Spatial Decision Support Systems for Urban Sustainability

Abstract submission deadline

31 October 2025

Manuscript submission deadline

31 December 2025

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Topic Information

Dear Colleagues,

Spatial Decision Support Systems (SDSSs) are designed around geospatial data, models, and analytical tools that collectively support human planning and decision-making procedures in multiple application areas. These areas are constantly evolving to better address existing real-world challenges and find innovative ways forward such as in enabling and facilitating urban sustainability.

In this Topic Issue, we focus on the theory and methods of SDSSs and their implementation in the context of urban sustainability. We are interpreting sustainability broadly to mean the understanding and improvement of inputs and processes that optimize the distribution of output patterns. We welcome contributions from research directions that focus on data-oriented approaches (e.g., spatial multicriteria methods and remote sensing), intelligence-based approaches (e.g., machine learning and artificial intelligence methods), model-based approaches (e.g., analytics and simulation methods), and participatory approaches (e.g., citizen science and volunteer GIS methods). In addition, the interoperability between the data, systems, and people can yield innovative contributions. We anticipate these ideas will be developed around the pressing urban sustainability challenges that deal with land use and land cover change, climate change adaptation, and population growth, among others.

The topic "Spatial Decision Support Systems for Urban Sustainability” provides an outlet to publish original research and application papers. Join us as we re-examine existing pathways and explore new ground in the science and applications of SDSSs. We look forward to your contributions.

Dr. Shivanand Balram
Dr. Raja Sengupta
Dr. Jorge Rocha
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Geographies geographies	-	1.7	2021	17.5 Days	CHF 1000	Submit
Geomatics geomatics	-	-	2021	22.1 Days	CHF 1000	Submit
ISPRS International Journal of Geo-Information ijgi	2.8	6.9	2012	35.8 Days	CHF 1900	Submit
Land land	3.2	4.9	2012	16.9 Days	CHF 2600	Submit
Urban Science urbansci	2.1	4.3	2017	20.7 Days	CHF 1600	Submit
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400	Submit

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Published Papers (17 papers)

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25 pages, 11681 KiB  

Open AccessArticle

Simulating Co-Evolution and Knowledge Transfer in Logistic Clusters Using a Multi-Agent-Based Approach

by Aitor Salas-Peña and Juan Carlos García-Palomares

ISPRS Int. J. Geo-Inf. 2025, 14(4), 179; https://doi.org/10.3390/ijgi14040179 - 20 Apr 2025

Viewed by 129

Abstract

Some complex social networks are driven by adaptive and co-evolutionary patterns. However, these can be difficult to detect and analyse since the links between actors are circumstantial and often not revealed. This paper employs a Geographic Information Systems (GIS) integrated multi-agent-based approach to [...] Read more.

Some complex social networks are driven by adaptive and co-evolutionary patterns. However, these can be difficult to detect and analyse since the links between actors are circumstantial and often not revealed. This paper employs a Geographic Information Systems (GIS) integrated multi-agent-based approach to simulate co-evolution in a complex social network. A case study is proposed for the modelling of contractual relationships between road freight transport companies. The model employs empirical data from a survey of transport companies located in the Basque Country (Spain) and utilises the DBSCAN community detection algorithm to simulate the effect of cluster size in the network. Additionally, a local spatial association indicator is employed to identify potentially favourable environments. The model enables the evolution of the network, leading to more complex collaborative structures. By means of iterative simulations, the study demonstrates how collaborative networks self-organise by distributing activity and knowledge and evolving into complex polarised systems. Furthermore, the simulations with different minimum cluster sizes indicate that clusters benefit the agents that are part of them, although they are not a determining factor in the network participation of other non-clustered agents. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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34 pages, 9249 KiB  

Open AccessArticle

Spatial Agglomeration Characteristics and Impact Factors of the Cultural and Creative Industries in Harbin

by Zuhang Liu, Daming Xu and Xinyang Wang

ISPRS Int. J. Geo-Inf. 2025, 14(4), 158; https://doi.org/10.3390/ijgi14040158 - 5 Apr 2025

Viewed by 254

Abstract

The cultural and creative industries have garnered widespread attention as an important vehicle for promoting the transformation and upgrading of urban industrial structures. In this investigation, we take Harbin—a city in China with a strong industrial legacy—as a case study. Through kernel density [...] Read more.

The cultural and creative industries have garnered widespread attention as an important vehicle for promoting the transformation and upgrading of urban industrial structures. In this investigation, we take Harbin—a city in China with a strong industrial legacy—as a case study. Through kernel density analysis and the DBSCAN clustering algorithm, we identify and analyze the spatial distribution and spatiotemporal evolution patterns of 157 clusters of cultural and creative industries in Harbin. We construct a Geographic Weighted Regression (GWR) model using 20 indicators from three categories (i.e., social, cultural, and economic) to analyze the factors impacting the agglomeration of cultural and creative industries in Harbin. Our findings reveal that the cultural and creative industries exhibit an agglomeration pattern. A large-scale agglomeration area for large enterprises has formed in the city center, while scattered, small-scale agglomeration zones for emerging small enterprises have formed in newly developed areas on the urban periphery. The GWR analysis indicates that economic factors have the most significant impact on the agglomeration of cultural and creative industries; however, night-time economic facilities show a negative correlation. Among social factors, the convenience of public transportation and new energy transportation infrastructure have a significant impact on industrial agglomeration. Regarding cultural factors, cultural and sports facilities have the greatest influence, while public information kiosks and public arts education facilities exhibit spatial variability. These findings provide a scientific basis for policy formulation and contribute to promoting the healthy development of cultural and creative industries. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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19 pages, 6062 KiB  

Open AccessArticle

Multi-Scenario Simulation of Urban Land Expansion Modes Considering Differences in Spatial Functional Zoning

by Jing Yang, Zheng Wang and Yizhong Sun

ISPRS Int. J. Geo-Inf. 2025, 14(4), 138; https://doi.org/10.3390/ijgi14040138 - 24 Mar 2025

Viewed by 243

Abstract

As a precious non-renewable resource, the rational utilization of land resources is crucial for global sustainable development, with urban land development scenario prediction and analysis serving as key methodologies to achieve this goal. Although previous studies have extensively explored urban land expansion simulation [...] Read more.

As a precious non-renewable resource, the rational utilization of land resources is crucial for global sustainable development, with urban land development scenario prediction and analysis serving as key methodologies to achieve this goal. Although previous studies have extensively explored urban land expansion simulation and scenario forecasting, further investigation is still required to simultaneously address spatial functional zoning differentiation and urban expansion mode diversity while simulating development trends under various expansion modes. In this study, we integrated major functional zones and ecological redlines to delineate urban spatial functional units and define development coefficients for construction land within each unit. Based on the spatial heterogeneity of expansion modes, the scopes of infill, sprawl, and leapfrog expansion modes were determined. Combining functional zoning and expansion mode zoning, we employed cellular automata model principles to design land conversion rules and simulate the evolution of land use under different expansion modes. Using Jiangyin City, China, as a case study, the model achieved a high simulation accuracy (kappa coefficient of 0.959), significantly outperforming comparative models. By predicting land-use patterns under different expansion scenarios and aligning with Jiangyin’s territorial planning goals, we recommend implementing infill–sprawl–leapfrog and infill–leapfrog–sprawl expansion modes. The results demonstrate that the model effectively supports the refined simulation of urban land expansion, providing a scientific basis for optimizing land resource allocation and balancing ecological protection with urban development. Future research could integrate multiple types of territorial control elements, refine land-use categories, and optimize prediction scenarios to enhance the model’s practicality and applicability. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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23 pages, 14425 KiB  

Open AccessArticle

Spatiotemporal Diffusion Patterns Associated with COVID-19 in the Tel Aviv-Jaffa and Haifa (Israel) Metropolitan Regions

by Adi Ofir and Motti Zohar

Geographies 2025, 5(1), 14; https://doi.org/10.3390/geographies5010014 - 16 Mar 2025

Viewed by 342

Abstract

Social and cultural diffusion determines how behavioral phenomena spread among communities. The COVID-19 pandemic, which emerged globally at the beginning of 2020, triggered changes in human behavior in various settlements and regions. In this study, we use a spatial approach to examine diffusion [...] Read more.

Social and cultural diffusion determines how behavioral phenomena spread among communities. The COVID-19 pandemic, which emerged globally at the beginning of 2020, triggered changes in human behavior in various settlements and regions. In this study, we use a spatial approach to examine diffusion patterns during the Omicron wave (December 2021–February 2022). We collected data on daily testing and confirmed cases from the Israeli Ministry of Health (MoH) database, as well as population characteristics from the Israel Central Bureau of Statistics (CBS). These data were normalized per population, classified regionally and analyzed spatially using GIS, to verify the significance of the results. We found a contagious diffusion pattern apparent spatially in the metropolitan regions of Tel Aviv-Jaffa and Haifa (Israel). Accordingly, the undulating pattern of the number of COVID-19 tests and confirmed cases began in the center of the given metropolitan region (populated with high-class settlements) at the beginning of the wave, spread out to the periphery (populated with high-class settlements) toward the mid-wave period, and returned to the center when the wave ended. Additionally, we have seen that these patterns do not accord with the morbidity spread, implying that social characteristics may have been dominant in determining the diffusion pattern. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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21 pages, 19976 KiB  

Open AccessArticle

Evaluation Methods for the Human–Land Coupling Coordination Relationship in a Metro Station Area: A Case Study of Chengdu Metro Line 1

by Zhiyue Qiu, Shirui Wen, Hong Yuan, Ziyi Liu, Yao Wei, Siqi Yanling, Runlong Dai, Xiang Li and Yuxin Gu

ISPRS Int. J. Geo-Inf. 2025, 14(3), 102; https://doi.org/10.3390/ijgi14030102 - 23 Feb 2025

Viewed by 633

Abstract

At present, more than 200 cities in the world have developed metro systems. Under the agglomeration effect of traffic nodes, rapid population agglomeration and land development and utilization have formed around metro stations in cities. However, there is still the problem of uncoordinated [...] Read more.

At present, more than 200 cities in the world have developed metro systems. Under the agglomeration effect of traffic nodes, rapid population agglomeration and land development and utilization have formed around metro stations in cities. However, there is still the problem of uncoordinated development in each station area along the metro, so it is urgent to build an evaluation method of the coupling and coordination relationship between people and land to study the laws of population activities, industrial agglomeration, traffic resources, and other aspects in the metro station area and analyze its rationality and matching. In this study, Chengdu, the central city in the west of China, is selected as an example, and Metro Line 1, which has the longest history and is the most mature development in the city, is taken as an example. Starting from the coupling and coordination relationship between the human activity demand and metro resource supply, the evaluation indicator system of the coupling and coordination relationship between people and land in the station area of Chengdu Metro Line 1 is constructed. By collecting multi-source data, the coupling coordination degree model (CCDM) is used to quantitatively evaluate the human–land coupling coordination relationship in the station area. Then, the gray relational analysis (GRA) combined with the spatial distribution characteristics are used to analyze the characteristics and influencing factors of the coupling and coordination relationship, and it is concluded that the station area of Chengdu Metro Line 1 presents a circular and multi-center coupling and horizontal coordination spatial structure. Among them, the degrees of the population concentration and activity intensity, the levels of economic and industrial development, the level of service support, and the degree of contact with surrounding areas have great influences on the coupling and coordination levels of the station area. Finally, some improvement strategies are put forward, such as optimizing the network layout, building multi-level centers, strengthening functional connections, and enhancing the development intensity. This study provides a new method for the study of the coordinated development of metro station areas and has practical significance for evaluating the construction and development statuses of metro station areas, guiding the planning of metro stations, and formulating regional development strategies of metro stations. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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24 pages, 15920 KiB  

Open AccessArticle

Optimizing the Equality of Healthcare Services in Wuhan, China, Using a New Multimodal Two-Step Floating Catchment Area Model in Conjunction with the Hierarchical Maximal Accessibility Equality Model

by Pengfei Lu, Xiang Li, Lina Wang, Zhengbin Zhang, Danfei Zhang, Wenya Zhang and Yaru Li

ISPRS Int. J. Geo-Inf. 2025, 14(2), 93; https://doi.org/10.3390/ijgi14020093 - 19 Feb 2025

Viewed by 394

Abstract

The equity of medical services is crucial for the quality of life of a population and the sustainable development of cities. Current research on optimizing the maximal equity of medical facilities has the following limitations: (1) In the accessibility calculation models for multiple [...] Read more.

The equity of medical services is crucial for the quality of life of a population and the sustainable development of cities. Current research on optimizing the maximal equity of medical facilities has the following limitations: (1) In the accessibility calculation models for multiple transportation modes, the impact of factors such as public transport transfers and travel distance on the choice of transportation mode is often overlooked. (2) Existing spatial equity indicators are mostly derived from the overall study area, failing to fully consider the differences in population distribution and development gaps within different development zones inside the region. This study proposes a novel Incorporating Multiple Transportation Two-Step Floating Catchment Area (IMT-2SFCA) and a Hierarchical Theil-based Maximal Accessibility Equality model (HT-MAE) to optimize the equity of access to tuberculosis medical institutions in Wuhan. The findings reveal that, compared to single-mode transportation accessibility models, the multimodal accessibility model integrates the characteristics of four transportation modes, providing a more realistic reflection of residents’ access to medical services. The optimization results show a significant improvement in the equity of access to medical services across Wuhan and among different economic development zones, although the equity indicators in non-central urban areas have declined. The results of this study provide a theoretical basis and practical insights for alleviating the inequality of access to medical services across different urban layers. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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43 pages, 10533 KiB  

Open AccessArticle

Footprints of the Future: Cleaner and Faster Transportation with Shared E-Scooter Operational Models

by Ömer Kaya

ISPRS Int. J. Geo-Inf. 2025, 14(1), 16; https://doi.org/10.3390/ijgi14010016 - 2 Jan 2025

Cited by 1 | Viewed by 1185

Abstract

In recent years, shared e-scooters have become increasingly popular as a mode of transportation in urban areas. Shared e-scooters have emerged as a convenient and sustainable transportation option in urban areas, providing users with a flexible and efficient way to travel short distances [...] Read more.

In recent years, shared e-scooters have become increasingly popular as a mode of transportation in urban areas. Shared e-scooters have emerged as a convenient and sustainable transportation option in urban areas, providing users with a flexible and efficient way to travel short distances within a city. Many service providers and local municipalities are interested in implementing shared e-scooter operational models. However, determining which operating model to prefer and what the service areas will be is a significant problem. We aimed to solve the implementation of three different operational models, the site selection problem of station locations, and service areas for Erzurum, the metropolitan city in this study. As shared e-scooter is quite a new transportation mode; information collected to assess the operational models’ sustainability performance may be indeterminate and vague. In this study, the Geographic Information System (GIS)-based hybrid multi-criteria decision-making (MCDM) method is proposed for the solution of implementation, site selection, and service areas problems of three different shared e-scooter operational models. To this end, a four-step scientific and strategic solution approach is developed: (i) the identification and detailed explanation of 5 main and 24 sub-criteria, (ii) the weighting of criteria through the Analytical Hierarchical Process (AHP), Multi-Influencing Factor (MIF), and Best–Worst Method (BWM) in order to increase the sensitivity and robustness of the study, (iii) obtaining a suitability map for the solution of implementation, site selection, and service areas problems of operational models, and (iv) assigning shared e-scooter stations and analyzing their performance levels with COmplex PRoportional ASsessment (COPRAS). The results show that, in Erzurum, the central three districts are the most suitable for service areas. The paper’s solution methodology can help service providers and policymakers invest in sustainable shared e-scooter operational models, even in situations of high uncertainty. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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18 pages, 1805 KiB  

Open AccessArticle

DPSTCN: Dynamic Pattern-Aware Spatio-Temporal Convolutional Networks for Traffic Flow Forecasting

by Zeping Dou and Danhuai Guo

ISPRS Int. J. Geo-Inf. 2025, 14(1), 10; https://doi.org/10.3390/ijgi14010010 - 31 Dec 2024

Cited by 1 | Viewed by 804

Abstract

Accurate forecasting of multivariate traffic flow poses formidable challenges, primarily due to the ever-evolving spatio-temporal dynamics and intricate spatial heterogeneity, where the heterogeneity signifies that the correlations among locations are not just related to distance. However, few of the existing models are designed [...] Read more.

Accurate forecasting of multivariate traffic flow poses formidable challenges, primarily due to the ever-evolving spatio-temporal dynamics and intricate spatial heterogeneity, where the heterogeneity signifies that the correlations among locations are not just related to distance. However, few of the existing models are designed to fully and effectively integrate the above-mentioned features. To address these complexities head-on, this paper introduces a novel solution in the form of Dynamic Pattern-aware Spatio-Temporal Convolutional Networks (DPSTCN). Temporally, the model introduces a novel temporal module, containing a temporal convolutional network (TCN) enriched with an enhanced pattern-aware self-attention mechanism, adept at capturing temporal patterns, including local/global dependencies, dynamics, and periodicity. Spatially, the model constructs static and dynamic pattern-aware convolutions, leveraging geographical and area-functional information to effectively capture intricate spatial patterns, including dynamics and heterogeneity. Evaluations across four distinct traffic benchmark datasets consistently demonstrate the state-of-the-art capacity of our model compared to the existing eleven approaches, especially great improvements in RMSE (Root Mean Squared Error) value. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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26 pages, 10311 KiB  

Open AccessArticle

Multi-Scenario Simulation Evaluation and Strategic Zoning of Habitat Services Based on Habitat Quality and Ecological Network: A Case Study of Lanzhou City

by Jin Shi and Xianglong Tang

ISPRS Int. J. Geo-Inf. 2025, 14(1), 7; https://doi.org/10.3390/ijgi14010007 - 30 Dec 2024

Viewed by 838

Abstract

Land management strategies play a pivotal role in the sustainable development of a region. Integrating space syntax into the ecological–social perspective to assess habitat services and optimize multi-scenario simulations and evaluations is crucial for developing resilient strategies for the future. This study takes [...] Read more.

Land management strategies play a pivotal role in the sustainable development of a region. Integrating space syntax into the ecological–social perspective to assess habitat services and optimize multi-scenario simulations and evaluations is crucial for developing resilient strategies for the future. This study takes Lanzhou, a semi-arid region, as a case study, combining multi-model analysis to explore the relationship between habitat quality and spatial accessibility and to conduct habitat service zoning. The findings indicate that under four development scenarios, the ecological network generally shows a three-segment distribution. The factors that have the most significant impacts on cultivated land, forests, shrubs, construction land, and bare land are GDP, precipitation, temperature, population density, and NDVI, respectively. The ecological priority scenario features the most corridors, while the cultivated land protection scenario incurs the lowest construction costs. Across various analysis radii of space syntax, except for MED at a 6000 m radius, the ecological priority scenario exhibits excellent network accessibility. The coupling coordination degree of the four scenarios generally lies within a mild imbalance level, with a spatial distribution pattern characterized by “high in the west and low in the east”. Based on 10 types of habitat services, a priority management sequence for land and key governance towns was established, leading to the proposal of a “dual coordination” multi-center compact network layout model. This research not only enriches the theory of land ecology but also overcomes the shortcomings in land spatial planning, addresses the practical problems of land development transformation in Lanzhou, and offers new data support and ideas for the construction of ecological cities in semi-arid regions. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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20 pages, 4625 KiB  

Open AccessArticle

Delineations for Police Patrolling on Street Network Segments with p-Median Location Models

by Changho Lee, Hyun Kim, Yongwan Chun and Daniel A. Griffith

ISPRS Int. J. Geo-Inf. 2024, 13(11), 410; https://doi.org/10.3390/ijgi13110410 - 13 Nov 2024

Cited by 1 | Viewed by 1210

Abstract

Police patrolling intends to enhance traffic safety by mitigating the risks associated with vehicle crashes and accidents. From a view of operations, patrolling requires an effective distribution of resources and often involves area delineations for this distribution purpose. Given constraints such as budget [...] Read more.

Police patrolling intends to enhance traffic safety by mitigating the risks associated with vehicle crashes and accidents. From a view of operations, patrolling requires an effective distribution of resources and often involves area delineations for this distribution purpose. Given constraints such as budget and human resources for traffic safety, delineating geographic areas optimally for police patrol areas is an important agenda item. This paper considers two p-median location models using segments on a street network as observational units on which traffic issues such as vehicle crashes occur. It also uses two weight sets to construct an enhanced delineation of police patrol areas in the City of Plano, Texas. The first model for the standard p-median formulation gives attention to the cumulative number of motor vehicle crashes from 2011 to 2021 on the major transportation networks in Plano. The second model, an extension of this first p-median one, uses balancing constraints to achieve balanced spatial coverage across patrol areas. These two models are also solved with network kernel density count estimates (NKDCE) instead of crash counts. These smoothed densities on a network enable consideration of uncertainty affiliated with this aggregation. The analysis results of this paper suggest that the p-median models provide effective specifications, including their capability to define patrol areas that encompass the entire study region while minimizing distance costs. The inclusion of balancing constraints ensures a more equitable distribution of workloads among patrol areas, improving overall efficiency. Additionally, the model with NKDCE results in an improved workload balance among delineated areas for police patrolling activities, thus supporting more informed spatial decision-making processes for public safety. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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27 pages, 10005 KiB  

Open AccessArticle

The Effect of War on Spatial Differentiation of Real Estate Values and Urban Disorder in the Damascus Metropolitan Area

by Mounir Azzam, Valerie Graw and Andreas Rienow

Urban Sci. 2024, 8(4), 183; https://doi.org/10.3390/urbansci8040183 - 22 Oct 2024

Viewed by 1967

Abstract

The Syrian war, which commenced in 2011, transformed the Damascus real estate market due to heightened insecurity and tenure disputes. Using the hedonic price models, including 2411 housing transactions over the period 2010–2022, this study aims to understand the spatial dynamics of the [...] Read more.

The Syrian war, which commenced in 2011, transformed the Damascus real estate market due to heightened insecurity and tenure disputes. Using the hedonic price models, including 2411 housing transactions over the period 2010–2022, this study aims to understand the spatial dynamics of the real estate market in wartime. Our findings indicate that war variables have had a significant impact on the differentiation of property prices. Notably, property attributes have a more substantial impact on real estate values than district location, with severely damaged buildings in Damascus City resulting in an 89% decline in prices, while prices in Rural Damascus districts have decreased by 50%. Additionally, this study examines the urban texture of Damascus using correlation and homogeneity statistics derived from the gray-level co-occurrence matrix obtained from Google Earth Engine. Our findings show that correlations were highly differentiated, particularly among Rural Damascus districts, with a total decline of 87.2%. While homogeneity values decreased overall between 2015 and 2019, they improved slightly after 2019. This study guides decision makers in mitigating severe property value variations across war-affected urban areas by fostering spatial justice in property rights and promoting balanced investment and sustainable real estate development during the post-war recovery phase. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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19 pages, 4338 KiB  

Open AccessArticle

Discovering Electric Vehicle Charging Locations Based on Clustering Techniques Applied to Vehicular Mobility Datasets

by Elmer Magsino, Francis Miguel M. Espiritu and Kerwin D. Go

ISPRS Int. J. Geo-Inf. 2024, 13(10), 368; https://doi.org/10.3390/ijgi13100368 - 18 Oct 2024

Cited by 1 | Viewed by 1479

Abstract

With the proliferation of vehicular mobility traces because of inexpensive on-board sensors and smartphones, utilizing them to further understand road movements have become easily accessible. These huge numbers of vehicular traces can be utilized to determine where to enhance road infrastructures such as [...] Read more.

With the proliferation of vehicular mobility traces because of inexpensive on-board sensors and smartphones, utilizing them to further understand road movements have become easily accessible. These huge numbers of vehicular traces can be utilized to determine where to enhance road infrastructures such as the deployment of electric vehicle (EV) charging stations. As more EVs are plying today’s roads, the driving anxiety is minimized with the presence of sufficient charging stations. By correctly extracting the various transportation parameters from a given dataset, one can design an adequate and adaptive EV charging network that can provide comfort and convenience for the movement of people and goods from one point to another. In this study, we determined the possible EV charging station locations based on an urban city’s vehicular capacity distribution obtained from taxi and ride-hailing mobility GPS traces. To achieve this, we first transformed the dynamic vehicular environment based on vehicular capacity into its equivalent urban single snapshot. We then obtained the various traffic zone distributions by initially utilizing k-means clustering to allow flexibility in the total number of wanted traffic zones in each dataset. In each traffic zone, iterative clustering techniques employing Density-based Spatial Clustering of Applications with Noise (DBSCAN) or clustering by fast search and find of density peaks (CFS) revealed various area separation where EV chargers were needed. Finally, to find the exact location of the EV charging station, we last ran k-means to locate centroids, depending on the constraint on how many EV chargers were needed. Extensive simulations revealed the strengths and weaknesses of the clustering methods when applied to our datasets. We utilized the silhouette and Calinski–Harabasz indices to measure the validity of cluster formations. We also measured the inter-station distances to understand the closeness of the locations of EV chargers. Our study shows how CFS + k-means clustering techniques are able to pinpoint EV charger locations. However, when utilizing DBSCAN initially, the results did not present any notable outcome. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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22 pages, 22557 KiB  

Open AccessArticle

Ecological Design for Urban Regeneration in Industrial Metropolitan Areas: The Santa Cruz Refinery Case

by Juan Diego López-Arquillo, Cano Ciborro Víctor, Oliveira Cristiana, Esteban Penelas José Luis, Domouso de Alba Francisco and Arteaga Orozco Mariana Bernice

Urban Sci. 2024, 8(3), 114; https://doi.org/10.3390/urbansci8030114 - 14 Aug 2024

Viewed by 1611

Abstract

Ecological design is crucial in shaping contemporary, resilient, and livable cities. The Santa Cruz de Tenerife Refinery, a prominent landmark in the Mid-Atlantic, serves as an exemplary case study for understanding advanced metropolitan processes and integrating trans-scalar, transdisciplinary, and nature-based solutions (NBS) practices [...] Read more.

Ecological design is crucial in shaping contemporary, resilient, and livable cities. The Santa Cruz de Tenerife Refinery, a prominent landmark in the Mid-Atlantic, serves as an exemplary case study for understanding advanced metropolitan processes and integrating trans-scalar, transdisciplinary, and nature-based solutions (NBS) practices into urban contexts. This article explores the challenges of transforming obsolete industrial areas, including the refinery’s decommissioning process, its port, and industrial heritage value, and their relationship with the sea, into vibrant urban cores. It examines innovative strategies for land use, decontamination, and urban resilience, which are vital for fostering adaptability and recovery from natural and anthropogenic disasters. By emphasizing the refinery’s connection to Santa Cruz de Tenerife and its metropolitan area, as well as its coastal interface, this study proposes a comprehensive methodology to assess the territorial impacts of urban processes and guide project decisions toward enhancing the quality of life for the region’s residents. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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21 pages, 5848 KiB  

Open AccessArticle

What Factors Revitalize the Street Vitality of Old Cities? A Case Study in Nanjing, China

by Yan Zheng, Ruhai Ye, Xiaojun Hong, Yiming Tao and Zherui Li

ISPRS Int. J. Geo-Inf. 2024, 13(8), 282; https://doi.org/10.3390/ijgi13080282 - 12 Aug 2024

Cited by 2 | Viewed by 1583

Abstract

Urban street vitality has been a perennial focus within the domain of urban planning. This study examined spatial patterns of street vitality in the old city of Nanjing during working days and weekends using real-time user datasets (RTUDs). A spatial autoregressive model (SAM) [...] Read more.

Urban street vitality has been a perennial focus within the domain of urban planning. This study examined spatial patterns of street vitality in the old city of Nanjing during working days and weekends using real-time user datasets (RTUDs). A spatial autoregressive model (SAM) and a multiscale geographically weighted regression (MGWR) model were employed to quantitatively assess the impact of various factors on street vitality and their spatial heterogeneity. This study revealed the following: (1) the distribution of street vitality in the old city of Nanjing exhibited a structure centered around Xinjiekou, with greater regularity and predictability in street vitality on working days than on weekends; (2) eight variables, such as traffic location, road density, and functional density, are positively associated with street vitality, whereas the green view index is negatively associated with street vitality, and commercial location benefits street vitality at weekends but detracts from street vitality on working days; and (3) the influence of variables such as traffic location and functional density on street vitality is contingent on their spatial position. Based on these results, this study provides new strategies to enhance the street vitality of old cities. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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26 pages, 5896 KiB  

Open AccessArticle

Urban Parks in Novi Sad (Serbia)—Insights from Landscape Architecture Students

by Milena Lakićević, Nebojša Dedović, Marco Marto and Keith M. Reynolds

Urban Sci. 2024, 8(3), 99; https://doi.org/10.3390/urbansci8030099 - 26 Jul 2024

Viewed by 1701

Abstract

Urban parks are vital components of city ecosystems, enhancing biodiversity, climate resilience, air and water quality, health, socialization, and economic benefits for citizens in urban areas. This paper examines urban parks in Novi Sad by gathering opinions on their qualities and functions through [...] Read more.

Urban parks are vital components of city ecosystems, enhancing biodiversity, climate resilience, air and water quality, health, socialization, and economic benefits for citizens in urban areas. This paper examines urban parks in Novi Sad by gathering opinions on their qualities and functions through a questionnaire. The respondents were students enrolled in the landscape architecture course at the University of Novi Sad. To analyze their responses, multivariate statistical analysis techniques, including ANOVA, MANOVA, and contingency tables, were applied. The results highlight the primary reasons for visiting urban parks in general, as well as specific parks in Novi Sad. The paper offers insights into visitor behavior, including the frequency and length of their stays, etc., and provides an assessment of the parks’ educational functions, which were expected to be highly relevant for the respondent group. The results can be relevant for further urban park development and serve as a starting point for applying multi-criteria (MC) analysis. Specifically, the results can be used to define a set of criteria, goals, and other essential elements necessary for conducting Analytic Hierarchy Processes or similar MC analysis methods. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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18 pages, 9889 KiB  

Open AccessArticle

Urban Planning with Rational Green Infrastructure Placement Using a Critical Area Detection Method

by Herath Mudiyanselage Malhamige Sonali Dinesha Herath, Takeshi Fujino and Mudalige Don Hiranya Jayasanka Senavirathna

Geomatics 2024, 4(3), 253-270; https://doi.org/10.3390/geomatics4030014 - 5 Jul 2024

Viewed by 1955

Abstract

In an era of intense urban development and climate extremes, green infrastructure (GI) has become crucial for creating sustainable, livable, and resilient cities. However, the efficacy of GI is frequently undermined by haphazard implementation and resource misallocation that disregards appropriate spatial scales. This [...] Read more.

In an era of intense urban development and climate extremes, green infrastructure (GI) has become crucial for creating sustainable, livable, and resilient cities. However, the efficacy of GI is frequently undermined by haphazard implementation and resource misallocation that disregards appropriate spatial scales. This study develops a geographic information system (GIS)-based critical area detection model (CADM) to identify priority areas for the strategic placement of GI, incorporating four main indices—spatial form, green cover, gray cover, and land use change—and utilizing the digital elevation model (DEM), normalized difference vegetation index (NDVI), urban density index (UDI), and up-to-date land use data. By employing the developed method, the study successfully locates priority zones for GI implementation in Saitama City, Japan, effectively pinpointing areas that require immediate attention. This approach not only guarantees efficient resource allocation and maximizes the multifunctional benefits of GI but also highlights the importance of a flexible, all-encompassing GI network to address urbanization and environmental challenges. The findings offer policymakers a powerful tool with which to optimize GI placement, enhancing urban resilience and supporting sustainable development. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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23 pages, 5816 KiB  

Open AccessArticle

Spatial Nonlinear Effects of Street Vitality Constrained by Construction Intensity and Functional Diversity—A Case Study from the Streets of Shenzhen

by Jilong Li, Niuniu Kong, Shiping Lin, Jie Zeng, Yilin Ke and Jiacheng Chen

ISPRS Int. J. Geo-Inf. 2024, 13(7), 238; https://doi.org/10.3390/ijgi13070238 - 2 Jul 2024

Cited by 2 | Viewed by 1696

Abstract

As an important part of urban vitality, street vitality is an external manifestation of street economic prosperity and is affected by the built environment and the surrounding street vitality. However, existing research on the formation mechanism of street vitality focuses only on the [...] Read more.

As an important part of urban vitality, street vitality is an external manifestation of street economic prosperity and is affected by the built environment and the surrounding street vitality. However, existing research on the formation mechanism of street vitality focuses only on the built environment itself, ignoring the spatial spillover effect on street vitality. This study uses 5290 street segments in Shenzhen as examples. Utilizing geospatial and other multisource big data, this study creates spatial weight matrices at varying distances based on different living circle ranges. By combining the panel threshold model (PTM) and the spatial panel Durbin model (SPDM), this study constructs a spatial autoregressive threshold model to explore the spatial nonlinear effects of street vitality, considering various spatial weight matrices and thresholds of construction intensity and functional diversity. Our results show the following: (1) Street vitality exhibits significant spatial spillover effects, which gradually weaken as the living circle range expands (Moran indices are 0.178***, 0.160***, and 0.145*** for the 500 m, 1000 m, and 1500 m spatial weight matrices, respectively). (2) Construction intensity has a threshold, which is 0.1466 under spatial matrices of different distances. Functional diversity has two thresholds: 0.6832 and 2.2065 for the 500 m spatial weight matrix, and 0.6832 and 1.4325 for the 1000 m matrices, and 0.6832 and 1.2724 for 1500 m matrices. (3) As an international metropolis, street accessibility in Shenzhen has a significant and strong positive impact on its street vitality. This conclusion provides stakeholders with spatial patterns that influence street vitality, offering a theoretical foundation to further break down barriers to street vitality. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

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