]. UK also collects vacant property data to identify and manage the vacant houses efficiently [16]. Japan and Korea enacted Vacant Housing Law in 2015 and 2018 respectively, which remediate annoyances of urban vacancy lawfully [17]. As a part of regeneration efforts, cities attempted to respond to vacant housing issues and the planning interventions have been evolved from temporary and community-based solutions to policies and laws.

2.3. Plan Evaluation

Development management is the deliberated and integrated government program designing to achieve broad public interest goals by controlling the type, quality, scale, rate, sequence or timing of development [18,19,20]. As low-density suburban developments were spread out around most cities during the postwar era, uncontrolled and wasteful consumption of land and resources by single-use development became a problem. Meanwhile, the needs of reasonable development management have also arisen across communities, regions, and states to address the issues directly and growth management programs were developed to achieve orderly urban growth, preservation of green space and natural resources, and efficient transportation systems [19].

In this sense, planning can also play an important role in guiding land use and development in areas having a high risk of vacancy issue. However, despite many policies and strategic plans that have been put in place for inner-city revitalization, conventional market-based redevelopment policies aggravate market dysfunction, chronic decay, and disinvestment due to the lack of understanding of each city’s situation [9,13]. Thus, it is critical to find different causes and effects of the vacancy in each city and suggest appropriate policies.

Previous literature is in rich to evaluate the contents of comprehensive plans. In particular, rational basis of plans, called factual basis, goals and objectives, and planning tools and strategies are the most frequently examined items of plan documents [21]. The items for evaluation under each category can be retrieved from previous studies and a city or community could get a ‘plan score card’ based on these evaluation items. Heim LaFrombois, Park and Yurcaba [11] examined the planning strategies for pro-growth, maintenance, and smart decline with 33 planning tools. Berke and Conroy [15] assessed 30 comprehensive plans’ policies and strategies to reveal whether they sufficiently support the key principles of sustainable development. By using their newly developed coding scheme, which scales from 0–2, they could readily score the level of existing policy achievements. Particularly, this evaluation coding protocol has been widely employed and applied in assessing various fields of local/regional plans. Godschalk et al. [22] expanded the previous three plan components approach into five by including inter-organizational coordination and implementation elements. Using this expanded method, several studies measured the degree and quality of local plans in diverse fields, such as ecosystem management, coastal zone land use planning capacity, and drought preparedness [23,24,25]. Kim et al. [17] adopted five plan components, including policies and implementation tools, in order to evaluate whether rapidly growing municipalities in US substantially incorporate the concepts of green infrastructure planning. Rather than assessing the quality of the plan itself, some studies attempted to examine the implementation effects of a plan. Laurian et al. [26,27] discerned how land development permitting processes followed the existing development policies of a plan in New Zealand by adopting a conformance-based method. Berke et al. [28] examined the networks of local plans toward hazards vulnerability and climate change by adopting a newly developed resilience scorecard and found that the contents of local plans were likely to be inconsistent and vulnerable areas to flood did not sufficiently create mitigation strategies/policies. As discussed above, previous plan assessments are imperfect because of self-selected criteria. However, they could guide local governments in ways that mediate facing challenges and quality of life by multiple jurisdictions [29,30].

3. Literature Gaps and Research Objective

Even though many studies on the vacant land were conducted over the last fifty years and explained the relationship between vacancy and urban shrinkage, existing research has the following limitations.

First, most studies have focused on physical and economic aspects such as depopulation and unemployment rate as the primary factors for a growing amount of vacant properties. However, the problem of population loss is not about size itself, but about who is leaving and who is staying. While some studies examine how socioeconomic status has influence on vacancy in a declining city, only a small number of existing studies attempt to explain the relationships between a mix of physical, economic, and social characteristics and vacant land. While most of the studies describe the demographic trends of a region, it is difficult to find any literature on assessing the statistical significance of those factors. Based on the literature, 18 different driving factors are identified as the principal causal mechanisms contributing to vacant urban land, not only physical but also socio-economic and environmental characteristics.

Second, some studies have also recognized the seriousness of vacancy issues and analyzed the spatial pattern of vacant land to suggest better solutions. However, since they only focus on historical vacancy pattern trends, it is questionable if the policies and strategies work in the future. Although there are three studies to predict future possible vacancy scenarios [3,4,31], they fail to explain how the prediction outputs can be applied in real urban planning systems. Thus, this research evaluates how well comprehensive plans have reflected the vacancy issue in vulnerable areas of both growing and shrinking cities.

Third, a local comprehensive plan has been employed from various prior studies as an effective measure to assess a community’s long-range visions and preparedness for future developments. Starting from early 1990s, many previous studies assessed diverse topics, including natural hazards [32,33,34,35], affordable housing [36], green infrastructure [37], land use pattern [38], new urbanism [39], sustainable development [21,40], smart growth [41], and urban sprawl [42]. These studies, however, have mostly adopted the content analysis method that was generally relying on Kasier et al.’s plan evaluation approach [43]. In addition, the fields of previous plan evaluation lacked on assessing issues related to shrinking cities and vacant lots. While evaluating the quality of plan can provide insightful lessons to local planners and decision-makers, it is more critical for us to understand whether planning mechanisms have been sufficiently and successfully implemented in practice. This study attempts to examine the plan implementation effect by employing a newly developed plan evaluation protocol.

4. Methods

4.1. Selection of Cities

For the first part of the research, the city of Fort Worth, TX and the city of Chicago, IL were selected as study areas to compare how well vacancy related policies have been created and adopted in vulnerable areas between a growing city and a shrinking city. As mentioned above, Fort Worth is one of the fastest growing cities, while the city of Chicago has suffered severe depopulation and economic crisis, losing over 920,000 people from its peak year.

The U.S. Census Bureau indicates that the population of the city increased by 206,512 persons (+37%) between 2000 and 2010 becoming the fastest growing large city with more than 250,000 population (see

Table 2. Top 10 Growing Cities with more than 250,000 Population from 2000 to 2010. Top 10 Shrinking Cities with more than 250,000 Population from 1980 to 2010.

City	State	2000	2010	2018	Pop. Change	Change (%)
				(Estimated)
Fort Worth	TX	534,694	748,481	895,008	213,787	40
Charlotte	NC	540,828	738,534	872,498	197,706	36.6
San Antonio	TX	1,144,646	1,332,883	1,532,233	188,237	16.4
New York	NY	8,008,278	8,175,133	8,398,748	166,855	2.1
Houston	TX	1,953,631	2,100,263	2,325,502	146,632	7.5
Austin	TX	656,562	806,423	964,254	149,861	22.8
Raleigh	NC	276,093	403,892	479,332	127,799	46.3
Phoenix	AZ	1,321,045	1,445,632	1,660,272	124,587	9.4
Las Vegas	NV	478,434	584,606	644,644	106,172	22.2
Los Angeles	CA	3,694,820	3,792,621	3,990,456	97801	2.6
City	State	1950	1960	2010	Pop. Change	Change (%)
Detroit	MI	1,849,568	1,670,144	713,777	−1,135,791	−61.4
Chicago	IL	3,620,962	3,550,404	2,695,598	−925,364	−25.6
Philadelphia	PA	2,071,605	2,002,512	1,688,210	−545,599	−26.3
St. Louis	MO	856,796	750,026	452,801	−537,539	−62.7
Cleveland	OH	914,808	876,050	573,822	−517,993	−56.6
Pittsburgh	PA	676,806	604,332	423,959	−371,102	−54.8
Baltimore	MD	949,708	939,024	786,741	−328,747	−34.6
Buffalo	NY	580,132	532,759	357,870	−318,822	−55
New Orleans	LA	570,445	627,525	557,927	−283,696	−45.2
Cincinnati	OH	503,998	502,550	385,460	−207,055	−41.1

). The rapid population growth is forecasted to continue considering the immigration and domestic migration enhanced by a strong economy. In contrast, Chicago will lose more than 1 million people between 1950 and 2020, which only two municipalities worldwide have experienced, London and Detroit [4,44]. In spite of Chicago’s depopulation rate, decline related issues in the city have been relatively overlooked compared to other shrinking cities such as Detroit, Cleveland, and Baltimore. Thus, Fort Worth and Chicago are selected as examples of growing and shrinking cities (See Table 2).

4.2. Variable Influence in Two Types of Cities

To evaluate the vacancy related plan quality, the variable influence output from our previous research was utilized [4]. Using 2000–2010 input data, two statistical results (PCM and Kappa) were calculated by dropping one variable for each city, Fort Worth and Chicago, and then, the differences in variable influences were compared between those two cities.

Different input factors that contribute to vacant land increase were selected due to the data capabilities of each city. While 18 rasterized variables were utilized for the City of Chicago, Fort Worth used 16 input factors, excluding mobile home rates, crime rates, and vehicle availability.

Table 3. Difference of Variable Influence between Fort Worth and Chicago.

Domain	Variable	City of Fort Worth			City of Chicago
		PCM	Kappa	Rank *	PCM	Kappa	Rank *
Accessibility	Proximity to Highways	53.1	0.48	10	45.5	0.43	18
	Proximity to Railroads	53.5	0.48	6	48.7	0.46	10
	No Vehicle available	-	-	-	45.8	0.43	17
Socioeconomic Status	Poverty Rate	54.7	0.49	2	49.0	0.46	7
	Household Income	52.6	0.47	12	50.1	0.47	2
	Educational Attainment	53.5	0.48	9	49.8	0.47	4
	Unemployment Rate	52.2	0.47	14	50.5	0.48	1
	Ethnicity	52.6	0.47	13	48.6	0.46	11
	Crime Rate	-	-	-	48.3	0.46	13
Housing	Home Ownership Rate	53.5	0.48	7	49.6	0.47	5
	Mobile Home Rate	-	-	-	46.0	0.43	16
	Housing Value	47.8	0.42	15	47.9	0.45	14
	Vacancy Rate	53.5	0.48	8	47.8	0.45	15
Physical/Demographic Status	Parcel Size	54.3	0.49	5	48.9	0.46	8
	Age of Buildings	54.5	0.49	3	48.6	0.46	12
	Population Change	52.7	0.47	11	49.3	0.47	6
Industrial Quotient	Secondary Industry Rate	55.1 **	0.5	1	48.9	0.46	9
	Service Industry Rate	54.4	0.49	4	49.9	0.47	3
Full Model		54.7	0.50		50.9	0.48

*: The larger number in rank indicates bigger influence. **: Producing higher PCM & Kappa Statistics than the full model, meaning this factor may not be a strong determinant to predict vacant land.

displays the variable influence (highest to lowest) by city and the difference in the influence between these two cities. In Chicago, transportation physical variables such as proximity to highway, vehicle accessibility and median year structure built are powerful determinants of vacancy, while personal wealth and socioeconomic variables such as housing value, unemployment rate, race, and household income have a stronger influence on the model than other factors in Fort Worth. This indicates that creating transportation and accessibility-related policies might be effective methods in dealing with vacancy issues in a shrinking city, and policies to reduce social and racial segregation can be an alternative in a growing city.

4.3. Comprehensive Plan Evaluation by Planning District

To demonstrate how well a comprehensive plan has considered the driving factors of vacancy and created appropriate policies, we begin to identify planning districts. Since most local plan policies are coordinated by planning districts such as residential neighborhoods, downtowns, and commercial corridors, the geographic districts are relevant units of analysis to examine each plan’s quality [28,45]. Using GIS software, the planning districts are intersected, and the variable data are recalculated to identify which districts are socially and physically vulnerable (high poverty rate, low income, and educational attainment, high rates of building deterioration, high risk of vacancy, etc.). Then, we select the most vulnerable districts and the wealthiest districts to evaluate how well the comprehensive plans support the vulnerable districts to reduce vacancy issues.

Since a comprehensive plan is a process and tool used to guide communities’ future land use decisions, seeking to balance development pressure with preservation for long-term economic health and quality of life, it includes all land in its regulatory jurisdiction and also consider all physical developments of the community [30]. Thus, we evaluate each community’s comprehensive plan to determine the extent to which local policies contribute to reducing vacancy and vulnerability by districts, following well-established plan content analysis procedures [46]. First, each vacancy related policy is classified by planning districts if the policy reduces/increases the vulnerability and obtains +1/−1 score. Next, we sum scores to create an index score by variables. Higher total scores indicate that the community creates more policies aimed at reducing vacancy, while zero scores indicate that there are no vacancy related policies by a variable within a district.

Table 4. An Example of Plan Policy Method, Fort Worth, TX.

Example 1.

A policy in the economic development section of the Fort Worth (TX) comprehensive plan states that the city should “Use appropriate incentives to promote development of vacant land and redevelopment or reuse of deteriorated properties within designated commercial districts” (Fort Worth 2017, 10-2). By revitalizing vacant properties, this policy aims to reduce vacancy related problems. Furthermore, this statement apparently indicates a spatially assigned indicator, designated commercial district. Thus, this policy received a score of +1 for the commercial district for the factor of vacancy.

shows an example of how plan policies are classified and scored. Since proper and effective planning policies for reinvestment and revitalization of central cities would contribute to slow down sprawl and solve the depopulation and vacancy issues, the outcomes of this study would provide a strong guidance by quantifying the quality of the planning process and the strength of its implementation.

5. Results

5.1. Vacancy Related Plan Evaluation

Based on the results of quantifying the effect of each factor through model performance in Section 4.2, we evaluate comprehensive plans to determine how well the primary factors contributing to vacancy are reflected existing plans in both growing and shrinking city. A local comprehensive plan is composed of two parts: (1) analysis of existing conditions and trends and (2) goals, objectives and policies. Since “existing conditions and trends” provides a foundation and basis for the formulation of “goals, objectives, and policies” by indicating the current status and problems of the local community, both “existing conditions” and “goals” sections should be reviewed.

This section consists of three processes: (1) regenerating socioeconomic status, and vacancy trends in current and future (2020) in each city by planning districts using a tool, Geospatial Modeling Environment (GME), (2) finding one(or two) of the most socially and physically vulnerable planning districts, and one(or two) of the wealthiest and healthiest communities, (3) evaluating comprehensive plans to determine how well their plans take into account current vacancy related problems by comparing wealthy-occupied and vulnerable-vacant communities of each city considering the variable influence outputs.

The results indicate that the cities place a greater emphasis on economic revitalization in vulnerable districts than in healthier communities in both growing and shrinking cities. Fort Worth has 123 policies/strategies which are associated with vacant properties. Among them, 63 policies cover South East, one of the most vulnerable districts in Fort Worth, that aim to revitalize the economy and reduce vacant properties. Also, 50 of the policies in South East closely correspond to neighborhood market conditions and socioeconomic statuses such as stabilization of property value and job markets which are stronger predictors of vacant land in the City of Fort Worth. Therefore, Fort Worth recognizes the vacancy issue in socially and physically vulnerable districts and provide diverse policies and strategies to revitalize these areas and reduce vacant properties.

In contrast, the City of Chicago does not have a city-level comprehensive plan. Rather, they have a comprehensive regional plan for the Chicago metropolitan area including 7 counties and 284 communities. Since the plan could not be evaluated at the neighborhood level, we reviewed the plan to determine how well it considers the vacancy issue at a city level. The variable influence test suggests that transportation system and physical condition are the most influential variables affecting vacancy transformation in Chicago while most personal wealth related variables have marginal influence predicting vacancy in the city. However, the results show that the city makes a greater effort to improve socioeconomic status than mobility and physical characteristics. Among 65 vacancy-related policies of the regional comprehensive plan, nineteen policies strived to improve the public transit system, highway system and physical condition of structures while thirty-nine policies targeted socioeconomic status, aiming to increase income and educational attainment and decrease the unemployment rate and poverty. Therefore, to overcome the chronic vacancy issue in Chicago, they would need to highlight policies to improve mobility and physical conditions of structures.

5.1.1. The City of Fort Worth

The Fort Worth 2017 comprehensive plan contains guidance for making decisions about growth and development relating to 22 functional sectors, including land use, housing, transportation, infrastructure, conservation, recreation and open spaces, and capital improvement. The comprehensive plan describes future development patterns and population projections for the city and protects natural and cultural resources for present and future generations. Among the 22 subsections of the plan, 12 different sections dealing with vacancy issues were reviewed: land use, housing, capital improvements, financial incentives, parks and community services, critical facilities (libraries, police services, fire, and fire and emergency services), economic development and transportation (See

Table 5. City of Fort Worth 2017 Comprehensive Plan Chapters & Vacancy-Related Topics.

Components	Vacancy-Related
I: Building Strong Neighborhoods
1.1. Land Use	O
1.2. Housing	O
1.3. Parks and Community Services	X
1.4. Libraries	O
1.5. Human Services	X
1.6. Neighborhood Capacity Building	O
II: Developing A Sound Economy
2.1. Economic Development	O
2.2. Transportation	X
2.3. Education	O
2.4. Historic Preservation	X
2.5. Urban Design	X
2.6. Arts and Culture	X
III: Providing A Safe Community
3.1. Police Services	O
3.2. Fire and Emergency Services	O
3.3. Environmental Quality	X
3.4. Public Health	X
3.5. Municipal Facilities	O
IV: Tools for Implementation
4.1. Capital Improvements	O
4.2. Development Regulation	X
4.3. Financial Incentives	O
4.4. Annexation Policy	X
4.5. Inter-governmental Cooperation	O

).

Since the City of Fort Worth has been divided into 16 districts for planning purposes, the current socio-economic and vacancy status of each district were regenerated based on the districts using a tool, GME. Considering the analytical outputs of physical, social, and economic circumstances of the neighborhoods, Far North (FN), one of the highest risks of vacancy and socially vulnerable district and South East (SE), one of the lowest risk of vacancy and wealthy district were selected among the 16 planning districts to evaluate how well the comprehensive plan reflects the vacancy issues in the vulnerable district. The poverty rate in the SE (31%) is about six times higher than FN (5%), the median household income ($28,374) is three times lower ($83,367), the unemployment rate (14%) is three times higher (5%), and the crime rate per 100,000 people (814) is twice as high (429). Consequently, these indicators show that South East district needs careful and specific planning policies to reduce vacancy rate, improving economic outcomes and developing safe communities (See Figure 1,

Table 6. 2010 Socioeconomic Status of Four Selected Planning District (Fort Worth).

District	2020 Vacancy	Long Term Vacancy (2014)	Race 1	Edu. 2	Unemp. 3	Income 4	Poverty	Ownership 5
Far North (FN)	30.4%	0.4%	8.8%	6.9%	5.2%	$83 K	4.8%	74.2%
South East (SE)	65.2%	6.9%	36.9%	42.8%	14.0%	$28 K	31.2%	52.0%

Race ¹: African American, Edu. ²: Less than a high-school graduate, Unemp.³: Unemployment rate. Income ⁴: Median household income, Ownership ⁵: Home Ownership.

, and

Table A1. 2020 Future Vacancy and 2010–2014 Long-term (24+ months) Vacancy by Planning District (Fort Worth).

District	2020 Predicted Composite Score				Long-Term (24+ months) Vacancy
	1	2	3	Total	2010	2011	2012	2013	2014
Arlington Heights	18.6%	17.3%	3.7%	39.7%	3.5%	4.7%	6.1%	6.2%	5.6%
Downtown	36.2%	17.5%	2.6%	56.3%	1.4%	1.6%	2.0%	1.8%	2.3%
Eastside	41.8%	7.4%	8.5%	57.7%	1.3%	2.2%	3.4%	3.9%	3.6%
Far North	30.4%	19.8%	6.0%	56.2%	0.2%	0.4%	0.5%	0.4%	0.4%
Far Northwest	60.4%	3.9%	8.3%	72.6%	0.1%	0.1%	0.2%	0.2%	0.2%
Far South	63.3%	5.5%	4.6%	73.4%	0.1%	0.3%	0.4%	0.3%	0.2%
Far Southwest	70.2%	0.4%	7.9%	78.5%	0.0%	0.0%	0.0%	0.1%	0.1%
Far West	36.3%	16.9%	5.8%	59.1%	0.3%	1.4%	2.2%	2.2%	1.8%
Northeast	35.1%	11.1%	6.1%	52.4%	2.8%	3.0%	3.4%	3.5%	3.5%
Northside	27.4%	17.9%	6.8%	52.0%	3.6%	4.8%	5.6%	5.8%	5.4%
South East	65.2%	2.4%	9.8%	77.4%	4.1%	5.4%	6.8%	7.4%	6.9%
Southside	25.4%	19.2%	5.8%	50.4%	4.6%	5.7%	6.9%	6.7%	6.2%
Sycamore	51.3%	4.0%	4.5%	59.9%	0.7%	1.2%	2.1%	2.2%	2.3%
TCU West Cliff	23.0%	7.5%	1.9%	32.4%	0.9%	1.1%	1.7%	1.9%	1.5%
Wedgwood	28.8%	4.8%	4.2%	37.7%	0.6%	0.8%	1.4%	1.3%	0.8%
Western Hills-Ridglea	22.1%	4.2%	3.3%	29.6%	3.6%	5.1%	6.4%	6.4%	6.5%
Fort Worth (City)	44.8%	8.4%	6.7%	60.0%	1.5%	2.4%	3.1%	3.2%	3.0%

and

Table A2. 2010 Socio-economic Status by Planning District (Fort Worth).

District	Race 1	Education 2	Unemploy.	Income 3	Vacancy	Value 4	Poverty	Ownership	Mobile Home	Crime 5
Arlington Heights	12.6%	17.6%	6.8%	$47,415	12.4%	$166,191	16.6%	49.5%	0.1%	1644
Downtown	24.4%	17.7%	5.3%	$51,196	16.7%	$236,800	21.0%	13.8%	1.1%	3774
Eastside	33.8%	18.0%	9.6%	$46,268	13.2%	$119,948	15.8%	44.6%	1.6%	4643
Far North	8.8%	6.9%	5.2%	$83,367	4.8%	$164,606	4.8%	74.2%	2.4%	3358
Far Northwest	7.8%	10.6%	8.1%	$71,811	8.7%	$144,348	7.1%	74.8%	1.7%	4065
Far South	26.9%	10.9%	5.5%	$65,559	9.0%	$125,163	9.6%	73.4%	3.9%	4482
Far Southwest	20.6%	6.7%	4.6%	$95,884	5.6%	$189,249	3.8%	85.8%	0.6%	1729
Far West	9.6%	14.4%	6.5%	$59,124	7.2%	$102,276	9.2%	60.9%	1.4%	3602
Northeast	9.1%	50.7%	9.9%	$33,836	10.9%	$73,534	25.5%	56.5%	0.5%	5913
Northside	3.2%	53.7%	9.4%	$199,857	14.2%	$72,133	27.1%	48.9%	3.8%	6036
South East	36.9%	42.8%	14.0%	$28,374	14.3%	$52,551	31.2%	52.0%	6.6%	6368
Southside	16.8%	44.6%	12.7%	$29,268	14.8%	$75,547	37.7%	43.9%	0.5%	5634
Sycamore	28.5%	31.3%	10.6%	$40,120	12.0%	$82,577	26.4%	53.1%	3.9%	5566
TCU West Cliff	3.4%	7.0%	5.9%	$60,563	9.7%	$282,905	14.5%	46.6%	0.6%	1644
Wedgwood	22.1%	9.6%	6.0%	$55,048	9.3%	$144,063	10.8%	49.3%	0.2%	3645
Western Hills-Ridglea	12.5%	18.1%	9.2%	$39,795	16.3%	$138,401	19.5%	34.0%	0.3%	3732
Fort Worth (City)	18.7%	21.9%	8.2%	$61,436	11.0%	$131,854	17.4%	53.2%	1.8%	4111

Race ¹: African American %, Education ²: Less than high-school graduate %, Income ³: Median household income, Value ⁴: Median house value, Crime ⁵: Crime/100,000 pop.

).

The variable influence outputs indicate marketing conditions and economic variables such as housing value, unemployment rate, ethnicity, and income have a greater influence on vacant land transition than most other factors. On the other hand, industry quotient (secondary and service industry), poverty and age of buildings did not seem to be strongly influential when predicting for vacant land in the City of Fort Worth. Thus, the basic policy direction on vacant land in the city should focus on socio-economic and industrial conditions such as improving economic opportunities and conditions and reducing racial segregation.

Table 7. The Number of Vacancy-related Policies/Strategies of Two Selected Districts (Fort Worth). (Sorted in order of greater to smaller variable influences).

Variable	Land Use			Housing			Economic Development			Capital Improvement			Financial Incentives			Critical Facilities			Transit			Total
	FN	SE	O	FN	SE	O	FN	FN	SE	O	SE	O	FN	SE	O	FN	SE	O	FN	SE	O	FN	SE	O
Housing value	1	1		1	5	3																2	9	5
Unemployment	2	1		1	3	2					1					1	1					4	14	5
Ethnicity					1	2					1				1							0	2	3
Income	2	1		1	3	2					1				2	1	1					4	12	7
Population change																						0	0	0
Highway								1	1	1									1	1	1	1	1	1
Education																						0	1	2
Vacancy rate		1	1			1					1											0	4	3
Ownership						1																0	0	1
Railroad	4	3	3	1	2	2		1	1										1	1		6	6	5
Parcel size																						0	0	0
Service industry																						0	0	0
Built year					1																	0	1	0
Poverty	2	1		1	3	2					1				2	1	1					4	13	7
Secondary industry																						0	0	0
Total	11	8	4	5	18	15	0	2	2	1	5	0	0	0	5	3	3	0	2	2	1	21	63	39

FN: Far North, SE: South East, O: Overall (entire city).

displays the number of vacancy-related policies by variables in their order of influence from high to low. It indicates that the comprehensive plan of the city provides 123 vacancy related policies/strategies, and among them, 63 (or 51%) policies were created for South East where is one of the most vulnerable districts in Fort Worth, and 41 of 63 policies were associated with economic growth or quality of life such as reducing the unemployment rate, poverty, and increasing income. Especially, in order to improve the local environment and revitalize the economy of socially and economically vulnerable districts, Fort Worth adopted diverse housing policies and development incentives programs to increase the supply of quality housing and expand homeownership opportunities. For example, through Neighborhood Empowerment Zones (NEZs) program and Community Development Block Grant (CDBG) funds, local development activities were planned for low to moderate income households such as affordable housing and infrastructure development within South East district (See Figure 2).

* Neighborhood Empowerment Zones (NEZs): An area to revitalize the central city through development incentives: promote (1) the development and rehabilitation of affordable housing within the zone; (2) an increase in economic development within the zone; and (3) an increase in the quality of social services, education, or public safety provided to residents of the zone. 20 NEZs have been designated by the City Council [47] p. 226.

** CDBG Eligible Area: Census tract in which fifty-one percent (51%) or more of the residents in that census tract have low to moderate incomes as defined by the United States Department of Housing and Urban Development ([47] p. 214).

5.1.2. The City of Chicago

GO TO 2040 is the long-range comprehensive regional plan for the Chicago metropolitan region that includes 7 counties and 284 communities by Chicago Metropolitan Agency for Planning (CMAP) which is the official regional planning organization for the northeastern Illinois counties. Based on the region’s existing challenges and opportunists, the comprehensive plan contains 12 functional sectors including land use, housing, parks, and open space, sustainable local food, capital improvements, governance, and transportation. Among those 12 high-priority sections, 7 chapters are reviewed which are associated with vacant properties: land use, housing, parks, and open space, sustainable local food, education, workforce development, and transportation (See

Table 8. City of Chicago 2040 Comprehensive Plan (Go To 2040).

Components	Vacancy-Related
I: Livable Communities
1.1. Achieve Greater Livability through Land Use and Housing	O
1.2. Manage and Conserve Water and Energy Resources	X
1.3. Expand and Improve Parks and Open Space	O
1.4. Promote Sustainable Local Food	O
II: Human Capital
2.1. Improve Education and Workforce Development	O
2.2. Support Economic Innovation	O
III: Efficient Governance
3.1. Reform State and Local Tax Policy	X
3.2. Improve Access to Information	X
3.3. Pursue Coordinate Investments	X
IV: Regional Mobility
4.1. Invest Strategically in Transportation	O
4.2. Increase Commitment to Public Transit	O
4.3. Create More Efficient Freight Network	X

). Since Chicago only provides a larger scale regional plan, they do not contain enough specific spatial indicators for the City of Chicago. Thus, although the city of Chicago has been divided into seventy-seven districts for planning purpose, we are only able to evaluate the comprehensive plan without considering specific districts of Chicago.

Figure 3 indicates that there is a higher risk of a vacancy in neighborhoods surrounding the downtown area and the industrial communities in the Southeast region. Especially, the 2020 scenarios predicted that 69% of Englewood and 41% of Washington Park might have a probability of future vacancy, while only 3% of Lake View and 4.7% of Lincoln Park were predicted to become vacant in 2020. Moreover, looking at the long-term (over 24 months) vacancy rate by districts, the average long-term vacancy rate between 2010 and 2014 in Englewood (9.2%) and Washington Park (7.1%) were higher than Lake View (1.3%) and Lincoln Park (1.5%). The socioeconomic status of each district also shows how Englewood and Washington Park are socially and physically vulnerable compared to Lake View and Lincoln Park. Over 98% of the population in Englewood and Washington Park were African American in 2010, while Lake View and Lincoln Park had less than 5%. Both income and housing value of those vulnerable districts are less than 30% of the wealthy neighborhoods. Furthermore, the poverty rate (43%) is about four times higher (11%), the unemployment rate (22%) is four times higher (5%), and the crime rate per 100,000 people (11,662) is twice as high (5151). Under the circumstances, Englewood and Washington Park need careful and specific planning policies for reducing vacancy rate, improving economic outcomes and providing a safe community (See

Table 9. 2010 Socioeconomic Status of Four Selected Planning District (Chicago).

District	2020 Vacancy	Long Term Vacancy (2014)	Race 1	Edu. 2	Unemp. 3	Income 4	Poverty	Ownership 5
Englewood	55.4%	8.4%	98.7%	29.4%	21.3%	$21 K	45.1%	31.8%
Washington Park	16.5%	5.7%	98.1%	28.3%	23.2%	$24 K	41.6%	21.6%
Lake View	2.0%	1.4%	3.6%	2.9%	4.7%	$80 K	10.9%	39.9%
Lincoln Park	1.8%	1.5%	4.7%	4.4%	4.5%	$94 K	12.6%	49.2%

Race ¹: African American, Edu. ²: Less than a high-school graduate, Unemp. ³: Unemployment rate, Income ⁴: Median household income, Ownership ⁵: Home Ownership.

and

Table A3. 2020 Future vacancy and 2010–2014 long-term (24+ months) Vacancy by Planning District (Chicago).

District	2020 Predicted Composite Score				Long-term (24+ Months) Vacancy
	1	2	3	Total	2010	2011	2012	2013	2014
Albany Park	0.0%	0.1%	0.0%	0.1%	1.8%	1.3%	1.4%	2.1%	2.6%
Archer Heights	3.7%	0.9%	0.0%	4.6%	0.6%	0.9%	1.4%	1.6%	1.7%
Armour Square	2.8%	6.3%	0.0%	9.1%	0.8%	0.9%	0.6%	0.6%	1.0%
Ashburn	4.0%	5.7%	0.0%	9.6%	0.6%	0.7%	1.1%	1.4%	1.2%
Auburn Gresham	7.2%	5.9%	0.0%	13.1%	2.5%	2.5%	3.2%	3.9%	4.1%
Austin	34.8%	13.3%	3.0%	51.0%	2.6%	2.3%	2.8%	3.2%	3.1%
Avalon Park	1.6%	1.3%	0.0%	2.9%	1.8%	1.8%	2.5%	2.8%	3.3%
Avondale	1.9%	1.5%	0.1%	3.5%	3.2%	2.1%	1.7%	2.3%	2.2%
Belmont Cragin	0.9%	1.7%	0.0%	2.6%	1.2%	1.4%	1.8%	2.0%	1.9%
Beverly	0.3%	1.7%	0.0%	2.0%	0.9%	0.7%	0.8%	1.2%	1.2%
Bridgeport	7.1%	3.2%	0.0%	10.3%	1.1%	1.2%	1.4%	1.5%	1.6%
Brighton Park	4.2%	1.1%	0.0%	5.3%	1.6%	1.5%	1.8%	2.0%	1.7%
Burnside	2.9%	4.4%	0.0%	7.2%	3.9%	4.4%	5.1%	4.9%	5.2%
Calumet Heights	4.4%	4.0%	0.0%	8.4%	2.1%	1.9%	2.5%	3.0%	2.9%
Chatham	9.1%	3.3%	0.0%	12.4%	3.2%	3.3%	4.8%	4.5%	4.8%
Chicago Lawn	4.3%	3.2%	0.0%	7.5%	2.9%	3.5%	4.3%	4.1%	4.3%
Clearing	2.1%	1.7%	0.0%	3.8%	0.8%	0.8%	1.1%	1.3%	1.1%
Douglas	9.0%	6.6%	6.1%	21.7%	1.3%	1.2%	1.2%	0.9%	1.1%
Dunning	3.0%	4.0%	0.0%	7.0%	1.0%	1.0%	0.9%	1.0%	0.8%
East Garfield Park	20.5%	16.1%	0.0%	36.6%	3.9%	3.5%	4.1%	4.4%	5.3%
East Side	5.8%	5.9%	0.0%	11.7%	2.8%	3.1%	3.6%	3.4%	3.1%
Edgewater	0.0%	0.9%	0.0%	0.9%	1.9%	1.1%	1.2%	1.8%	1.7%
Edison Park	0.0%	0.0%	0.0%	0.0%	0.6%	0.6%	0.8%	0.9%	1.3%
Englewood	55.4%	13.6%	0.0%	69.0%	8.6%	9.3%	9.8%	10.1%	8.4%
Forest Glen	0.0%	0.8%	0.0%	0.9%	0.5%	0.3%	0.4%	0.4%	0.4%
Fuller Park	8.4%	2.7%	1.9%	13.0%	10.4%	7.4%	5.0%	6.2%	8.0%
Gage Park	1.6%	2.3%	0.0%	3.9%	1.4%	1.4%	1.7%	2.0%	1.7%
Garfield Ridge	1.9%	8.5%	0.0%	10.4%	0.6%	0.6%	0.8%	0.9%	0.9%
Grand Boulevard	23.2%	25.1%	14.6%	62.9%	5.3%	6.2%	7.2%	5.5%	4.4%
Greater Grand Crossing	12.6%	3.9%	0.0%	16.5%	4.5%	5.0%	6.0%	6.1%	5.8%
Hegewisch	14.3%	27.1%	0.0%	41.4%	1.9%	2.2%	2.4%	2.7%	2.9%
Hermosa	0.0%	0.6%	0.0%	0.6%	2.1%	1.9%	2.4%	2.6%	2.1%
Humboldt Park	23.2%	13.2%	3.2%	39.6%	4.3%	3.8%	4.2%	4.8%	4.3%
Hyde Park	0.5%	0.9%	0.0%	1.4%	2.2%	2.4%	3.2%	2.5%	1.4%
Irving Park	0.0%	0.1%	0.0%	0.1%	2.1%	1.6%	1.6%	1.9%	1.9%
Jefferson Park	0.0%	0.0%	0.2%	0.2%	1.0%	1.0%	1.3%	1.5%	1.3%
Kenwood	6.7%	5.1%	0.7%	12.5%	3.3%	3.0%	3.6%	2.6%	1.9%
Lake View	2.0%	1.0%	0.0%	3.0%	1.4%	1.0%	1.2%	1.7%	1.4%
Lincoln Park	1.8%	2.9%	0.0%	4.7%	2.1%	1.6%	1.3%	1.2%	1.5%
Lincoln Square	0.2%	0.2%	0.0%	0.5%	1.3%	1.2%	1.1%	1.2%	1.3%
Logan Square	8.1%	5.4%	0.3%	13.8%	2.8%	2.7%	2.3%	2.3%	2.7%
Loop	3.0%	1.9%	0.0%	4.9%	1.4%	1.8%	3.4%	2.5%	1.1%
Lower West Side	6.6%	8.6%	0.0%	15.2%	2.8%	2.3%	2.4%	2.8%	3.4%
McKinley Park	0.7%	2.4%	0.0%	3.2%	1.8%	1.5%	1.2%	1.5%	2.0%
Montclare	0.4%	0.7%	0.2%	1.3%	0.6%	0.7%	0.9%	1.0%	0.9%
Morgan Park	3.3%	3.4%	0.0%	6.7%	1.9%	1.8%	2.1%	2.5%	2.7%
Mount Greenwood	0.3%	4.4%	0.0%	4.7%	0.4%	0.5%	0.8%	0.8%	1.0%
Near North Side	14.0%	14.7%	0.0%	28.7%	1.6%	1.8%	1.9%	1.6%	1.3%
Near South Side	10.8%	8.8%	0.0%	19.7%	0.6%	1.0%	2.1%	2.5%	1.7%
Near West Side	30.6%	38.7%	0.0%	69.3%	0.9%	0.9%	0.9%	1.0%	1.3%
New City	38.8%	36.1%	0.0%	74.9%	6.0%	4.7%	5.8%	6.7%	8.0%
North Center	1.3%	2.7%	0.0%	4.0%	3.2%	2.2%	2.1%	1.9%	1.7%
North Lawndale	36.0%	16.3%	0.0%	52.3%	3.9%	3.3%	4.0%	4.9%	5.4%
North Park	0.7%	0.9%	0.4%	2.0%	1.4%	1.3%	1.5%	1.6%	1.3%
Norwood Park	0.2%	0.9%	0.0%	1.0%	0.5%	0.5%	0.8%	0.8%	0.7%
Oakland	7.0%	7.8%	3.7%	18.5%	3.7%	4.2%	5.1%	3.3%	1.5%
O’Hare	1.9%	18.7%	0.0%	20.6%	0.8%	0.8%	1.2%	1.3%	1.0%
Portage Park	0.3%	0.2%	0.0%	0.5%	1.5%	1.5%	1.8%	2.1%	1.8%
Pullman	5.5%	7.8%	0.0%	13.3%	4.5%	3.6%	5.5%	5.4%	5.8%
Riverdale	16.2%	11.2%	0.0%	27.4%	28.3%	25.0%	23.0%	23.2%	25.3%
Rogers Park	0.3%	1.6%	0.0%	1.9%	3.2%	2.1%	1.8%	2.3%	2.2%
Roseland	13.6%	1.2%	0.0%	14.9%	4.1%	3.9%	4.4%	4.3%	5.4%
South Chicago	15.7%	7.3%	0.0%	23.0%	7.4%	8.2%	9.3%	9.0%	9.6%
South Deering	28.6%	45.2%	0.0%	73.8%	1.9%	2.0%	3.0%	3.5%	4.0%
South Lawndale	14.4%	15.2%	0.0%	29.7%	1.6%	1.2%	1.5%	2.0%	2.2%
South Shore	4.7%	4.0%	0.0%	8.7%	6.1%	7.5%	6.0%	5.1%	5.5%
Uptown	0.6%	2.7%	0.0%	3.3%	1.2%	1.1%	1.3%	1.8%	1.5%
Washington Heights	3.1%	3.8%	0.0%	6.9%	1.7%	1.8%	2.4%	2.4%	2.7%
Washington Park	16.5%	11.8%	13.1%	41.3%	6.4%	6.4%	8.6%	8.5%	5.7%
West Elsdon	0.0%	1.2%	0.0%	1.2%	0.8%	0.7%	0.8%	1.1%	1.4%
West Englewood	37.7%	22.0%	0.0%	59.7%	5.7%	5.8%	6.9%	7.8%	8.3%
West Garfield Park	21.4%	6.7%	2.1%	30.3%	4.6%	4.1%	4.0%	4.3%	4.6%
West Lawn	3.4%	3.0%	0.0%	6.4%	0.8%	0.9%	1.0%	1.0%	1.1%
West Pullman	15.5%	14.5%	0.0%	30.0%	4.7%	5.1%	5.6%	5.9%	6.6%
West Ridge	0.6%	1.9%	0.3%	2.8%	2.9%	1.9%	1.9%	1.9%	1.5%
West Town	5.1%	10.0%	1.5%	16.6%	2.3%	1.8%	1.9%	2.8%	2.2%
Woodlawn	15.1%	9.9%	3.4%	28.3%	5.1%	5.7%	7.3%	6.8%	6.4%
Chicago	5.5%	4.7%	4.2%	14.4%	2.5%	2.4%	2.7%	2.8%	2.7%

and

Table A4. 2010 Socio-economic Status by Planning District (Chicago).

District	Race 1	Education 2	Unemploy.	Income 3	Vacancy	Value 4	Poverty	Ownership	Mobile Home	Crime 5
Albany Park	3.8%	34.9%	9.0%	$46,865	8.7%	$328,123	19.6%	38.3%	0.2%	2287
Archer Heights	1.1%	36.4%	14.2%	$44,171	12.1%	$259,372	12.4%	64.6%	0.7%	4483
Armour Square	11.2%	37.5%	11.6%	$29,430	9.9%	$244,607	30.1%	37.1%	1.3%	4590
Ashburn	50.8%	18.3%	8.8%	$62,205	4.2%	$203,099	10.8%	88.7%	0.1%	3070
Auburn Gresham	98.6%	19.5%	24.2%	$35,003	14.4%	$162,760	27.6%	50.4%	0.0%	6932
Austin	86.6%	25.0%	21.0%	$34,275	15.6%	$227,455	27.7%	40.9%	0.1%	7070
Avalon Park	97%	13.3%	16.6%	$44,682	8.3%	$170,101	19.4%	70.0%	0.0%	7439
Avondale	3.4%	25.7%	9.3%	$46,982	10.5%	$343,544	15.7%	46.3%	0.2%	4071
Belmont Cragin	5.7%	37.0%	11.5%	$43,390	8.4%	$302,504	20.5%	50.5%	0.4%	3899
Beverly	33.4%	5.1%	7.8%	$87,173	5.6%	$322,293	4.2%	82.2%	0.2%	2468
Bridgeport	1.4%	26.1%	11.7%	$43,054	14.7%	$293,381	18.4%	49.6%	0.3%	2940
Brighton Park	1.0%	48.2%	11.2%	$39,726	13.4%	$222,120	23.8%	47.1%	0.3%	2935
Burnside	97.8%	18.6%	23.4%	$31,391	8.2%	$141,400	31.5%	55.9%	0.7%	4983
Calumet Heights	96.1%	11.2%	17.2%	$55,840	7.2%	$194,811	14.6%	75.9%	0.4%	6814
Chatham	97.7%	13.7%	19.0%	$35,059	15.2%	$179,384	24.5%	37.1%	0.1%	9105
Chicago Lawn	55.8%	31.6%	11.9%	$39,273	17.7%	$178,183	24.7%	47.3%	0.2%	7163
Clearing	1.5%	18.5%	9.6%	$54,622	6.7%	$241,552	6.4%	75.2%	0.1%	1858
Douglas	76.3%	16.9%	16.7%	$40,042	19.1%	$177,867	27.5%	20.7%	0.0%	5250
Dunning	1.2%	18.0%	8.6%	$61,757	4.8%	$298,414	7.7%	78.6%	0.3%	1782
East Garfield Park	92.2%	26.2%	16.4%	$25,010	25.8%	$237,982	41.6%	29.2%	0.0%	10,813
East Side	2.5%	35.5%	14.5%	$41,596	9.9%	$154,254	20.7%	71.4%	0.0%	2348
Edgewater	14.1%	9.1%	8.9%	$47,803	9.3%	$311,524	16.4%	39.4%	0.1%	2917
Edison Park	0.0%	8.4%	7.7%	$79,646	5.3%	$363,559	4.4%	81.9%	0.3%	679
Englewood	98.7%	29.4%	21.3%	$21,138	26.6%	$135,587	45.1%	31.8%	0.5%	11,289
Forest Glen	1.9%	6.3%	5.5%	$90,735	4.3%	$462,245	5.8%	86.3%	0.0%	1505
Fuller Park	94.8%	33.7%	40.0%	$16,204	30.4%	$120,961	46.6%	34.9%	4.6%	13,628
Gage Park	4.9%	54.1%	14.0%	$38,709	11.4%	$212,705	20.7%	57.7%	0.5%	3709
Garfield Ridge	8.9%	19.4%	8.1%	$61,664	7.9%	$244,987	9.1%	83.4%	0.3%	2353
Grand Boulevard	94.7%	19.4%	20.6%	$32,922	20.3%	$301,460	31.0%	28.6%	0.1%	6842
Greater Grand Crossing	98.0%	17.9%	18.9%	$30,033	19.3%	$162,509	31.4%	37.6%	0.3%	9059
Hegewisch	8.7%	17.9%	9.6%	$50,292	8.9%	$160,088	13.1%	76.0%	6.8%	2594
Hermosa	1.9%	41.9%	12.9%	$42,676	12.2%	$316,207	19.9%	46.3%	0.6%	3441
Humboldt Park	43.6%	36.8%	12.3%	$30,142	17.7%	$253,712	32.7%	34.3%	0.2%	6458
Hyde Park	33.9%	5.3%	6.9%	$46,918	16.1%	$293,951	21.2%	38.5%	0.0%	4676
Irving Park	3.8%	34.9%	9.0%	$46,865	8.7%	$328,123	19.6%	38.3%	0.2%	2287
Jefferson Park	1.1%	36.4%	14.2%	$44,171	12.1%	$259,372	12.4%	64.6%	0.7%	4483
Kenwood	11.2%	37.5%	11.6%	$29,430	9.9%	$244,607	30.1%	37.1%	1.3%	4590
Lake View	50.8%	18.3%	8.8%	$62,205	4.2%	$203,099	10.8%	88.7%	0.1%	3070
Lincoln Park	98.6%	19.5%	24.2%	$35,003	14.4%	$162,760	27.6%	50.4%	0.0%	6932
Lincoln Square	4.9%	12.5%	6.8%	$58,210	10.2%	$375,125	11.5%	41.2%	0.0%	2887
Logan Square	7.5%	18.5%	7.5%	$51,993	10.3%	$405,750	21.3%	38.0%	0.2%	5247
Loop	10.5%	3.4%	4.2%	$81,068	22.4%	$387,971	12.3%	50.1%	0.2%	22,568
Lower West Side	3.0%	44.3%	13.0%	$34,328	18.3%	$285,993	29.0%	30.3%	0.0%	3518
Mckinley Park	1.3%	31.8%	11.9%	$42,206	11.5%	$256,521	15.5%	58.5%	0.0%	3821
Montclare	4.7%	28.4%	10.8%	$48,463	8.0%	$302,504	11.6%	62.4%	0.6%	2968
Morgan Park	65.5%	10.9%	14.9%	$53,805	12.8%	$201,701	14.1%	75.4%	0.2%	4730
Mount Greenwood	5.4%	4.5%	6.9%	$82,743	4.8%	$253,442	2.5%	88.2%	0.0%	1335
Near North Side	13.2%	3.8%	5.6%	$73,348	17.6%	$459,946	15.1%	47.5%	0.1%	9173
Near South Side	35.5%	7.1%	5.7%	$76,205	13.6%	$388,066	11.8%	53.8%	0.1%	5454
Near West Side	35.7%	11.2%	10.7%	$61,064	12.2%	$352,069	27.5%	41.7%	0.1%	9788
New City	31.6%	42.4%	17.4%	$34,613	23.3%	$195,803	33.9%	42.5%	0.5%	5908
North Center	3.0%	5.4%	4.5%	$84,015	11.3%	$545,334	7.2%	52.9%	0.0%	3054
North Lawndale	92.5%	30.4%	18.5%	$26,165	26.6%	$209,021	42.4%	26.4%	0.4%	9406
North Park	2.7%	18.2%	7.5%	$53,889	6.7%	$374,113	11.4%	56.2%	0.8%	2854
Norwood Park	0.5%	13.6%	7.4%	$66,555	3.9%	$353,104	5.9%	77.4%	0.2%	1376
Oakland	93.9%	17.6%	26.6%	$21,506	10.2%	$366,031	34.1%	22.5%	0.0%	5776
O’Hare	1.1%	11.4%	4.9%	$50,462	9.1%	$225,346	9.7%	49.3%	0.1%	4423
Portage Park	2.2%	18.7%	10.6%	$52,277	9.5%	$324,694	14.6%	57.1%	0.2%	2575
Pullman	84.5%	15.6%	21.0%	$37,144	12.2%	$138,865	23.9%	48.8%	0.0%	5684
Riverdale	97.7%	24.6%	26.4%	$13,795	39.9%	$97,709	60%	15.7%	0.0%	6709
Rogers Park	30.4%	18.4%	7.3%	$41,374	15.8%	$254,681	26.1%	31.0%	0.1%	3673
Roseland	98.0%	17.4%	17.8%	$40,847	12.9%	$148,513	23.4%	59.6%	0.2%	7915
South Chicago	73.9%	28.2%	17.7%	$32,057	21.5%	$149,574	31.0%	41.2%	0.0%	7720
South Deering	59.7%	21.9%	11.8%	$38,482	11.2%	$120,362	27.0%	68.2%	0.0%	6280
South Lawndale	14.7%	58.7%	11.5%	$34,014	22.3%	$223,179	29.5%	37.6%	0.0%	3117
South Shore	96.9%	14.9%	17.7%	$28,783	23.3%	$205,114	31.8%	23.1%	0.1%	8863
Uptown	20.2%	13.9%	7.9%	$39,028	9.0%	$304,175	26.9%	29.6%	0.0%	3673
Washington Heights	96.9%	15.6%	18.3%	$43,559	9.9%	$155,628	19.3%	69.5%	0.2%	5813
Washington Park	98.1%	28.3%	23.2%	$24,001	30.7%	$176,320	41.6%	21.6%	0.5%	12,035
West Elsdon	2.4%	39.6%	13.5%	$50,348	7.7%	$232,108	11.8%	77.0%	0.1%	3122
West Englewood	96.3%	30.3%	34.7%	$27,412	24.3%	$117,392	41.4%	46.6%	0.1%	10,148
West Garfield Park	97.7%	26.2%	25.2%	$24,676	26.5%	$229,365	39.9%	27.5%	0.1%	9051
West Lawn	3.4%	33.4%	7.8%	$47,413	6.3%	$218,347	18.6%	77.8%	0.4%	3710
West Pullman	94.8%	22.6%	17.0%	$38,399	16.3%	$134,032	25.8%	64.5%	0.0%	6745
West Ridge	10.6%	19.6%	7.9%	$49,447	10.8%	$285,661	17.5%	52.9%	0.2%	2638
West Town	9.8%	13.4%	6.0%	$63,470	12.2%	$422,685	17.6%	40.4%	0.2%	7019
Woodlawn	89.0%	17.9%	17.3%	$28,475	27.6%	$228,166	28.8%	27.5%	0.0%	8797
Chicago	34.3%	20.8%	11.2%	$48,648	13.7%	$292,604	21.0%	48.1%	0.3%	5314

Race ¹: African American %, Education ²: Less than high-school graduate %, Income ³: Median household income, Value ⁴: Median house value, Crime ⁵: Crime/100,000 pop.

).

As mentioned above, however, since the regional plan of the Chicago metropolitan area does not provide specific policies for each district of Chicago city, it was not able to evaluate the comprehensive plan at the neighborhood level. Therefore, a broad evaluation of the entire city was conducted without considering spatial indicators.

Table 10. The Number of Vacancy-related Policies/Strategies of Chicago. (Sorted in order of greater to smaller variable influences).

Variable	Livable Communities	Sustainable Food	Workforce Development	Economic Innovation	Regional Mobility	Total
Highway	1				2	3
Vehicle Accessibility
Mobile homes
Vacancy rate		3				3
Housing value
Crime
Built year
Ethnicity	3					3
Railroad	3				13	16
Secondary industry
Parcel size
Poverty	4	1	9			14
Population change
Ownership
Education
Service industry				4		4
Income		1	9			10
Unemployment		1	9	2		12
Total	11	6	27	6	15	65

displays the number of policies which are associated with vacancy by plan category.

The variable influence test in Section 5.1 indicates that mobility and public transportation, housing condition, and crime seemed to have a stronger influence on increasing/decreasing vacant land, while some economic variables such as unemployment rate and income are influential, but only marginally when predicting for vacant land of Chicago. Thus, the basic policy direction on the vacant land of the city should be focused on improving transportation networks and promoting the rehabilitation of older housing stock to increase housing values and reduce crimes for Chicago.

Due to the recent economic downturn, metropolitan Chicago faces fiscal pressures, damaging quality of life and created various policies and strategies to revitalize the economy. The result of plan evaluation indicates that workforce development is recognized as one of the most important factors to revitalize their economy. Among 65 vacancy-related policies, 27 policies were obtained from “Improve education and workforce development” section which addresses the high-quality labor force and reducing differences between racial groups in terms of income, educational attainment and many other measures. Furthermore, 19 policies are suggested to improve the public transit system and highway systems focusing investments on maintenance and modernization.

6. Discussion and Conclusions

This research seeks to use a newly developed plan evaluation tool by predicting future outcomes of vacancy. Based on quantifying the effect of each factor on model performance in the previous study, each city’s comprehensive plan was evaluated to determine how well the primary factors of urban vacancy contributing to vacancy are reflected in policies in vulnerable districts compared to wealthy districts in shrinking and growing cities.

To summarize findings from analyses, this research reveals some interesting trends. First, while socioeconomic status related variables such as ethnicity, income and unemployment rate are stronger predictors of vacancy in Fort Worth, transportation and physical status related variables including proximity to highway and vehicle accessibility show a stronger influence on increasing vacant land in Chicago. Second, both cities have attempted to understand the causes and impacts of vacancy issues and suggested diverse planning policies. The plan evaluation outcomes indicate that Fort Worth has diagnosed the vacancy issue and its causes in socially vulnerable planning districts and established various vacancy related planning policies. Although Chicago might have a thorough grasp of the problem, the city doesn’t seem to have transportation and/or physical status related planning policies at planning district level. Thus, Chicago might need more specific and cause-based planning policies to revitalize vulnerable districts.

Overall, this study strived to quantify the influence of each driving factors and provide initial solutions that can be utilized in future projects. This study has not only supported methodological frameworks to predict future vacancy pattern and quantify the influence of each factor but has also explored theoretical and practical connections between planning and policy implementation.

Although this study provides a greater opportunity to create policies considering future spatial pattern trends, some limitations remain that should be furthered in the future study. First, since this study only dealt with two cities, Fort Worth and Chicago, the relatively small sample size may not be able to generalize conclusions with statistical power to all municipalities. Therefore, the study area needs to be extended to other communities facing rapid growth in population/size and/or experiencing serious deindustrialization and depopulation.

Second, in terms of evaluating vacancy-related plan quality by districts, while Fort Worth provides a city-level comprehensive plan, Chicago has a regional comprehensive plan for the Chicago metropolitan region that includes 7 counties. Since the regional plan does not provide specific policies or strategies by planning district in the city of Chicago, it is difficult to determine how well the existing policies consider the socially and physically vulnerable neighborhoods.

Lastly, the comprehensive plan is a tool used to guide overall future land use decisions, evaluating only the comprehensive plan may not be comprehensive enough to understand a city’s vacancy-related policies. If cities have small area programs or plans regarding depopulation or vacant properties such as central area revitalization plans, parks, and open space plans and transportation plans, it may useful to include these in future studies.

This is only a starting point for understanding the overall vacant land transformation. Further research is needed to extend study areas, define key terminologies, collect better data and provide more applicable policy implications.