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Spatial Analysis for the Sustainable City

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 7455

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Special Issue Editors

Dr. Sumeeta Srinivasan

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Guest Editor

Department of Urban and Environmental Policy and Planning, Tufts University, Medford, MA 02155, USA
Interests: transportation; health; spatial models; geographic information systems
Special Issues, Collections and Topics in MDPI journals

Dr. Rebecca Shakespeare

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Guest Editor

Department of Urban and Environmental Policy and Planning, Tufts University, Medford, MA 02155, USA
Interests: housing; geographic information systems (GISs); cities; qualitative GIS

Special Issue Information

Dear Colleagues,

Urban sustainability requires interaction between the eco-physical, social, and economic environments [1]. City planners and policy makers must closely examine several aspects of urban sustainability, including land use and the built environment, energy conservation, recycling and reuse, communication, and transport [2]. There are neighborhoods in cities all over the world that are vulnerable to climate change based on where they are located, or because of the socioeconomic characteristics of the residents [3,4]. The use of geographic information systems (GISs) has also contributed to a better understanding of the spatial differences within cities. City and regional planning agencies routinely collect data and make it available; thus, spatial analysis is increasingly selected as a tool of choice for planners and policy makers. Spatial data can be acquired in a variety of ways, including surveys, remote sensing through satellite or drones, and apps that urban residents can install on their phones or wear.

This Special Issue of Sustainability is for researchers who want to publish innovative high-quality research papers, reviews, case studies, or position papers focusing on the use of spatial data analyses in planning for sustainable cities. A nonexhaustive list of potential topics is provided below:

Spatial data analysis for transportation, health, energy, and land use studies in urban areas;
Spatiotemporal simulation or modelling of data in urban planning for sustainablity;
Spatial methods for statistical and qualitative analysis impacting urban planning;
Data ethics in spatial studies of cities;
Case studies of qualitative or quantitative GIS-based urban and regional planning;
Spatial data quality, and processing for urban planning;
Applications for spatiotemporal data mining, geovisualization, or spatial decision-support systems for urban planning.

References:

Hassan, A.M.; Lee, H. The paradox of the sustainable city: Definitions and examples. Environ. Dev. Sustain. 2015, 17, 1267–1285.
Jenks, M.; Jones, C. Dimensions of the sustainable city. Stice 2009, 14, 87–97.
Cassarino, M.; Shahab, S.; Biscaya, S. Envisioning happy places for all: A systematic review of the impact of transformations in the urban environment on the wellbeing of vulnerable groups. Sustainability 2021, 13, 8086.
Hendricks, M.D.; Van Zandt, S. Unequal protection revisited: Planning for environmental justice, hazard vulnerability, and critical infrastructure in communities of color. Environ. Justice 2021, 14, 87–97.

Dr. Sumeeta Srinivasan
Dr. Rebecca Shakespeare
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

urban planning
spatial analysis
spatial decision support systems
spatial indicators
geovisualization
sustainability assessment
spatial statistics
GIS (geographic information systems)
sustainable development goals
qualitative GIS
big data
remote sensing

Published Papers (7 papers)

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Research

18 pages, 3009 KiB

Open AccessArticle

Constructing Ecological Networks for Mountainous Urban Areas Based on Morphological Spatial Pattern Analysis and Minimum Cumulative Resistance Models: A Case Study of Yongtai County

by Cheng Zou, Xiaoxiang Tang, Qian Tan, Huicheng Feng, Huanyu Guo and Junxiang Mei

Sustainability 2024, 16(13), 5559; https://doi.org/10.3390/su16135559 - 28 Jun 2024

Viewed by 379

Abstract

In order to alleviate the increased habitat fragmentation caused by the accelerating urbanization and ecological deterioration, constructing ecological networks is an effective way to improve ecological connectivity, facilitate regional energy flow, and promote biodiversity enhancement. In this study, Yongtai County was taken as the research object, and the morphological spatial pattern analysis (MSPA) method was used to analyze the landscape pattern, identify the ecological source sites, classify the ecological source sites according to the importance degree by possible connectivity index (PC) and the Delta values for probability index of connectivity (dPC), and then construct the potential ecological corridors with the help of the minimum cumulative resistance (MCR) model to generate the ecological network, and then put forward the optimization strategy according to the current situation. The results show that (1) the core area of Yongtai County is 1071.06 km², the largest among all landscape types, with a fragmented distribution, high degree of fragmentation, and poor connectivity, mainly in the east and southwest, and sparser in the middle. (2) The area of highest resistance value is mainly located in the built-up areas of towns and rural settlements in the central and northwestern parts of the country; the lowest value is distributed in the southwest and southeast, and the land use mode is mainly expressed as woodland. (3) The ecological network consists of 13 ecological sources and 78 potential ecological corridors. The ecological sources are mainly located in the east and southwest, with high connectivity; the potential ecological corridors are distributed in the form of a network, with fewer in the center, resulting in the phenomenon of ecological disconnection. (4) Lack of ecological sources and corridors, serious landscape fragmentation, and optimization of ecological network by adding and protecting ecological sources, repairing ecological breakpoints and building stepping stones. This study is of guiding significance for urban green space system planning, biodiversity protection, and ecosystem function enhancement in Yongtai County, and also provides reference for ecological protection and optimization in other mountainous cities. Full article

(This article belongs to the Special Issue Spatial Analysis for the Sustainable City)

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27 pages, 35594 KiB

Open AccessArticle

Study on Spatialization and Spatial Pattern of Population Based on Multi-Source Data—A Case Study of the Urban Agglomeration on the North Slope of Tianshan Mountain in Xinjiang, China

by Yunyi Zhang, Hongwei Wang, Kui Luo, Changrui Wu and Songhong Li

Sustainability 2024, 16(10), 4106; https://doi.org/10.3390/su16104106 - 14 May 2024

Viewed by 600

Abstract

The urban agglomeration on the north slope of the Tianshan Mountains is a pivotal place in Western China; it is essential for the economic growth of Xinjiang and acts as a critical bridge between China’s interior and the Asia–Europe continent. Due to unique natural conditions, the local population distribution exhibits distinct regional characteristics. This study employs the spatial lag model (SLM) from conventional spatial analysis and the random forest model (RFM) from contemporary machine learning techniques. It integrates traditional geographic data, including land cover data and nighttime light data, with geographical big data, such as POI (points of interest) and OSM (OpenStreetMap), to build a comprehensive indicator database. Subsequently, it simulates the spatial population distribution within the urban agglomeration on the northern slopes of the Tianshan Mountains in 2020. The accuracy of the results is then compared and assessed against the accuracy of other available population raster datasets, and the spatial distribution pattern in 2020 is analyzed. The findings reveal the following: (1) The result of SLM, combined with multi-source data, predicts the population distribution as a relatively uniform and nearly circular structure, with minimal spatial differentiation. (2) The result of RFM, employing multi-source data, better captures the spatial population distribution, resulting in irregular boundaries that are indicative of strong spatial heterogeneity. (3) Both models demonstrate superior accuracy in simulating population distribution. The spatial lag model’s accuracy surpasses that of the GHS and GPW datasets, albeit still trailing behind WorldPop and LandScan. Meanwhile, the random forest model significantly outperforms the four aforementioned population raster datasets. (4) The population spatial pattern in the urban agglomeration on the north slope of the Tianshan Mountains predominantly consists of four distinct circles, illustrating a “one axis, one center, and multiple focal points” distribution characteristic. Combining the random forest model with geographic big data for spatialized population simulation offers robust scientific validity and practicality. It holds potential for broader application within the urban agglomeration on the Tianshan Mountains and across Xinjiang. This study can offer insights for studies on regional population spatial distributions and inform sustainable development strategies for cities and their populations. Full article

(This article belongs to the Special Issue Spatial Analysis for the Sustainable City)

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22 pages, 7534 KiB

Open AccessArticle

Towards Resilient Cities: Optimizing Shelter Site Selection and Disaster Prevention Life Circle Construction Using GIS and Supply-Demand Considerations

by Hong Jiao and Shining Feng

Sustainability 2024, 16(6), 2345; https://doi.org/10.3390/su16062345 - 12 Mar 2024

Viewed by 1020

Abstract

City health examinations are integral to China’s urban planning, construction, and management. They effectively identify potential risks and vulnerabilities in urban development, ensuring safety resilience—a critical component. This resilience enhances the city’s ability to withstand internal and external shocks, promoting the safety of urban residents and fostering sustainable city development. Drawing on the Japanese disaster prevention strategy, the disaster prevention life circle emerges as a rescue and protection system during urban disasters, fortifying urban safety resilience. However, smaller and mid-sized cities, constrained by limited resources, significantly need to catch up in disaster prevention planning. Consequently, bolstering safety resilience in these cities becomes a pressing concern. This study focuses on Lindian County in Heilongjiang Province as the urban area under consideration for resilient city objectives. Leveraging the ArcGIS network analysis tool, we optimize the placement of emergency shelters, aligning with urban disaster assessments and the equilibrium of disaster prevention facility supply and demand. Accessibility analysis of emergency shelters was conducted using the Gaussian two-step floating catchment area method. Ultimately, we integrate the range of demand points assigned to each shelter, along with the effective land area reflecting the supply of shelters, as weights into a weighted Voronoi diagram. This diagram is combined with a reference to the entire region to delineate the disaster prevention life circle. Findings reveal that, under the premise of minimizing government construction costs while maximizing coverage and evacuation utilization rates, the optimal resident emergency congregate shelters in the study area are 8, with 98 emergency evacuation and embarkation shelters. Striking a balance between disaster prevention facility supply and demand and regional accessibility, the urban area of Lindian County is segmented into 3 resident disaster prevention life circles and 24 emergency disaster prevention life circles. The objective of this study is to optimize shelter siting and establish disaster prevention life circles in diverse urban areas. This endeavor aims to bolster urban resilience and foster sustainable urban development. Full article

(This article belongs to the Special Issue Spatial Analysis for the Sustainable City)

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17 pages, 3857 KiB

Open AccessArticle

Research on the Public Environment Renewal of Traditional Villages Based on the Social Network Analysis Method

by Qin Li, Shuangning Lv, Jingya Cui, Yijun Liu and Zonghao Chen

Sustainability 2024, 16(3), 1006; https://doi.org/10.3390/su16031006 - 24 Jan 2024

Cited by 1 | Viewed by 911

Abstract

Constructing digital models of public spaces of social networks found in traditional villages helps us explore the logic behind the interactions that occur within various relationships as well as achieve the optimization of spatial layouts and the equalization of the different use needs that social groups have. However, this analytical method has not been fully studied in the field focusing on the rationality of public spaces in traditional villages. This paper takes the traditional village protection demonstration area in Mentougou District, Beijing, China, as the object of research and selects three different forms of traditional villages to be analyzed. It tries to excavate the universal laws and unique differences in the models of the different forms of traditional villages and establish models for quantitative research, such as index calculation, so as to increase the depth and accuracy of research and embody the characteristic laws of the spaces studied in terms of the nature of the structures and relationships that are part of these spaces. The results show that the spatial characteristics of the different forms of traditional villages are obviously different from the relevance, equalization, and connectivity of spatial networks. The cluster form of traditional villages tends to focus on the villagers’ use demands and the assessment of the spatial status quo by increasing the number of spatial nodes and transforming spatial functions in order to achieve higher equalization. The dispersed form of traditional villages tends to focus on optimizing the relevance of spatial network structures. The linear form of traditional villages tends to establish public spaces so as to increase the depth and accuracy of research. Villages ought to establish direct links between public spaces in order to increase the connectivity of traditional villages. This study provides a rational basis for the differentiated planning decisions of traditional villages and lays the foundation for the promotion of the smooth and sustainable development of regional villages. Full article

(This article belongs to the Special Issue Spatial Analysis for the Sustainable City)

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19 pages, 12715 KiB

Open AccessArticle

Pro-Social Solutions in Residential Environments Created as a Result of Participatory Design

by Katarzyna Kołacz and Anna Podlasek

Sustainability 2024, 16(2), 510; https://doi.org/10.3390/su16020510 - 6 Jan 2024

Cited by 2 | Viewed by 951

Abstract

The pro-social dimension of contemporary housing is one of the main postulates of sustainability. The work aims to draw attention to the residential environment created as a result of participatory design and to examine how and to what extent it supports the creation of social contacts and the identification of inhabitants with their place of residence. The study included three housing projects prepared by the communities: B.R.O.T Aspern, Seestern Aspern, and LiSA. They are part of one urban block located in Aspern, part of the 22nd district of Vienna—Donaudstadt. The case studies were analysed using the same ten evaluation criteria. They were established based on previously developed theories of sociologists, psychologists and architects on the features of architecture and spaces supporting the formation of neighbourly contacts and the identification of users with their place of residence. The research showed that although the same evaluation criteria were used, each design group found an individual way to meet them in their project such as innovative design elements, unique community spaces, or user-driven features. This is proof that not only the place where architecture is created, has its conditions, and the planners and architects creating the project give it an individual, pro-social character, but also the users who create it. However, it is important to create an appropriate organizational, legal architectural and urban framework for the participation process to be successful. Full article

(This article belongs to the Special Issue Spatial Analysis for the Sustainable City)

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21 pages, 5626 KiB

Open AccessArticle

Spatiotemporal Evolution and Driving Factors of Land Development: Evidence from Shandong Province, China

by Chuansong Zhao, Ran Geng, Jianxu Liu, Liuying Peng and Woraphon Yamaka

Sustainability 2023, 15(20), 15069; https://doi.org/10.3390/su152015069 - 19 Oct 2023

Cited by 1 | Viewed by 924

Abstract

As populations and economies have grown rapidly, questions of land development and use have intensified. It has become a major global concern to achieve sustainable land use practices. This study reveals evolution of the spatiotemporal pattern of land development intensity of counties in Shandong Province by introducing a land development intensity measurement model combined with three-dimensional trend surface and spatial autocorrelation analyses. Geodetector and geographically weighted regression models were employed to demonstrate the interplay and spatiotemporal heterogeneity between development intensity and drivers. The empirical results show that the value of land development intensity of counties in Shandong Province shows a general growth trend, with the number of counties with higher values gradually increasing and the number of counties with lower values gradually decreasing. We also found that the spatial heterogeneity of land development intensity across counties in Shandong Province is significant, and the spatial distribution pattern is basically consistent with the “one group, two centers and three circles” strategy proposed by the Shandong Provincial Government. There is also a positive spatial correlation and clustering effect of land development intensity of counties in Shandong Province. High (low) value clusters are concentrated in core hot (cold) counties, driving some of the surrounding counties towards radial development. The alteration in the intensity of county land development is a complex occurrence that is shaped by numerous factors. Among these, GDP per capita and population density have the primary influence on land development of counties in Shandong Province. To achieve coordinated regional social, economic, and environmental benefits, land development within the county should adhere to the principle of adapting to local conditions and implement differentiated development strategies according to different development intensities. Full article

(This article belongs to the Special Issue Spatial Analysis for the Sustainable City)

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22 pages, 5150 KiB

Open AccessArticle

Multi-Scale Geographically Weighted Elasticity Regression Model to Explore the Elastic Effects of the Built Environment on Ride-Hailing Ridership

by Zhenbao Wang, Xin Gong, Yuchen Zhang, Shuyue Liu and Ning Chen

Sustainability 2023, 15(6), 4966; https://doi.org/10.3390/su15064966 - 10 Mar 2023

Cited by 3 | Viewed by 1630

Abstract

Understanding the relationship between the built environment and the ride-hailing ridership is crucial to the prediction of the demand for ride-hailing and the formulation of the strategy for upgrading the built environment. However, the existing studies on ride-hailing ignore the scale effect and zone effect of the modifiable area unit problem (MAUP), and show a lack of consideration for the elastic relationship with spatial heterogeneity between built environment variables and ride-hailing ridership. Taking Chengdu as an example, this paper selects 12 independent variables based on the “5Ds” (density, diversity, design, destination accessibility and distance to transit) of the built environment, the dependent variables are the density of ride-hailing pick-ups in the morning and evening peak hours, and 11 spatial units are proposed according to different scales and zoning methods for the aggregation of built environment variables and ride-hailing pick-ups. With the goal of global optimal goodness-of-fit, we determined the optimal spatial unit by using the log-linear Ordinary Least-Squares (OLS) model. A multi-scale geographically weighted elastic regression (MGWER) model is formulated to explore the relative effect of the built environment on the ride-hailing ridership and spatial heterogeneity. The average value of positive elastic local regression coefficient of different variables is used to measure the relative positive impact of built environment factors, and the absolute value of the average value of negative elastic local regression coefficient is used to measure the relative negative impact of built environment factors. The results show that: (1) The MGWER model under the community unit division has the best global goodness-of-fit. (2) Different built environment variables have different elastic impacts on the demand for ride-hailing. For the morning peak hours and evening peak hours, the top three built environment factors with positive impacts are ranked as follows: commercial POI density > average house price > population density, and distance to CBD has the highest negative impacts on pick-up ridership. (3) The different local elasticity coefficients of the built environment factors at different stations are discussed, which indicate the spatial heterogeneity of the ride-hailing ridership. The optimal community zoning method can provide a basis for the zoning and scheduling management of ride-hailing. The results of the built environment variables with greater impact are conducive to the formulation of targeted urban renewal strategies in the process of adjusting the ridership of ride-hailing. Full article

(This article belongs to the Special Issue Spatial Analysis for the Sustainable City)

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