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Vacant land is a ubiquitous urban phenomenon. The existence of vacant land in a neighborhood can either lower or heighten nearby housing values, depending on its relative development potential. However, this condition has rarely been examined longitudinally, nor has it been examined thoroughly across different socioeconomic conditions. This research examines the impact of vacant lots on housing premiums using 2006–2015 single-family home sale transactions in the City of Minneapolis, Minnesota. The study area was divided into low-, middle-, and high-income levels. The results show that vacant lands have negative impacts on nearby single-family houses and these impacts differ by income level per neighborhood. The study sheds light on how planners and researchers should conceive vacant lands differently in various surroundings and conditions.

Populating and depopulating cities have some degree of underutilised land. The duration of vacancy, or length of time a property remains unused, more strongly influences urban decline than the amount of vacant land. Assessment of the duration of vacancy is seldom conducted, due to a lack of linking longitudinal data. This research creates and applies a Python script to track the duration of vacancy in Minneapolis, MN, U.S.A, to create a tool that can be utilised by cities with vacant land inventories. The tool can be used globally to prioritise treatment areas for urban regeneration plans.

Vacant and abandoned land can be public eyesores that can potentially result in neighborhood distress in the long term. In some cases, the contextual conditions of a neighborhood have been shown to have more of a negative effect on communities than the vacant property itself. Maximum opportunities to actually reuse vacant and abandoned land is known to primarily exist in cases where the surrounding area has locational benefits or when local economic conditions are hopeful. This study examines and compares neighborhood socioeconomic characteristics around vacant lots in Minneapolis, Minnesota, USA, to identify spatial heterogeneity within vacancy types and neighborhood characteristics. Specifically, we examine 1) if the socioeconomic characteristics of a neighborhood can predict existing vacant lots and 2) what neighborhood characteristics are associated with certain vacant lot types. Three logistic regressions were tested with different buffers around each vacant lot, and a total of eighteen regressions were performed to capture the effects on six vacancy types. Results suggest that there are various types of vacancies interacting differently at the neighborhood scale, and that a large-scale neighborhood context matters when predicting vacancy types. The results also indicate three salient points. First, minority populations are a strong predictor of residential and commercial vacancies. Second, high-income areas tend to predict vacancies with potential investment opportunities or vacancies as a part of an existing park or recreational system. Third, vacant properties designated for institutional land uses tend to be found in lower-income areas, yet, not necessarily in areas with high minority populations. Managing and repurposing vacant and abandoned land should be handled more progressively with a better understanding of the socioeconomic characteristics of neighborhoods. Further, examining vacancy types by community can be a way to diagnose potential neighborhood risks associated with vacant and abandoned land.

This study develops a methodology to distinguish vacant land types and introduces a classification scheme using a citywide vacancy inventory. Using Minneapolis, MN as a study area, three land characteristics associated with vacant properties - parcel size, ownership, and land use - are examined. Kaplan-Meier survival rates are then estimated to evaluate and compare the durations of vacancy between 2005 and 2015. The results indicate that a vacant property, in general, has the lowest probability to remain vacant within its first two years after becoming vacant. Smaller-sized parcels tend to result in a longer-term vacancy; while publicly owned, industrial, institutional, and/or recreational vacancies show similar tendencies. From this analysis, this study then develops a six-category classification scheme that can be used as (1) a novel tool to inventory vacant urban lands, (2) a diagnostic tool to identify repurposing opportunities, and (3) reliable means of comparing vacant properties across localities.

Vacant urban areas (VUAs) can consist of both vacant land and abandoned structures. In this article, the authors summarize a recent survey on VUA, examine current conditions and causes of VUA, and explore the possible interconnections among these conditions and causes. The research examines employment, fiscal position, elasticity, population alteration, and regional location as primary variables. We find that VUAs are not interchangeable indicators of urban decay. Vacant land is most often associated with cities that have expanded their political boundaries while structural abandonment is more related to a city's population loss. Improvement of the local economy may not necessarily help reduce vacant land while structural abandonment is more sensitive to a city's economic status. Regional planning for VUAs, the strategic location of new industries and jobs, and new population/density regulatory approaches could be the next phase in addressing VUA changes.

Housing vacancies have become a major issue in depopulating, or shrinking, cities. All urban areas, however, are subject to some degree of vacant housing. A small percentage is necessary to allow mobility and sufficient space for growth, and is an indicator of healthy urbanization. Conversely, widespread housing vacancies may indicate structural crisis due to property abandonment. Land area and population changes, shifts in employment, demographic trends, development intensity, and economic conditions are primary drivers of housing vacancies. The degree to which these interrelated factors contribute can fluctuate by city. This paper explores relationships between factors contributing to housing vacancies over time to identify changes in underlying factors. The research examines U.S. cities of over 100,000 population over the period of 1960–2010, conducting multivariate regression analyses in 10-year periods and performing longitudinal panel analyses. The regressions examine changes in urban housing vacancy factors over time while the panel models assess which factors have remained consistent. The panel model results indicate that population change, percent nonwhite populations, unemployment and density are consistent, significant predictors of housing vacancies, The incremental regression models suggest that unemployment and regional location have also been strong indicators of housing vacancies. These results, while somewhat exploratory, provide insight into long-term data that cities should track over time to determine the optimal policy approaches to offset housing vacancies.

Disaster science is increasingly incorporating interdisciplinary methods and participatory research techniques. Yet, traditional higher education programs remain focused on lecture. More examples of educational efforts that meet the needs of future researchers and practitioners to foster collaboration across disciplines and with communities are needed. This paper describes one such effort that included three projects co-designed and co-led by university students, faculty, and community residents to address flooding challenges in socially vulnerable neighborhoods. This paper provides an overview of the educational programs, the three projects, and the feedback from graduate and undergraduate students who helped initiate these efforts, and discusses the benefits and challenges for similar interdisciplinary and participatory educational programs. Benefits for students include increased interdisciplinary dialogue, improved science communication, increased research participation, real-world research experience, and awareness of resident perspectives and knowledge. Challenges include a lack of cultural competency among students, time needed to earn resident trust, and mismatched community, academic, and student schedules.

The Dallas-Fort Worth (DFW) metropolitan area is one of the fastest growing areas in the U.S. As the urbanization process continues in DFW, existing greenfields are being developed and more developments appear near floodplains. This research examines the relationships between existing vacant land and the urbanization process by analyzing the land cover change between 2011 and 2016 in and around current floodplains in the DFW metro area. The major focus lies in three questions: 1) are flood-prone areas in DFW more likely to experience new development? 2) does existing vacant land in flood-prone areas bring new development activities? and 3) is the urbanization process associated with neighborhood change? Three logistic regression models were constructed to examine if existing vacant land can predict new development activities – with subgroups of different neighborhood socioeconomic status and by the level of flood hazard exposure. The results suggest that, in the DFW area, floodable areas are experiencing more development, and existing vacancies are a trigger only when vacancies are not clustered and when flood exposure is low. A heterogeneous pattern across different neighborhood profiles was found as areas with high flood exposure are likely to experience more large-scale development activities only for the low-income groups. This study suggests city planners pay attention to citywide vacant properties as they could either predict or detour potential developments. At the same time, areas with a close proximity to floodplains require more attention for the neighborhood socioeconomic status than existing vacant land uses.

The regeneration of vacant properties due to increased investments in declining neighborhoods does not always have positive outcomes. Vacant urban land can be, on one hand, an opportunity for neighborhood revitalization. On the other hand, regenerated vacant land can lead to neighborhood change in the form of gentrification, with increases in upper-class populations into mostly non-wealthy communities. The relationship between vacant land, its regeneration, and gentrification has been quite limited in the current research, mainly relying on an economic standpoint. Using Minneapolis, Minnesota as a case area, this research questions what types of vacant lands promote gentrification more than others. We analyze if 1) clustered vacant properties in Minneapolis are associated with the neighborhood gentrification process and 2) if certain types of vacant properties attract new investments and catalyze gentrification in Minneapolis. We examine such relationships using spatial autoregressive and logistic regression models. We also identify different vacancy types using proven classification schemes and measure significantly clustered vacancies using Getis-Ord Gi* statistics. Results suggest that clustered residential and commercial vacancies are positively associated with neighborhood gentrification while vacancies typified by institutional land uses are negatively associated with gentrification. Clustered, small-sized, industrial, and recreational vacancies show as insignificant factors contributing to gentrification. This study recommends that moderately-sized privately-owned properties should be targeted for the adoption of policies to preserve neighborhood affordability. In the case of publicly-owned vacancies highly threatened by gentrification, non-developmental pursuits should be primarily sought, such as re-greening and temporary usages.

Vacant land is a significant issue in virtually every country across the globe. This study presents a current inventory of vacant land and structural abandonment in the urban United States. Using survey data, it analyses vacant land trends by region and city type. Nationally, an average 16.7% of large US cities’ land area is considered vacant, with approximately 4% of city addresses unoccupied. The ratio of vacant land to city size has increased by 1.3 percentage points since 1998 but decreased by 3 percentage points since 1963. Regional variations exist in both the amount and kind of vacant land, suggesting that any ameliorative actions should be designed to fit specific conditions. Cities also reported that most vacant parcels are small, odd shaped, and disconnected, making them difficult to regenerate. Disinvestment, suburbanization and annexation are the primary causes of increases in vacant land supply while growing local economies, population in-migration, and city policies tend to help reduce the amount of vacant land.

Despite global projections of increasingly concentrated urban population growth, many cities still suffer from severe depopulation (or shrinkage), which results in increased vacant land/structural abandonment. As a consequence, shrinking urban areas are now seeking ways to more intelligently inventory and manage declining neighborhoods. Smart Shrinkage, a means of planning for fewer people and less development, has become a popular approach to managing depopulation. This research explores current approaches to managing vacant urban land through case evaluations approach, using findings to inform an applied Smart Shrinkage strategy for repurposing vacant lots. Land use prediction modeling is integrated into the process using Dayton, Ohio, USA, as an application site. A GIS-based development suitability model was used to identify pockets of future nodal development, and the land transformation model (LTM) was used to predict areas of future decline. Typologies of vacant/abandoned lots were then developed based on spatial characteristics of each parcel. The result of the process is a framework for executing Smarter Shrinkage—a community-scaled approach integrating land use prediction modeling into the process for managing vacant lots. Findings suggest that forecasts from the LTM require policy mechanisms to be put into place that will allow land to be transformed for nonresidential uses that are consistent with where demand exists. Smarter Shrinkage approaches should emphasize the implementation of newly proposed development only within nodes of high development potential and should utilize temporary or green infrastructure-based functions in areas predicted to become vacant or with low development potential.

Uncertainty about the impacts of sea level rise make the ability to forecast future spatial conditions a necessary planning/design tool. Geodesign integrates multiple fields of science with change/impact models and planning/design strategies. Proactive planning analyses such as newly developed scorecards allow for plan evaluation; design strategies can now be quantitatively assessed using landscape performance calculators. Neither have been explored as Geodesign tools. A Geodesign process was developed using the resilience scorecard to assess flood vulnerability using projections for the 100 year floodplain with sea level rise by 2100. Projections were used as a guide to develop a resilient master plan for League City, TX, USA. Future impacts of the plan are projected using landscape performance measures.