Urban Vacant Land Research Articles

Spatiotemporal changes of urban vacant land and its distribution patterns in shrinking cities on the globe

Urban vacant land (UVL) has been an important issue in the urbanization process, especially for shrinking cities. Identifying UVL and analyzing its spatiotemporal characteristics are the foundation for coping with this issue. This study identified UVL in 497 shrinking cities on the globe (10 % of shrinking cities in total) in 2016 and 2021 using manual labeling and deep learning to reflect the distribution patterns of UVL and its spatiotemporal changes. The results reveal that a global expansion of UVL from 2016 to 2021 in 497 shrinking cities, with diverse distribution patterns and varying changes across different regions. As for socioeconomic factors, UVL is related to population shrinkage, and the UVL ratio presents a phased change with the increase of the urbanization rate, revealing an inverted U-shaped relationship between the UVL ratio and the urbanization rate. The distribution patterns of UVL also vary globally in different urbanization phases. This study can provide theoretical and practical insights for improving urban planning and promoting sustainable urbanization.

Research on Green Infrastructure-Oriented Urban Vacant Land Transformation from the Perspective of One Health

Research on Green Infrastructure-Oriented Urban Vacant Land Transformation from the Perspective of One Health

Evaluating the feasibility of constructing shopping centers on urban vacant land through a spatial multi-criteria decision-making model

Shopping centers are among the major economic and commercial places in cities in terms of social function, urban sustainability, environment, etc. Therefore, it is crucial to determine suitable locations for building new shopping centers. In this regard, urban vacant lands can be considered as high-potential locations to transform the urban landscape and enhance socio-economic development. The main purpose of this study is to assess the potential of urban vacant lands based on a spatial multi-criteria decision-making (SMCDM) system for building shopping centers in 22 districts of Tehran. In this study, first, 16 effective spatial criteria for locating the new shopping centers were identified using expert opinions and a literature review. The best-worst method (BWM) and the Min/Max method were used to calculate the weight and standardized values of each criterion. Then, the ordered weighted averaging (OWA) method was used to prepare a potential map of urban vacant lands for the construction of a shopping center under different decision-making scenarios, including very optimistic, optimistic, intermediate, pessimistic, and very pessimistic. Finally, the spatial distribution of potential locations in the 22 districts of Tehran was investigated. The results showed that among the different criteria, the distance from the highway networks and distance from public transportation stations had the most weight, whereas the distance from fault and distance from stream networks had the least weight. The number of vacant lands with a very high potential for building a shopping center in Tehran based on very pessimistic, pessimistic, intermediate, optimistic and very optimistic scenarios was obtained at 29, 95, 105, 122, and 224, respectively. An increase in the degree of optimism in the attitude of decision-makers or investors increased the number of available options in the very high potential category. Under all scenarios, all vacant lands in 10 of Tehran’s 22 districts with very high potential for building shopping centers. The results of the proposed model in this study can be useful and practical for a wide range of planners, decision-makers, and investors with different mental attitudes and risk tolerance. Close attention to these results can contribute to achieving sustainable urban development.

Evaluation of the Potential for Renewing Urban Vacant Land into Green Infrastructure

Evaluation of the Potential for Renewing Urban Vacant Land into Green Infrastructure

Large-Scale Spatial–Temporal Identification of Urban Vacant Land and Informal Green Spaces Using Semantic Segmentation

The large-scale identification of urban vacant land (UVL) and informal green spaces (IGSs) using conventional identification methods is challenged by the high cost of time and resources as well as inconsistent outcomes. Moreover, the spatial–temporal changes of UVL and IGSs have received limited academic attention. We introduce a methodological framework for the large-scale automatic identification of UVL and IGSs in Hangzhou, China, based on semantic segmentation. We construct and release a large-scale dataset for UVL identification, containing five different UVL categories, and one of them is IGS, with 3096 patches for training and 128 patches for evaluation. We then train five different semantic segmentation networks using the dataset and utilise Segformer to predict UVL and IGSs within the whole urban area of Hangzhou. The presented segmentation model has a hierarchically structured Transformer encoder and a multilayer perceptron decoder, which incorporates local and global information to obtain effective feature representations. Extensive experiments have been conducted to evaluate the segmentation performance of the applied Segformer. Experimental results show the good identification performance of Segformer for UVL and IGSs. Results also verify that the proposed identification framework can be effectively used to analyse the spatial–temporal changes of UVL and IGSs in Hangzhou.

Dynamic monitoring of urban renewal based on multi-source remote sensing and POI data: A case study of Shenzhen from 2012 to 2020

Accurate information on the spatiotemporal distribution of urban renewal (UR) is important for sustainable urban development. Due to its complexity, existing studies could not completely describe the land cover types after demolition, and lacked the effective conversion rules to monitor the whole process of UR demolition and reconstruction which made it impossible to obtain high-precision UR extent, demolition time, and reconstruction time. This study proposed an UR monitoring framework by combining Point of Interest, nighttime light RS data, time-series RS data from Google Earth high-resolution and Landsat imageries. The urban vacant land was introduced to supplement the land cover classification system for UR monitoring and extracted by DeepLabv3 semantic segmentation model. The new conversion rules were then generated to track the historical changes in urban land types, and the multi-temporal classification model was applied to extract spatial and temporal characteristics of UR process. Results showed a total of 3,525.55 hm2 UR region were identified in Shenzhen during 2012–2020, and the largest demolition and reconstruction areas were both observed in 2019. The F1 and F2 scores of extracted UR extent, UR demolition time, and UR reconstruction time were larger than 0.72, 0.63 and 0.66, respectively, indicating high overall accuracies. Our proposed framework is important for the UR dynamic monitoring and can provide scientific basis for future urban construction.

Mapping urban land type with multi-source geospatial big data: a case study of Shenzhen, China

ABSTRACT Land types visually reflect the comprehensive attributes of land resources, allowing the monitoring of land development dynamics and evaluation of the land use situation. However, existing land type classification systems in urban areas lacked the integrated consideration of human characteristics and natural landscapes. Thus, this study integrated multi-source geospatial data including Weibo check-in, taxi-tracking, building-surveys, and remote sensing images to acquire anthropogenic features including building characteristics and human activities, and natural landscape features including water, vegetation, and urban vacant land. Three-level urban land type classification system was then constructed with two primary categories, six secondary categories, and 17 tertiary categories to reveal integrated characteristics of urban land resources. Based on the extracted urban areas of Shenzhen, urban land types in 2014 were mapped at street block to reveal the distribution and utilization efficiency of land resources in a visual and detailed format, thus guiding land resources optimization.

Assessing the Urban Vacant Land Potential for Infill Housing: A Case Study in Oklahoma City, USA

Vacant land in residual urban areas is a crucial resource to tackle the current climate and housing crises. In this study, we present the development of a geodatabase to determine the occurrence of vacant land in the urban core of Oklahoma City, USA (OKC), and assess its potential for infill housing. As a starting point, we define urban vacant land through a literature review. We present a description of the case study’s social and urbanistic context by highlighting its relevance to this study. We explain the methodology for the development of the geodatabase to quantify residual urban land in OKC’s urban core. We examine the spatial distribution and recurring characteristics of vacant parcels using QGIS, Python scripting for Rhinoceros 3D, and aerial imagery. We find that small parcels have higher vacancy rates than average-sized parcels and there is a correlation between higher vacancy rates and proximity to downtown and brownfields. Finally, we discuss the implications of the findings by assessing the urban vacant land potential for residential development and its contribution to OKC’s housing provision. Under all the proposed scenarios, the considered developable vacant land in the urban core could entirely fulfill the need for new housing units for the entire city.

Assessment of Urban Wastelands using GIS and IoT as Tools for Spatial Data Analysis

Large urban development around cities often results in vacant, abandoned or unproductive land parcels, sometimes called ‘wastelands’. There are various types of urban vacant land identified as post-industrial, derelict, land without any vegetation and left unattended, natural, and transportation-related vacant lands. The traditional way of collecting the data to study and manage such massive wastelands is hugely time consuming. Geographical Information Systems (GIS) and Remote sensing applications can extract periodic spatial changes and make it easier to collect and generate base maps, assess the number of wastelands in a given city, and remotely assess the extent of the area of wastelands/ vacant/ degraded lands. GIS also helps as a valuable tool to identify the neighboring land uses, lakes, green cover, and road networks, which could be considered as base work for any study to progress further with accurate information. Newer technologies like big data and cloud-assisted technology are employed in IoT applications for these wastelands to formulate an intelligent environment. Factors such as workforce, time, labor, transportation, money, and all other logistics can thus be strategized better with the combination of GIS and IoT applications; these are integral to wasteland monitoring and management practices for urban regions. This review paper aims to demonstrate how GIS, remote sensing, and IoT facilitate us to carry out monitoring, analyze, extrapolate, process, store, and integrate the spatial data for urban wastelands; and becomes a basis for planning and decision-making for on-site and management plans.

Reclaiming urban vacant land to manage stormwater and support insect habitat

Reclaiming urban vacant land to manage stormwater and support insect habitat

The distribution characteristics and driving mechanism of vacant land in Chengdu, China: A perspective of urban shrinkage and expansion

Solving the land vacancy problem and promoting urban transformation is a crucial challenge for the new urbanization construction in China, especially under the dual pressure of rapid urban expansion and localized shrinkage. This study explores the spatial distribution rules and driving mechanisms of urban vacant land (UVL) in Chengdu, China, using GIS spatial analysis and multi-scale geographically weighted regression (MGWR) model. Our results indicated that there are 3859 UVLs in Chengdu, accounting for 16.19 % of the total construction land. There are three typical characteristics for their spatial distribution: typological differentiation, circular structure, and spatial agglomeration. The double-layer classification scheme of UVL from the perspective of urban shrinkage and expansion is a promising option for the future research. Furthermore, location, economic vitality, infrastructure, and natural conditions significantly impact the distribution of UVL, but the driving mechanisms of shrinking and expanding vacant lots are different. The impact intensity of the driving factors has significant spatial non-stationarity characteristics, and their driving directions may even be the opposite among different regions. The formation causes of UVL are complex and multi-dimensional, and future research should fully consider spatial scale dependence.

Planning Tools to Revitalise Urban Vacant Land from Ecological Perspectives: A Systematic Review

Urban vacant land availability offers revitalisation opportunities in the form of improving ecological functions. However, less is known about the available planning tools with which to mobilise this effort. Hence, this systematic review adopts ecological perspectives to explore planning tools to revitalise urban vacant land. The search strategy employs Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to track original research on vacant urban land from selected electronic databases. The search revealed thirty-six studies focusing on substance-oriented planning tools (indicator systems, Geographic Information System (GIS), models/simulations, field surveys, and experiments) and process-oriented tools (questionnaire surveys, the Delphi method, focus groups, and interviews). This review suggests that future studies adopt hybrid planning tools that combine the essence of substance- and process-oriented tools. Furthermore, as a framework, it recommends taking a stepwise approach at various planning stages to revive vacant land. Additional studies from the perspective of growing cities are necessary to provide insights into urban vacant land revitalisation planning, considering the competing objectives of economic prosperity and green space preservation.

Pocket park in urban regeneration of China: Policy and perspective

Perched on the edge and corner of the city center, pocket parks transform urban vacant land into vibrant urban oases. It can greatly shorten the distance from citizens to the park, thereby promoting citizens' participation in outdoor activities and improving urban vitality. The construction of pocket parks in China started late. However, it has developed rapidly in recent years, which supports urban regeneration. A government document, published by the Ministry of Housing and Urban-Rural Development of the People’s Republic of China in 2002, promotes the construction of pocket parks. In the process of promoting the construction of pocket parks in Chinese cities, problems such as unclear construction standards, difficult operation and maintenance, blind copying, and emphasis on the landscape over the function have emerged. The aforementioned issues are elaborated and corresponding suggestions are pointed out in this short communication.

Movement of Urban Vacant Land Use as an Effort in Keeping the Food Security in Surakarta during the Pandemic

The urban farming movement has been carried out in several parts of the world, such as Havana and Detroit, which was initiated by the food or economic crisis faced by the region. Urban farming through the movement of “ Lihat Kebunku ” (Look at My Garden) by using the rest of the house yard by planting household crops. The movement of “ Lihat Kebunku ” (Look at My Garden) can be done with collaborative actions and can be carried out with many parties, from the local community, the private sector, other communities, universities, and even the government. This study reveals the potential of the urban farming movement that can support the food self-sufficiency in Indonesia if it is promoted massively. This study was conducted using the normative method by looking at data from various sources with concept research methods. The data and information collection techniques used were secondary data studies and existing concepts. The results of this study indicate that the movement of agricultural land use in the city of Surakarta can be a mobilization process that leads to efforts to ensure the growth of participation and awareness of the wider community in using the abandoned land through urban farming. Keywords: urban farming, food self-sufficiency, Covid-19. DOI: https://doi.org/10.55463/hkjss.issn.1021-3619.60.71

An Analysis of Urban Vacant Land on the Macau Peninsula

With the development and construction of the city, the urban development of the Macau Peninsula has entered an era of stock development against the background of the limited scale of urban land. With the shortage of land resources, the problem of unused land on the Macau Peninsula is coming to the fore. This paper mainly studies the problem of idle land in the Macau Peninsula, based on the urban development and particular historical background of the region, investigates and elaborates on its complex formation causes through the literature research method, and analyzes the spatial distribution characteristics of idle land in the current situation of the Macau Peninsula by using GIS technology. Based on the above research,suggestions are put forward to prevent and manage the urban vacant land problem in the future urban management and development of Macau.

Optimizing the co-benefits of food desert and urban heat mitigation through community garden planning

Urban community gardens can reduce food insecurity and serve as green spaces alleviating extreme temperatures. Such co-benefit synergy may prove especially significant for arid-land metropolises. Despite these synergistic roles, planning for community gardens is largely undertaken in an ad-hoc manner. To date, few studies have addressed the full potential (co-benefits) of developing urban vacant land into community garden-green spaces. We addressed this in a spatially-optimized way, developing a model seeking to mitigate food desert and urban heat, and applied it to the fast sprawling Phoenix metro-area, Arizona (USA). Examining more than 5,000 vacant parcels for potential garden-green spaces, we found that the optimal number and locations of community gardens needed for different mitigation goals can vary significantly. In the Phoenix metro-area, the gardens required for extreme heat mitigation is about twice the number for food desert mitigation because high-temperature areas are more prevalent and expansive in semi-arid desert environment compared to the relatively small number low income, food desert areas. Furthermore, we found that the existing 76 community gardens were mostly clustered around urban cores, leaving two-thirds of the metro-area underserved. If sited in a spatially-optimized way, the co-benefits gained from the 76 gardens could be doubled, and covering more high-need neighborhoods. Integrating fine-scale vacant parcel data, our model identified high potential community garden-greening sites in priority neighborhoods with a precision not capable in conventional planning methods. Our findings demonstrate that spatially-optimized planning is of particular importance to avoid clustering of community gardens and ensure more equal access to local food and outdoor cooling benefits.

Large-scale automatic identification of urban vacant land using semantic segmentation of high-resolution remote sensing images

Urban vacant land is a growing issue worldwide. However, most of the existing research on urban vacant land has focused on small-scale city areas, while few studies have focused on large-scale national areas. Large-scale identification of urban vacant land is hindered by the disadvantage of high cost and high variability when using the conventional manual identification method. Criteria inconsistency in cross-domain identification is also a major challenge. To address these problems, we propose a large-scale automatic identification framework of urban vacant land based on semantic segmentation of high-resolution remote sensing images and select 36 major cities in China as study areas. The framework utilizes deep learning techniques to realize automatic identification and introduces the city stratification method to address the challenge of identification criteria inconsistency. The results of the case study on 36 major Chinese cities indicate two major conclusions. First, the proposed framework of vacant land identification can achieve over 90 percent accuracy of the level of professional auditors with much higher result stability and approximately 15 times higher efficiency compared to the manual identification method. Second, the framework has strong robustness and can maintain high performance in various cities. With the above advantages, the proposed framework provides a practical approach to large-scale vacant land identification in various countries and regions worldwide, which is of great significance for the academic development of urban vacant land and future urban development.

What Else Is There? Vacancy as Development Problem and Solution

Urban vacant land is often framed as a consequence of political and economic problems that negatively affect land values, tax bases, public safety, and community flourishing. At the same time, vacancy presents governments—and private developers—with opportunities for transformation. This commentary examines a development plan that makes use of vacancy in Chicago, Illinois to shed light on the ways in which vacancy can become a project in itself rather than a side effect of growth, decay, and change. I argue that through processes of erasure, re-inscription, and assemblage, vacancy projects enable redevelopment in ways that further politicians' and developers' agendas for post-industrial urban economic growth. In Chicago, vacant industrial land, such as the former Clybourn Corridor Planned Manufacturing District, is simultaneously positioned as an insurmountable problem and an exceptional development opportunity. I use the Clybourn Corridor case to illuminate the social, political, and economic processes through which vacancy is made productive in urban contexts. The relative opacity of such processes has profound implications for urban futures, shaping who makes plans for and benefits from the transformation of urban space. By delving into a vacancy project ethnographically in Chicago, a city struggling, like many, to define a post-industrial future, this commentary contributes to our understandings of vacancy as a tool to draw resources in and make development happen. It demonstrates the political, economic, and social processes through which urban land is defined and reconfigured as a site for public and private intervention as well as opportunity in the contemporary moment.

Automatic detection of urban vacant land: An open-source approach for sustainable cities

With urban vacant land including brownfield land attracting increasing attention; spatial information on vacant land is crucial for city planners and decision-makers. Yet vacant land mapping faces the challenges of confusing terminology, reliance on inefficient registration systems, and the cost of data collection. Automatic site detection has been attempted using classification of remote sensing images. However, because the morphology of vacant land can cover such diverse aspects as derelict structures, bare soil, and vegetation or a mix thereof, even when commercial high-resolution images are used, it remains difficult to achieve this goal.This study starts by defining an urban vacant land typology suitable for automatic site detection. It covers four categories: transportation-associated land; natural sites with unfavorable conditions such as wetlands, steep slopes, or riverbanks; unattended areas or reserve parcels as “leftover spaces” within the urban fabric; and brownfield sites previously used but now abandoned.The study goes on to describe the rule-based data fusion method applied for site detection. The fusion procedure combines remote sensing images, GIS layers and citizen science data. For each type of vacant land, a separate data processing flow was developed. The method was tested in 63 urban and rural districts in Germany, identifying a large number of vacant sites.The study used an open-source approach. Open-source spatial data was collected for analysis, aerial photos provided by open-data projects were used for quality checks, and free software was used for data processing. This means that, information on vacant land is retrievable by local administrations irrespective of their financial circumstances. Depending on local urban development strategies, the detected sites can be used to support different sustainability goals.

Urban vacant land in rapidly urbanized areas: Status, micro-level drivers, and implications

The existence of vacant land is a worldwide phenomenon. However, few studies have used quantitative methods to focus on the micro-level drivers that cause land to remain vacant in small towns. In this study, we determined the ordered utilization status of vacant land in N County of Zhejiang Province, China, via visual inspection of high-resolution images captured in 2014, and identified the micro-level drivers of continued land vacancy using ordinal logistic regression. The results show that 57% of the newly supplied land, converted from agricultural land to urban land, released between 2006 and 2012 in N County was still unutilized or underutilized in 2014. Micro-level drivers, including elevation, distance to the industrial park, number of urban land units within the neighborhood, and the vacant years, positively affected the utilization rate of urban land. In contrast, the slope, distance to water, and distance to built-up areas had a negative effect. To address the continuing prevalence of vacant land, N County should prioritize the micro-level drivers of positive land use and strengthen post-land-supply supervision. This study provides a micro perspective for studying the drivers of vacant land prevalence and a decision-making framework in small towns of China to formulate land-supply schemes.