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Recent Progress in RS&GIS-Based Urban Planning
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Recent Progress in RS&GIS-Based Urban Planning

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land Planning and Landscape Architecture".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 10755

Special Issue Editors

Dr. Jing Xie

E-Mail Website
Guest Editor
School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
Interests: natural and urban environmental gradients; urban local climate; urban analytics; environmental factors' modeling; phenology and productivity of vegetation; land use land cover; climate change
Dr. Yeran Sun

E-Mail Website
Co-Guest Editor
Department of Geography, University of Lincoln, Lincoln LN6 7TS, UK
Interests: remote sensing AI; GeoAI; quantitative human geography; sensing mobility and activity; geospatial big data analytics
Special Issues, Collections and Topics in MDPI journals
Dr. Xiao Liu

E-Mail Website
Co-Guest Editor
School of Architecture, South China University of Technology, Guangzhou 510641, China
Interests: green building; green campus; carbon-neutral building; healthy building; urban heat mitigation and adaptation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Within the context of the mobility of populations and urban development, feasible and accessible urban planning has become increasingly important, as well as for achieving the 2030 Agenda for Sustainable Development Goals (SDGs). The current problem of urban planning is that planners rely extensively on their subjective and historic experience, which makes urban planning inefficient, chaotic in zoning, poor in practicality, and unsustainable.

As an emerging information technology science in recent years, Remote Sensing (RS) and Geographic Information System (GIS), through the database platform, information service, and 3D modelling and monitoring, provides more scientific and quantitative analysis methods for urban planning. The Special Issue aims to combine geographic information systems and geospatial data, using technologies such as remote sensing, satellite imagery, and airborne lidar to build geographic information analysis models, and to provide decision-making tools for the players involved in urban planning.

We encourage researchers to submit their original research papers as well as technical or review articles to this Special Issue, focusing on the application and prospects of RS and GIS in urban planning, such as:

  • Application of geographic information systems (GIS);
  • Big data analytics for urban planning;
  • Green spaces and sustainable urban planning;
  • Urban planning with remote sensing;
  • Landscape and urban planning;
  • Urban planning and smart city;
  • Decision support tools in urban planning;
  • Urban planning and land management;
  • Sustainable urban-planning techniques.

We look forward to receiving your original research articles and reviews.

Dr. Jing Xie
Guest Editor

Dr. Yeran Sun
Dr. Xiao Liu
Co-Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Land is an international peer-reviewed open access monthly 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 2600 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
  • geographic information systems
  • remote sensing
  • big data
  • land management
  • smart city
  • green spaces

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (11 papers)

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Research

34 pages, 52274 KiB  
Article
Classification and Distribution of Traditional Grass-Roofed Dwellings in China Based on Deep Learning
by Jin Tao, Yuxin Zeng, Xiaolan Zhuo, Zhibo Wang, Jihang Xu and Peng Ren
Land 2024, 13(10), 1595; https://doi.org/10.3390/land13101595 - 30 Sep 2024
Viewed by 232
Abstract
Traditional grass-roofed dwellings are important components of Chinese vernacular architecture. Building a comprehensive nationwide database of traditional grass-roofed dwellings is crucial for the inherence of this cultural heritage and its traditional ecological technologies. This study proposes classifying traditional Chinese grass-roofed dwellings into three [...] Read more.
Traditional grass-roofed dwellings are important components of Chinese vernacular architecture. Building a comprehensive nationwide database of traditional grass-roofed dwellings is crucial for the inherence of this cultural heritage and its traditional ecological technologies. This study proposes classifying traditional Chinese grass-roofed dwellings into three types according to recognizable appearance features. Based on the YOLOv8 deep learning framework, a recognition model is constructed to recognize and spatially locate various grass-roofed dwellings from the image dataset on a county-level. Further, by conducting spatial overlap analysis with a variety of natural and socio-environmental factors on ArcGIS, their influences on the distribution pattern of traditional grass-roofed dwellings were examined. The study findings are as follows: (1) Traditional grass-roofed dwellings are concentrated on the southeast side of the Hu Line with different distribution patterns according to their types. (2) The natural environment influences the original construction and distribution of traditional grass-roofed dwellings in terms of the growth of grass resources and the ecological adaptability of grass material. (3) The development of economy, population, and urbanization pose challenges to the retention of grass-roofed dwellings. This research provides useful references for the precise preservation of various grass-roofed dwellings and introduced a novel approach for the classification of traditional buildings. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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16 pages, 6087 KiB  
Article
Land Use Thematic Maps Recommendation Based on Pan-Map Visualization Dimension Theory
by Yebin Chen, Zhicheng Shi, Yaxing Li, Dezhi Han, Minmin Li and Zhigang Zhao
Land 2024, 13(9), 1389; https://doi.org/10.3390/land13091389 - 29 Aug 2024
Viewed by 353
Abstract
In the era of information and communication technology (ICT), the advancement of science and technology has led to a trend of diversification in map representation. However, the lack of professional knowledge means that there is still a challenge in determining the appropriate type [...] Read more.
In the era of information and communication technology (ICT), the advancement of science and technology has led to a trend of diversification in map representation. However, the lack of professional knowledge means that there is still a challenge in determining the appropriate type of thematic map for land use expression. To address this issue, this paper proposes a knowledge recommendation method for land use thematic maps based on the theory of visualization dimensions. Firstly, we establish a knowledge ontology of land use thematic maps centered on spatial data, data characteristics, visualization dimensions, thematic map forms, and application scenarios. A land use thematic map knowledge graph is constructed through knowledge extraction and storage operations. Secondly, knowledge embedding is performed on the knowledge graph to enable the knowledge-based expression of map visualization elements. Finally, based on the knowledge elements of land use thematic expression, a similarity calculation model is established to calculate the similarity between input data and the spatial data characteristics, visualization dimensions, and application scenarios within the knowledge graph, deriving a comprehensive similarity result to achieve precise recommendation for land use thematic map forms. The results show that the method can provide a more accurate visualization reference for the selection of land use themes, meeting the diversified needs of land use thematic expression to a certain extent. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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19 pages, 10217 KiB  
Article
Progress in Remote Sensing and GIS-Based FDI Research Based on Quantitative and Qualitative Analysis
by Zifeng Li
Land 2024, 13(8), 1313; https://doi.org/10.3390/land13081313 - 19 Aug 2024
Viewed by 729
Abstract
Foreign direct investment (FDI) by transnational companies (TNCs) is the primary indicator of urban globalization. The initial publication on the topic of remote sensing and geographic information system-based urban globalization research was published in 1981. However, the number of publications on this topic [...] Read more.
Foreign direct investment (FDI) by transnational companies (TNCs) is the primary indicator of urban globalization. The initial publication on the topic of remote sensing and geographic information system-based urban globalization research was published in 1981. However, the number of publications on this topic remains relatively limited. Despite some advances in the field in recent decades, there is currently no comprehensive review of related research, and it is not clear how the different perspectives and views have been developed. Furthermore, previous literature reviews on the utilization of remote sensing and GIS technology in urban development have predominantly employed quantitative methodologies, which has resulted in a paucity of qualitative analysis. In order to address these shortcomings, this paper employs a mixed-methods approach, integrating quantitative and qualitative analyses. This entails the utilization of a combination of the scientometric method and a qualitative literature review method. The findings are as follows: (1) The number of publications is still relatively limited, and research in this area is still in its infancy. (2) Some of the articles are evidently interdisciplinary in nature. (3) Progress has been made in terms of geographic visualization of FDI, macro-environmental research at different scales, global value chains, the micro-geography of TNCs, and globalization of the geo-information industry. (4) The spatial and temporal development pattern, location, and accessibility of FDI have constituted a significant area of research interest in the past. Similarly, the relationships between FDI and regional development, urban growth, land use, and environmental change have emerged as prominent research directions. China’s Belt and Road Initiative is an emerging popular topic. (5) In recent years, there has been a notable increase in the number of papers employing multi-source data and multi-method approaches. (6) The extent of research collaborations between countries is relatively limited, with the majority of such collaborations occurring within the past five years. Finally, based on these research findings, this paper suggests future research directions. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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21 pages, 7391 KiB  
Article
Assessment of Urban Spatial Integration Using Human Settlement Environmental Geographic Dataset: A Case Study in the Guangzhou–Foshan Metropolitan Area
by Rui Chen, Siyu Zhou, Shuyuan Liu, Zifeng Li and Jing Xie
Land 2024, 13(8), 1262; https://doi.org/10.3390/land13081262 - 11 Aug 2024
Viewed by 764
Abstract
Urbanization is an important process in China’s urban development, significantly contributing to resource allocation and the cooperative development of neighboring cities. In recent years, remote-sensing technology has emerged as a powerful tool in urbanization research. However, the disparity in development between urban and [...] Read more.
Urbanization is an important process in China’s urban development, significantly contributing to resource allocation and the cooperative development of neighboring cities. In recent years, remote-sensing technology has emerged as a powerful tool in urbanization research. However, the disparity in development between urban and rural areas poses challenges in evaluating the degree of urbanization within a region. This paper addresses this issue by using LCZ (Local Climate Zone) data to provide a unified framework for analyzing a human settlement environmental geographic dataset. This study focuses on the spatial development and transformation of the Guangzhou–Foshan urbanization from 2000 to 2020. The LCZ data offer a suitable framework for examining urban–rural gradients, facilitating the analysis of spatial characteristics under varying development conditions. This unified framework enables a comprehensive analysis of the spatiotemporal characteristics of urban spatial integration. The results show that the analysis of the Guangzhou–Foshan metropolitan area reveals that the region has maintained a “core–edge” spatial structure over the past 20 years. The development rate has decelerated following policy changes in 2010, with the adjacent area experiencing significantly slower development compared to the overall study area. LCZ data are effective for comparative analysis of internal spatial development within urban areas, offering a novel approach to studying spatial integration amid urban development. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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20 pages, 6983 KiB  
Article
Identification of the Spatial Structure of Urban Polycentres Based on the Dual Perspective of Population Distribution and Population Mobility
by Rongrong Zhang, Ming Li, Xiao Zhang, Yuanyuan Guo, Yonghe Li, Qi Gao and Song Liu
Land 2024, 13(8), 1159; https://doi.org/10.3390/land13081159 - 29 Jul 2024
Viewed by 465
Abstract
The accelerated growth of urban areas has resulted in substantial alterations to the spatial structure of these settlements. The accurate identification of the multi-centre spatial structure is a fundamental prerequisite for the assessment of urban spatial development and the optimisation of urban space. [...] Read more.
The accelerated growth of urban areas has resulted in substantial alterations to the spatial structure of these settlements. The accurate identification of the multi-centre spatial structure is a fundamental prerequisite for the assessment of urban spatial development and the optimisation of urban space. Accordingly, this study aimed to identify the multi-centre spatial structure of cities through a novel approach of data fusion based on night-time lighting data, LandScan data, and population heat data. Furthermore, this study compared the differential effects of population distribution and population mobility in identifying urban spatial structures. The empirical research results for Zhengzhou City demonstrate that the accuracy of using LandScan data fusion to identify multi-centre spatial structures was 0.7463, while the accuracy of using night-time light data fusion to identify urban spatial structures through population mobility reached 0.8235. This suggests that, in the context of increasing population mobility and economic activity, the integration of population mobility data may have a significant impact on the accuracy of urban spatial research. Moreover, this study places a dual focus on population distribution and population mobility and a new method of data integration for urban spatial research. These are of considerable practical value in facilitating spatial optimisation and the coordinated development of cities. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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22 pages, 3367 KiB  
Article
Evaluating Human Needs: A Study on the Spatial Justice of Medical Facility Services in Social Housing Communities in Guangzhou
by Ruixia Chao, Desheng Xue and Benshuo Wang
Land 2024, 13(7), 1109; https://doi.org/10.3390/land13071109 - 22 Jul 2024
Cited by 1 | Viewed by 625
Abstract
Mainstream empirical studies on the spatial justice of medical facilities focus on equal accessibility or resource availability based on population scale, overlooking critiques that emphasize the importance of assessing inequality and the multidimensionality of human needs. However, access to medical care, particularly for [...] Read more.
Mainstream empirical studies on the spatial justice of medical facilities focus on equal accessibility or resource availability based on population scale, overlooking critiques that emphasize the importance of assessing inequality and the multidimensionality of human needs. However, access to medical care, particularly for vulnerable groups in social housing, often demands a higher level of consideration. Evaluating whether people can access the facilities they demand and expect is crucial for improving living standards. This study categorizes medical facilities into primary healthcare and hospital facilities based on their service grade, and integrates survey-based satisfaction into a spatial analysis of cost–distance-based accessibility and gravity-2SFCA-based availability. Analysis reveals that satisfaction primarily correlates with two factors: the distance to primary healthcare and the ease of reaching hospital facilities. While low accessibility to primary healthcare contributes to the evident distribution injustice of medical resources, satisfaction with service quality and scope is more strongly associated with the ease of reaching hospitals. To reduce injustice in social housing, specific remedies are needed to improve the difficult conditions for accessing primary healthcare faced by communities such as Guangdan, Likang, and Jinshazhou. Moreover, improving the easiness of reaching hospital facilities may significantly enhance the resident satisfaction with the level of medical service provided. Findings obtained in this research may not only enlighten Guangzhou’s urban planning, but may also be noteworthy for developing livable cities, which people anticipated. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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24 pages, 8725 KiB  
Article
Urban Spatial Image Acquisition and Examination Based on Geographic Big Data
by Xiaowen Zhou, Hongwei Li, Jian Xu and Qingzhen Sun
Land 2024, 13(6), 774; https://doi.org/10.3390/land13060774 - 30 May 2024
Viewed by 577
Abstract
This study proposes a two-dimensional analytical framework based on urban spatial form and spatial service perspectives, utilizing data on buildings and points of interest (POIs). It integrates fishnet analysis, kernel density analysis, the categorization of POI functionalities, and mixture calculations to enhance our [...] Read more.
This study proposes a two-dimensional analytical framework based on urban spatial form and spatial service perspectives, utilizing data on buildings and points of interest (POIs). It integrates fishnet analysis, kernel density analysis, the categorization of POI functionalities, and mixture calculations to enhance our understanding of urban spatial form and function. Taking the main urban area of Zhengzhou as an example, this study identifies image elements that can describe urban spatial characteristics through the results of two-dimensional analysis and enriches the city image in the form of a portrait. The experimental findings demonstrate that the elements of the annular layer, functional landmarks, ring line boundaries, and special districts can fully convey the spatial picture of Zhengzhou City. The performance of the four types of image elements has a high degree of matching with the content of the urban spatial planning of Zhengzhou City, which can effectively identify the urban multi-center structure and development pattern. This paper explores and tests the development status of the city from a new perspective, which can provide an effective reference for the future planning and sustainable development of the city. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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25 pages, 6483 KiB  
Article
Assessment Methodology for Physical Vulnerability of Vernacular Architecture in Areas Affected by Depopulation: The Case of Comunidad Valenciana, Spain
by Eva Tortajada Montalvá, Camilla Mileto and Fernando Vegas López-Manzanares
Land 2024, 13(5), 695; https://doi.org/10.3390/land13050695 - 15 May 2024
Viewed by 847
Abstract
The intensity with which the phenomenon of depopulation has affected rural municipalities in Spain between 1950 and 2022 has led to a loss in the intergenerational transmission of traditional knowledge, values and customs. Sociocultural loss entails associated physical risks: the abandonment, demolition, and [...] Read more.
The intensity with which the phenomenon of depopulation has affected rural municipalities in Spain between 1950 and 2022 has led to a loss in the intergenerational transmission of traditional knowledge, values and customs. Sociocultural loss entails associated physical risks: the abandonment, demolition, and loss of vernacular architecture. This research analyzes the evolution of this type of architecture in a period of acute depopulation and its current state of conservation. A total of 180 case studies in the region of Comunidad Valenciana are analyzed through four factors affecting the physical vulnerability of dwellings: year of construction, state of conservation, type of use, and a combination of all three. Data management software is used to combine all the information and produce the results in a tabular and graphical format, while the Geographic Information System is used to draw up risk maps showing the results. These results are then divided into analysis groups created according to the degree of depopulation observed in the years mentioned. This made it possible to identify the relationship between depopulation and the conservation of vernacular architecture, showing the risk level for each case study, and thus creating an analysis methodology applicable in other territories affected by depopulation at a national and international level. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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19 pages, 21675 KiB  
Article
Unraveling the Dynamic Relationship between Neighborhood Deprivation and Walkability over Time: A Machine Learning Approach
by Qian Wang, Guie Li and Min Weng
Land 2024, 13(5), 667; https://doi.org/10.3390/land13050667 - 12 May 2024
Viewed by 1065
Abstract
Creating a walkable environment is an essential step toward the 2030 Sustainable Development Goals. Nevertheless, not all people can enjoy a walkable environment, and neighborhoods with different socioeconomic status are found to vary greatly with walkability. Former studies have typically unraveled the relationship [...] Read more.
Creating a walkable environment is an essential step toward the 2030 Sustainable Development Goals. Nevertheless, not all people can enjoy a walkable environment, and neighborhoods with different socioeconomic status are found to vary greatly with walkability. Former studies have typically unraveled the relationship between neighborhood deprivation and walkability from a temporally static perspective and the produced estimations to a point-in-time snapshot were believed to incorporate great uncertainties. The ways in which neighborhood walkability changes over time in association with deprivation remain unclear. Using the case of the Hangzhou metropolitan area, we first measured the neighborhood walkability from 2016 to 2018 by calculating a set of revised walk scores. Further, we applied a machine learning algorithm, the kernel-based regularized least squares regression in particular, to unravel how neighborhood walkability changes in relation to deprivation over time. The results not only capture the nonlinearity in the relationship between neighborhood deprivation and walkability over time, but also highlight the marginal effects of each neighborhood deprivation indicator. Additionally, comparisons of the outputs between the machine learning algorithm and OLS regression illustrated that the machine learning approach did tell a different story and should contribute to remedying the contradictory conclusions in earlier studies. This paper is believed to renew the understanding of social inequalities in walkability by bringing the significance of temporal dynamics and structural interdependences to the fore. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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24 pages, 7024 KiB  
Article
Researching Tourism Space in China’s Great Bay Area: Spatial Pattern, Driving Forces and Its Coupling with Economy and Population
by Lingfeng Li and Quan Gao
Land 2023, 12(10), 1878; https://doi.org/10.3390/land12101878 - 6 Oct 2023
Cited by 3 | Viewed by 1263
Abstract
Analysis of the spatial patterns and dynamics of tourism services and facilities is crucial for tourism and land use planning. However, most studies in the spatial analysis of tourism rely on the city- or regional-level data; limited research has used POI (point of [...] Read more.
Analysis of the spatial patterns and dynamics of tourism services and facilities is crucial for tourism and land use planning. However, most studies in the spatial analysis of tourism rely on the city- or regional-level data; limited research has used POI (point of interest) data to accurately uncover the spatial distribution of tourism, especially its interactive and coupling relationship with the local economy and population. Based on POI data, this paper, therefore, investigates the spatial patterns and driving forces of tourism services distribution and how tourism space is coupled with the local economy and population in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) of China. The results show the following: (1) Different categories of tourism services (catering, shopping, scenic spots, leisure, and sports) exhibit diverse spatial patterns and agglomerations, but they tend to align with the variables of economic level and population in a grid of 1 km2. (2) The spatial econometric models further reveal that population density, transportation, and hospitality facilities are positively correlated with the spatial distribution of tourism services, but GDP in a grid of 1 km2 shows a weak negative correlation with the POI of tourism services, which may be attributed to the incoordination between GDP and tourism in some areas. (3) The analysis of coupling degree further identifies the areas where tourism services have good interaction/coupling with the local GDP and population density, such that these areas can be viewed as hotspots suitable for tourism promotion. This paper thus offers meaningful policy implications by calling for an optimization of the coupling of tourism services with local social–economic factors in the GBA. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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20 pages, 17527 KiB  
Article
Evaluation of Urban Green Space Supply and Demand Based on Mobile Signal Data: Taking the Central Area of Shenyang City as an Example
by Yukuan Dong, Xi Chen, Dongyang Lv and Qiushi Wang
Land 2023, 12(9), 1742; https://doi.org/10.3390/land12091742 - 7 Sep 2023
Cited by 5 | Viewed by 2280
Abstract
The degree of coordination between the supply and demand for urban green spaces serves as a vital metric for evaluating urban ecological development and the well-being of residents. An essential principle in assessing this coordination is the precise quantification of both the demand [...] Read more.
The degree of coordination between the supply and demand for urban green spaces serves as a vital metric for evaluating urban ecological development and the well-being of residents. An essential principle in assessing this coordination is the precise quantification of both the demand and supply of green spaces, as well as the differential representation of their spatiotemporal structures. This study utilizes the entropy weight method (EWM) and principal component analysis (PCA) to comprehensively measure supply indicators for green space quantity and quality in the central urban area of Shenyang, China. To establish reliable and quantifiable demand indicators, mobile signaling spatial-temporal data are corrected by incorporating static population cross-sectional data. The Gaussian two-step floating catchment area method (Ga2SFCA) is employed to calculate the accessibility of green spaces in each community with ArcGIS 10.2 software, while the Gini coefficient is utilized to assess the equity of green space distribution within the study area. This study employs location entropy to determine the levels of supply and demand for green spaces in each subdistrict. Furthermore, the priority of community-scale green space regulation is accurately determined by balancing vulnerable areas of green space supply and replenishing green space resources for the ageing population. The findings suggest a Gini coefficient of 0.58 for the supply and demand of green spaces in Shenyang’s central metropolitan region, indicating a relatively low level of equalization in overall green space allocation. Based on location entropy, the classification of supply and demand at the street level yields the following outcomes: balanced areas comprise 21.98%, imbalanced areas account for 26.37%, and highly imbalanced regions represent 51.65%. After eliminating the balanced regions, the distribution of the elderly population is factored in, highlighting the spatial distribution and proportions of communities with distinct regulatory priorities: Level 1 (S1) constitutes 7.4%, Level 2 (S2) accounts for 60.9%, and Level 3 (S3) represents 31.7%. Notably, the communities in the S1 category exhibit spatial distribution characteristics of aggregation within the inner ring and the northern parts of the third ring. This precise identification of areas requiring urgent regulation and the spatial distribution of typical communities can provide reliable suggestions for prioritizing green space planning in an age-friendly city. Full article
(This article belongs to the Special Issue Recent Progress in RS&GIS-Based Urban Planning)
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