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17 pages, 5460 KiB

Open AccessArticle

Factors Influencing the Efficiency of Demand-Responsive Transport Services in Rural Areas: A GIS-Based Method for Optimising and Evaluating Potential Services

by Carlos Tejero-Beteta, Amparo Moyano and Santos Sánchez-Cambronero

ISPRS Int. J. Geo-Inf. 2024, 13(8), 275; https://doi.org/10.3390/ijgi13080275 - 1 Aug 2024

Viewed by 886

Abstract

Demand-responsive transport (DRT) could be an alternative for extending the accessibility of high-speed rail (HSR) servicing cities in rural environments, where fixed public transport does not provide efficient services. This paper proposes a method to analyse the factors that influence the implementation of [...] Read more.

Demand-responsive transport (DRT) could be an alternative for extending the accessibility of high-speed rail (HSR) servicing cities in rural environments, where fixed public transport does not provide efficient services. This paper proposes a method to analyse the factors that influence the implementation of DRT systems for inter-urban mobility, connecting and integrating towns in rural areas. Methodologically, a vehicle routing problem analysis in a GIS-based environment is applied to a theoretical case study to evaluate the factors that influence DRT efficiency in different scenarios, considering the specific singularities of this kind of inter-urban long-distance mobility. The results suggest the optimal DRT solutions in these rural contexts to be those that, after adjusting the fleet to specific demands, use low-capacity vehicles, which are much better adapted to the geography of sparsely populated areas. Moreover, in adapting DRT systems to HSR travellers’ needs, windows catering to these needs should incorporate the option of setting the pickup or arrival times. This paper demonstrates that DRT systems could reach significant levels of service in rural areas compared with fixed lines and even private vehicles, especially when evaluating key aspects of the system’s efficiency for its implementation. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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23 pages, 8631 KiB

Open AccessArticle

Analysis of Road Safety Perception and Influencing Factors in a Complex Urban Environment—Taking Chaoyang District, Beijing, as an Example

by Xinyu Hou and Peng Chen

ISPRS Int. J. Geo-Inf. 2024, 13(8), 272; https://doi.org/10.3390/ijgi13080272 - 31 Jul 2024

Cited by 1 | Viewed by 939

Abstract

Measuring human perception of environmental safety and quantifying the street view elements that affect human perception of environmental safety are of great significance for improving the urban environment and residents’ safety perception. However, domestic large-scale quantitative research on the safety perception of Chinese [...] Read more.

Measuring human perception of environmental safety and quantifying the street view elements that affect human perception of environmental safety are of great significance for improving the urban environment and residents’ safety perception. However, domestic large-scale quantitative research on the safety perception of Chinese local cities needs to be deepened. Therefore, this paper chooses Chaoyang District in Beijing as the research area. Firstly, the network safety perception distribution of Chaoyang District is calculated and presented through the CNN model trained based on the perception dataset constructed by Chinese local cities. Then, the street view elements are extracted from the street view images using image semantic segmentation and target detection technology. Finally, the street view elements that affect the road safety perception are identified and analyzed based on LightGBM and SHAP interpretation framework. The results show the following: (1) the overall safety perception level of Chaoyang District in Beijing is high; (2) the number of motor vehicles and the proportion of the area of roads, skies, and sidewalks are the four factors that have the greatest impact on environmental safety perception; (3) there is an interaction between different street view elements on safety perception, and the proportion and number of street view elements have interaction on safety perception; (4) in the sections with the lowest, moderate, and highest levels of safety perception, the influence of street view elements on safety perception is inconsistent. Finally, this paper summarizes the results and points out the shortcomings of the research. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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15 pages, 5033 KiB

Open AccessArticle

Using Wi-Fi Probes to Evaluate the Spatio-Temporal Dynamics of Tourist Preferences in Historic Districts’ Public Spaces

by Yichen Gao, Sheng Liu, Biao Wei, Zhenni Zhu and Shanshan Wang

ISPRS Int. J. Geo-Inf. 2024, 13(7), 244; https://doi.org/10.3390/ijgi13070244 - 9 Jul 2024

Cited by 1 | Viewed by 918

Abstract

Tourist preferences for public spaces in historic districts can reflect whether renovated spaces and functional structures meet tourism demands. However, conventional big data lack the spatio-temporal accuracy needed to support a refined, dynamic study of small-scale public spaces inside historic districts. This paper, [...] Read more.

Tourist preferences for public spaces in historic districts can reflect whether renovated spaces and functional structures meet tourism demands. However, conventional big data lack the spatio-temporal accuracy needed to support a refined, dynamic study of small-scale public spaces inside historic districts. This paper, therefore, proposes using a Wi-Fi probe to evaluate the spatio-temporal dynamics of tourists’ spatial preferences in historic districts. We conducted a one-week measurement in the Xiaohe Street Historic Block in Hangzhou, China. Three indicators—visit time preference, aggregation preference, and stay preference—were used to examine the dynamic change in tourists’ spatial preferences, with 15 min as the time unit and public spaces with a radius of 25 m as the spatial unit. Our research demonstrates that, compared with conventional big data, the Wi-Fi probe offers a more reasonable and accurate method to measure tourists’ spatial preferences in historic districts at a smaller time and spatial granularity. The research findings can be applied to evaluate the effectiveness of spatial regeneration and diagnose renewal-related issues in historic districts. It can also serve as a foundation for more precise planning of public spaces in historic districts, as well as the modification of functional structures. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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17 pages, 9818 KiB

Open AccessArticle

Constraining the Geometry of NeRFs for Accurate DSM Generation from Multi-View Satellite Images

by Qifeng Wan, Yuzheng Guan, Qiang Zhao, Xiang Wen and Jiangfeng She

ISPRS Int. J. Geo-Inf. 2024, 13(7), 243; https://doi.org/10.3390/ijgi13070243 - 8 Jul 2024

Viewed by 1291

Abstract

Neural Radiance Fields (NeRFs) are an emerging approach to 3D reconstruction that use neural networks to reconstruct scenes. However, its applications for multi-view satellite photogrammetry, which aim to reconstruct the Earth’s surface, struggle to acquire accurate digital surface models (DSMs). To address this [...] Read more.

Neural Radiance Fields (NeRFs) are an emerging approach to 3D reconstruction that use neural networks to reconstruct scenes. However, its applications for multi-view satellite photogrammetry, which aim to reconstruct the Earth’s surface, struggle to acquire accurate digital surface models (DSMs). To address this issue, a novel framework, Geometric Constrained Neural Radiance Field (GC-NeRF) tailored for multi-view satellite photogrammetry, is proposed. GC-NeRF achieves higher DSM accuracy from multi-view satellite images. The key point of this approach is a geometric loss term, which constrains the scene geometry by making the scene surface thinner. The geometric loss term alongside z-axis scene stretching and multi-view DSM fusion strategies greatly improve the accuracy of generated DSMs. During training, bundle-adjustment-refined satellite camera models are used to cast rays through the scene. To avoid the additional input of altitude bounds described in previous works, the sparse point cloud resulting from the bundle adjustment is converted to an occupancy grid to guide the ray sampling. Experiments on WorldView-3 images indicate GC-NeRF’s superiority in accurate DSM generation from multi-view satellite images. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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24 pages, 8649 KiB

Open AccessArticle

Assessing the Impact of Land Use and Land Cover Changes on Surface Temperature Dynamics Using Google Earth Engine: A Case Study of Tlemcen Municipality, Northwestern Algeria (1989–2019)

by Imene Selka, Abderahemane Medjdoub Mokhtari, Kheira Anissa Tabet Aoul, Djamal Bengusmia, Kacemi Malika and Khadidja El-Bahdja Djebbar

ISPRS Int. J. Geo-Inf. 2024, 13(7), 237; https://doi.org/10.3390/ijgi13070237 - 2 Jul 2024

Cited by 2 | Viewed by 2529

Abstract

Changes in land use and land cover (LULC) have a significant impact on urban planning and environmental dynamics, especially in regions experiencing rapid urbanization. In this context, by leveraging the Google Earth Engine (GEE), this study evaluates the effects of land use and [...] Read more.

Changes in land use and land cover (LULC) have a significant impact on urban planning and environmental dynamics, especially in regions experiencing rapid urbanization. In this context, by leveraging the Google Earth Engine (GEE), this study evaluates the effects of land use and land cover modifications on surface temperature in a semi-arid zone of northwestern Algeria between 1989 and 2019. Through the analysis of Landsat images on GEE, indices such as normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), and normalized difference latent heat index (NDLI) were extracted, and the random forest and split window algorithms were used for supervised classification and surface temperature estimation. The multi-index approach combining the Normalized Difference Tillage Index (NDTI), NDBI, and NDVI resulted in kappa coefficients ranging from 0.96 to 0.98. The spatial and temporal analysis of surface temperature revealed an increase of 4 to 6 degrees across the four classes (urban, barren land, vegetation, and forest). The Google Earth Engine approach facilitated detailed spatial and temporal analysis, aiding in understanding surface temperature evolution at various scales. This ability to conduct large-scale and long-term analysis is essential for understanding trends and impacts of land use changes at regional and global levels. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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27 pages, 33073 KiB

Open AccessArticle

Exploring Summer Variations of Driving Factors Affecting Land Use Zoning Based on the Surface Urban Heat Island in Chiang Mai, Thailand

by Damrongsak Rinchumphu, Manat Srivanit, Niti Iamchuen and Chuchoke Aryupong

ISPRS Int. J. Geo-Inf. 2024, 13(7), 228; https://doi.org/10.3390/ijgi13070228 - 30 Jun 2024

Viewed by 1391

Abstract

Numerous studies have examined land surface temperature (LST) changes in Thailand using remote sensing, but there has been little research on LST variations within urban land use zones. This study addressed this gap by analyzing summer LST changes in land use zoning (LUZ) [...] Read more.

Numerous studies have examined land surface temperature (LST) changes in Thailand using remote sensing, but there has been little research on LST variations within urban land use zones. This study addressed this gap by analyzing summer LST changes in land use zoning (LUZ) blocks in the 2012 Chiang Mai Comprehensive Plan and their relationship with surface biophysical parameters (NDVI, NDBI, MNDWI). The approach integrated detailed zoning data with remote sensing for granular LST analysis. Correlation and stepwise regression analyses (SRA) revealed that NDBI significantly impacted LST in most block types, while NDVI and MNDWI also influenced LST, particularly in 2023. The findings demonstrated the complexity of LST dynamics across various LUZs in Chiang Mai, with SRA results explaining 45.7% to 53.2% of summer LST variations over three years. To enhance the urban environment, adaptive planning strategies for different block categories were developed and will be considered in the upcoming revision of the Chiang Mai Comprehensive Plan. This research offers a new method to monitor the urban heat island phenomenon at the block level, providing valuable insights for adaptive urban planning. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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22 pages, 17637 KiB

Open AccessArticle

A Spatial Semantic Feature Extraction Method for Urban Functional Zones Based on POIs

by Xin Yang and Xi’ang Ma

ISPRS Int. J. Geo-Inf. 2024, 13(7), 220; https://doi.org/10.3390/ijgi13070220 - 25 Jun 2024

Viewed by 1041

Abstract

Accurately extracting semantic features of urban functional zones is crucial for understanding urban functional zone types and urban functional spatial structures. Points of interest provide comprehensive information for extracting the semantic features of urban functional zones. Many researchers have used topic models of [...] Read more.

Accurately extracting semantic features of urban functional zones is crucial for understanding urban functional zone types and urban functional spatial structures. Points of interest provide comprehensive information for extracting the semantic features of urban functional zones. Many researchers have used topic models of natural language processing to extract the semantic features of urban functional zones from points of interest, but topic models cannot consider the spatial features of points of interest, which leads to the extracted semantic features of urban functional zones being incomplete. To consider the spatial features of points of interest when extracting semantic features of urban functional zones, this paper improves the Latent Dirichlet Allocation topic model and proposes a spatial semantic feature extraction method for urban functional zones based on points of interest. In the proposed method, an assumption (that points of interest belonging to the same semantic feature are spatially correlated) is introduced into the generation process of urban functional zones, and then, Gibbs sampling is combined to carry out the parameter inference process. We apply the proposed method to a simulated dataset and the point of interest dataset for Chaoyang District, Beijing, and compare the semantic features extracted by the proposed method with those extracted by the Latent Dirichlet Allocation. The results show that the proposed method sufficiently considers the spatial features of points of interest and has a higher capability of extracting the semantic features of urban functional zones than the Latent Dirichlet Allocation. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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16 pages, 2922 KiB

Open AccessArticle

Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration by Fusing Nighttime Light Data with Weibo Sign-In Data

by Yongwang Cao, Song Liu and Zaigao Yang

ISPRS Int. J. Geo-Inf. 2024, 13(6), 214; https://doi.org/10.3390/ijgi13060214 - 19 Jun 2024

Viewed by 1120

Abstract

Accurately identifying the spatial range of urban agglomerations holds significant practical importance for the precise allocation of various elements and coordinated development within urban agglomerations. However, current research predominantly focuses on the physical spaces of urban agglomerations, overlooking their sphere of influence. This [...] Read more.

Accurately identifying the spatial range of urban agglomerations holds significant practical importance for the precise allocation of various elements and coordinated development within urban agglomerations. However, current research predominantly focuses on the physical spaces of urban agglomerations, overlooking their sphere of influence. This study begins with the spatial interactions of population elements within urban agglomerations and fuses Weibo sign-in data with NTL data to identify the spatial range of urban agglomerations. It further compares and validates the results before and after the fusion of data. The results reveal that the accuracy of identifying the spatial range of urban agglomerations with the fusion of NTL data and Weibo sign-in data has improved by 7%, with a Kappa increase of 0.1766 compared to using NTL data alone, which indicates that fusing social media data can significantly enhance the accuracy of identifying the spatial range of urban agglomerations. This study proposes a novel approach for identifying the spatial range of urban agglomerations through the fusion of NTL data and social media data from a data fusion perspective. On one hand, it supplements the application of data fusion in the study of urban agglomeration spaces; on the other hand, it accurately identifies the spatial range of urban agglomerations, which holds great practical value for the sustainable development of urban agglomerations. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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17 pages, 297 KiB

Open AccessArticle

The Relationship between the Construction of Transportation Infrastructure and the Development of New Urbanization

by Jia Shen, Xiaohong Ren, Honglin Wu and Zhitao Feng

ISPRS Int. J. Geo-Inf. 2024, 13(6), 194; https://doi.org/10.3390/ijgi13060194 - 12 Jun 2024

Viewed by 1067

Abstract

Transport infrastructure plays a crucial role in facilitating the high-quality development of new urbanization. Based on the provincial panel data of 31 provinces in China from 2013 to 2020, this study empirically analyzed the impact and mechanism of transportation infrastructure on the high-quality [...] Read more.

Transport infrastructure plays a crucial role in facilitating the high-quality development of new urbanization. Based on the provincial panel data of 31 provinces in China from 2013 to 2020, this study empirically analyzed the impact and mechanism of transportation infrastructure on the high-quality development of new urbanization from multiple perspectives. The results showed that transportation infrastructure can significantly promote the development of new urbanization, and the promoting effect was significantly positive in the eastern and western regions, while it was positive but not significant in the central region. Transportation infrastructure can promote the development of new urbanization by promoting industrial agglomeration. When the population density is lower than the corresponding threshold value, the transport infrastructure can significantly promote the development of new urbanization; when the population density is higher than the corresponding threshold value, the transport infrastructure will significantly hinder the development of new urbanization. Transport infrastructure has a significant positive spatial spillover effect on the development of new urbanization, and the positive spatial spillover effect has been significant in the eastern, central and western regions. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

34 pages, 22533 KiB

Open AccessArticle

Interpretation of Hot Spots in Wuhan New Town Development and Analysis of Influencing Factors Based on Spatio-Temporal Pattern Mining

by Haijuan Zhao, Yan Long, Nina Wang, Shiqi Luo, Xi Liu, Tianyue Luo, Guoen Wang and Xuejun Liu

ISPRS Int. J. Geo-Inf. 2024, 13(6), 186; https://doi.org/10.3390/ijgi13060186 - 3 Jun 2024

Viewed by 1271

Abstract

The construction of new towns is one of the main measures to evacuate urban populations and promote regional coordination and urban–rural integration in China. Mining the spatio-temporal pattern of new town hot spots based on multivariate data and analyzing the influencing factors of [...] Read more.

The construction of new towns is one of the main measures to evacuate urban populations and promote regional coordination and urban–rural integration in China. Mining the spatio-temporal pattern of new town hot spots based on multivariate data and analyzing the influencing factors of new town construction hot spots can provide a strategic basis for new town construction, but few researchers have extracted and analyzed the influencing factors of new town internal hot spots and their classification. In order to define the key points of Wuhan’s new town construction and promote the construction of new cities in an orderly and efficient manner, this paper first constructs a space-time cube based on the luminous remote sensing data from 2010 to 2019, extracts hot spots and emerging hot spots in Wuhan New City, selects 14 influencing factor indicators such as population density, and uses bivariate Moran’s index to analyze the influencing factors of hot spots, indicating that the number of bus stops and vegetation coverage rate are the most significant. Secondly, the disorderly multivariate logistic regression model is used to analyze the influencing factors of emerging hot spots. The results show that population density, vegetation coverage, road density, distance to water bodies, and distance to train stations are the most significant factors. Finally, based on the analysis results, some relevant suggestions for the construction of Wuhan New City are proposed, providing theoretical support for the planning and policy guidance of new cities, and offering reference for the construction of new towns in other cities, promoting the construction of high-quality cities. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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15 pages, 6892 KiB

Open AccessArticle

A New Method Based on Lattice Boltzmann Method and Unsupervised Clustering for Identification of Urban-Scale Ventilation Corridors

by Tianyu Li and Peng Xie

ISPRS Int. J. Geo-Inf. 2024, 13(6), 183; https://doi.org/10.3390/ijgi13060183 - 31 May 2024

Viewed by 726

Abstract

With the increase in urban development intensity, the urban climate has become an important factor affecting sustainable development. The role of urban ventilation corridors in improving urban climate has received widespread attention. Urban ventilation identification and planning based on morphological methods have been [...] Read more.

With the increase in urban development intensity, the urban climate has become an important factor affecting sustainable development. The role of urban ventilation corridors in improving urban climate has received widespread attention. Urban ventilation identification and planning based on morphological methods have been initially applied. Traditional morphological methods do not adequately consider the dynamic process of air flow, resulting in a rough evaluation of urban ventilation patterns. This study proposes a new urban-scale ventilation corridor identification method that integrates the Lattice Boltzmann method and the K-means algorithm. Taking Wuhan, China as the research area, an empirical study in different wind directions was conducted on a 20 m grid. The results showed that three levels of ventilation corridors (

245.47 {k m}^{2} in total

) and two levels of ventilation obstruction areas (

658.09 {k m}^{2} in total

) were identified to depict the ventilation pattern of Wuhan’s central urban area. The method proposed in this study can meet the needs of urban-scale ventilation corridor identification in terms of spatial coverage, spatial distribution rate and dynamic analysis. Compared with the classic least cumulative ventilation cost method, the method proposed in this study can provide more morphologic details of the ventilation corridors. This plays a very important role in urban planning based on urban ventilation theory. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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18 pages, 18073 KiB

Open AccessArticle

Evaluating School Location Based on a Territorial Spatial Planning Knowledge Graph

by Xiankang Xu, Jian Hao and Jingwei Shen

ISPRS Int. J. Geo-Inf. 2024, 13(6), 173; https://doi.org/10.3390/ijgi13060173 - 24 May 2024

Viewed by 974

Abstract

The reasonable spatial planning of primary and secondary schools is an important factor in education development. In spatial planning, there are many models for the locations of primary and secondary schools; however, few quantitative evaluation models are available. Therefore, based on the many [...] Read more.

The reasonable spatial planning of primary and secondary schools is an important factor in education development. In spatial planning, there are many models for the locations of primary and secondary schools; however, few quantitative evaluation models are available. Therefore, based on the many factors affecting the layout planning of primary and secondary schools, a knowledge graph of territorial spatial planning that considers the topological relationship, direction relationship and metric relationship in spatial planning is designed and constructed. A school location evaluation model based on the knowledge graph of territorial spatial planning is proposed. The model combines many factors of the locations of schools, such as the service population, the impact of factories on schools, the adjacency and centrality of school plots, terrain and existing schools in the region, to quantitatively evaluate whether schools are reasonably located within a region. This study focuses on the Guangyang Island area in Chongqing, China, exploring the superiority and rationality of the planned land use for primary and secondary schools within the region. By analyzing the top three and bottom three ranked schools in conjunction with the actual conditions of the site, and comparing them with AHP hierarchical analysis and ArcGIS modelling research, the study concludes that the results of this model are highly reasonable within the scope of China’s territorial spatial planning. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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19 pages, 5672 KiB

Open AccessArticle

Where Are Business Incubators Built? County-Level Spatial Distribution and Rationales Based on the Big Data of Chinese Yangtze River Delta Region

by Tianhe Jiang and Zixuan Zhou

ISPRS Int. J. Geo-Inf. 2024, 13(6), 169; https://doi.org/10.3390/ijgi13060169 - 21 May 2024

Viewed by 1153

Abstract

Business incubators (BIs) in China have predominantly exhibited a government-led characteristic, recently broadening their spatial and temporal scope and extending reach to the county level. Regarding the inadequacies of county-level analysis scale, this study leverages Points of Interest (POI) big data to overcome [...] Read more.

Business incubators (BIs) in China have predominantly exhibited a government-led characteristic, recently broadening their spatial and temporal scope and extending reach to the county level. Regarding the inadequacies of county-level analysis scale, this study leverages Points of Interest (POI) big data to overcome them. To comprehend the governmental rationale in the construction of BIs, we examine the evolution dynamics of BIs in conjunction with policies. An economic geography framework is developed, conceptualizing BIs as quasi-public goods and productive services, and incorporating considerations of county-level fiscal operations and industrial structures. Focusing on the Yangtze River Delta (YRD) region as a case study, our findings reveal that over 98% of County Administrative Units (CAUs) have built BIs. Using kernel density estimation and Moran’s I, the spatial patterns of CAUs are identified. The CAUs are further classified into three categories of economic levels using the k-means algorithm, uncovering differentiated relationships between industry, finance, and their respective BI. Additionally, we analyze the density relationship between BIs and other facilities at a micro-level, showcasing various site selection rationales. The discussions highlight that while BIs tend to align with wealthier areas and advanced industries, affluent CAUs offer location advantages on BIs, whereas less wealthy CAUs prioritize quantity for political achievements. This paper concludes with recommendations about aligning BIs based on conditions and outlooks on future research. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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22 pages, 976 KiB

Open AccessArticle

The Geospatial Crowd: Emerging Trends and Challenges in Crowdsourced Spatial Analytics

by Sultan Alamri

ISPRS Int. J. Geo-Inf. 2024, 13(6), 168; https://doi.org/10.3390/ijgi13060168 - 21 May 2024

Cited by 1 | Viewed by 1982

Abstract

Crowdsourced spatial analytics is a rapidly developing field that involves collecting and analyzing geographical data, utilizing the collective power of human observation. This paper explores the field of spatial data analytics and crowdsourcing and how recently developed tools, cloud-based GIS, and artificial intelligence [...] Read more.

Crowdsourced spatial analytics is a rapidly developing field that involves collecting and analyzing geographical data, utilizing the collective power of human observation. This paper explores the field of spatial data analytics and crowdsourcing and how recently developed tools, cloud-based GIS, and artificial intelligence (AI) are being applied in this domain. This paper examines and discusses cutting-edge technologies and case studies in different fields of spatial data analytics and crowdsourcing used in a wide range of industries and government departments such as urban planning, health, transportation, and environmental sustainability. Furthermore, by understanding the concerns associated with data quality and data privacy, this paper explores the potential of crowdsourced data while also examining the related problems. This study analyzes the obstacles and challenges related to “geospatial crowdsourcing”, identifying significant limitations and predicting future trends intended to overcome the related challenges. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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26 pages, 6618 KiB

Open AccessArticle

Community Quality Evaluation for Socially Sustainable Regeneration: A Study Using Multi-Sourced Geospatial Data and AI-Based Image Semantic Segmentation

by Jinliu Chen, Wenquan Gan, Ning Liu, Pengcheng Li, Haoqi Wang, Xiaoxin Zhao and Di Yang

ISPRS Int. J. Geo-Inf. 2024, 13(5), 167; https://doi.org/10.3390/ijgi13050167 - 20 May 2024

Cited by 5 | Viewed by 1373

Abstract

The Chinese urban regeneration movement underscores a “people-oriented” paradigm, aimed at addressing urban challenges stemming from rapid prior urbanization, while striving for high-quality and sustainable urban development. At the community level, fostering quality through a socially sustainable perspective (SSP) is a pivotal strategy [...] Read more.

The Chinese urban regeneration movement underscores a “people-oriented” paradigm, aimed at addressing urban challenges stemming from rapid prior urbanization, while striving for high-quality and sustainable urban development. At the community level, fostering quality through a socially sustainable perspective (SSP) is a pivotal strategy for people-oriented urban regeneration. Nonetheless, explorations of community quality assessments grounded in an SSP have been notably scarce in recent scholarly discourse. This study pioneers a multidimensional quantitative model (MQM) for gauging community quality, leveraging diverse geospatial data sources from the SSP framework. The MQM introduces an evaluative framework with “Patency, Convenience, Comfort, and Safety” as primary indicators, integrating multi-sourced data encompassing the area of interest (AOI), Point of Interest (POI), Weibo check-ins, and Dianping data. The model’s efficacy is demonstrated through a case study in the Gusu district, Suzhou. Furthermore, semantic analysis of the Gusu district’s street view photos validates the MQM results. Our findings reveal the following: (1) AI-based semantic analysis accurately verifies the validity of MQM-generated community quality measurements, establishing its robust applicability with multi-sourced geospatial data; (2) the community quality distribution in Gusu district is notably correlated with the urban fabric, exhibiting lower quality within the ancient town area and higher quality outside it; and (3) communities of varying quality coexist spatially, with high- and low-quality communities overlapping in the same regions. This research pioneers a systematic, holistic methodology for quantitatively measuring community quality, laying the groundwork for informed urban regeneration policies, planning, and place making. The MQM, fortified by multi-sourced geospatial data and AI-based semantic analysis, offers a rigorous foundation for assessing community quality, thereby guiding socially sustainable regeneration initiatives and decision making at the community scale. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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23 pages, 7657 KiB

Open AccessArticle

A Multi-Feature Fusion Method for Urban Functional Regions Identification: A Case Study of Xi’an, China

by Zhuo Wang, Jianjun Bai and Ruitao Feng

ISPRS Int. J. Geo-Inf. 2024, 13(5), 156; https://doi.org/10.3390/ijgi13050156 - 7 May 2024

Cited by 1 | Viewed by 1512

Abstract

Research on the identification of urban functional regions is of great significance for the understanding of urban structure, spatial planning, resource allocation, and promoting sustainable urban development. However, achieving high-precision urban functional region recognition has always been a research challenge in this field. [...] Read more.

Research on the identification of urban functional regions is of great significance for the understanding of urban structure, spatial planning, resource allocation, and promoting sustainable urban development. However, achieving high-precision urban functional region recognition has always been a research challenge in this field. For this purpose, this paper proposes an urban functional region identification method called ASOE (activity–scene–object–economy), which integrates the features from multi-source data to perceive the spatial differentiation of urban human and geographic elements. First, we utilize VGG16 (Visual Geometry Group 16) to extract high-level semantic features from the remote sensing images with 1.2 m spatial resolution. Then, using scraped building footprints, we extract building object features such as area, perimeter, and structural ratios. Socioeconomic features and population activity features are extracted from Point of Interest (POI) and Weibo data, respectively. Finally, integrating the aforementioned features and using the Random Forest method for classification, the identification results of urban functional regions in the main urban area of Xi’an are obtained. After comparing with the actual land use map, our method achieves an identification accuracy of 91.74%, which is higher than other comparative methods, making it effectively identify four typical urban functional regions in the main urban area of Xi’an (e.g., residential regions, industrial regions, commercial regions, and public regions). The research indicates that the method of fusing multi-source data can fully leverage the advantages of big data, achieving high-precision identification of urban functional regions. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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18 pages, 2094 KiB

Open AccessArticle

Evolution Characteristics and Influencing Factors of City Networks in China: A Case Study of Cross-Regional Automobile Enterprises

by Daming Xu and Weiliang Shen

ISPRS Int. J. Geo-Inf. 2024, 13(5), 145; https://doi.org/10.3390/ijgi13050145 - 28 Apr 2024

Viewed by 1343

Abstract

The optimization of the spatial structure of the city network is conducive to the scientific spatial distribution of industries and the promotion of coordinated regional development. This study selected the top 100 automobile enterprises in the Chinese stock market that belong to China’s [...] Read more.

The optimization of the spatial structure of the city network is conducive to the scientific spatial distribution of industries and the promotion of coordinated regional development. This study selected the top 100 automobile enterprises in the Chinese stock market that belong to China’s pillar industry, a total of 1455 headquarters and branches, to establish an enterprise matrix. Based on the ownership linkage model, the evolution characteristics of city networks in China from 2000 to 2020 are revealed, and the influential factors of city networks are discussed using the negative binomial regression model. The findings are as follows: (1) there are significant differences in the status of automobile cities, forming a “pyramid network” hierarchy. (2) The agglomeration area of automobile cities has formed the development region of “4 + 4 + 1”. (3) The city network with hierarchical connections has formed a spatial structure of a “cross–cobweb” in the middle and “trapezoid–diamond” in the periphery. (4) Urban transportation conditions, the scientific research environment, the enterprise agglomeration economy, GDP per capita, and technological proximity positively impact the formation of a city network, but the total export–import volume has a negative impact. Overall, the government can use this study’s results to formulate policies for the automotive industry and urban development. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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27 pages, 11739 KiB

Open AccessArticle

Unveiling the Non-Linear Influence of Eye-Level Streetscape Factors on Walking Preference: Evidence from Tokyo

by Lu Huang, Takuya Oki, Sachio Muto and Yoshiki Ogawa

ISPRS Int. J. Geo-Inf. 2024, 13(4), 131; https://doi.org/10.3390/ijgi13040131 - 15 Apr 2024

Viewed by 1732

Abstract

Promoting walking is crucial for sustainable development and fosters individual health and well-being. Therefore, comprehensive investigations of factors that make walking attractive are vital. Previous research has linked streetscapes at eye-level to walking preferences, which usually focuses on simple linear relationships, neglecting the [...] Read more.

Promoting walking is crucial for sustainable development and fosters individual health and well-being. Therefore, comprehensive investigations of factors that make walking attractive are vital. Previous research has linked streetscapes at eye-level to walking preferences, which usually focuses on simple linear relationships, neglecting the complex non-linear dynamics. Additionally, the varied effects of streetscape factors across street segments and intersections and different street structures remain largely unexplored. To address these gaps, this study explores how eye-level streetscapes influence walking preferences in various street segments and intersections in Setagaya Ward, Tokyo. Using street view data, an image survey, and computer vision algorithms, we measured eye-level streetscape factors and walking preferences. The Extreme Gradient Boosting (XGBoost) model was then applied to analyze their non-linear relationships. This study identified key streetscape factors influencing walking preferences and uncovered non-linear trends within various factors, showcasing a variety of patterns, including upward, downward, and threshold effects. Moreover, our findings highlight the heterogeneity of the structural characteristics of street segments and intersections, which also impact the relationship between eye-level streetscapes and walking preferences. These insights can significantly inform decision-making in urban streetscape design, enhancing pedestrian perceptions. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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26 pages, 6480 KiB

Open AccessArticle

Spatial Relationship of Inter-City Population Movement and Socio-Economic Determinants: A Case Study in China Using Multiscale Geographically Weighted Regression

by Sihan Liu and Xinyi Niu

ISPRS Int. J. Geo-Inf. 2024, 13(4), 129; https://doi.org/10.3390/ijgi13040129 - 12 Apr 2024

Cited by 1 | Viewed by 1461

Abstract

In the current field of regional studies, there is a growing focus on regional spatial relationships from the perspective of functional linkages between cities. Inter-city population movement serves as an embodiment of the integrated functionality of cities within a region, and this is [...] Read more.

In the current field of regional studies, there is a growing focus on regional spatial relationships from the perspective of functional linkages between cities. Inter-city population movement serves as an embodiment of the integrated functionality of cities within a region, and this is closely tied to the socio-economic development of urban areas. This study utilized Location-Based Services (LBSs) to collect the scale of inter-city population movement across 355 cities in China. Additionally, socio-economic data published by local governments were incorporated. By establishing a Multiscale Geographically Weighted Regression (MGWR) model, this research explores the spatial relationships between inter-city population movement and socio-economic influencing factors in China. This study aims to elucidate the spatial scales of the relationships between various variables. Our research findings indicate that the relationship between inter-city population movement and potential socio-economic determinants exhibits spatial non-stationarity. It is better to explore this spatial relationship through the MGWR model as there are different determinants operating on inter-city population movement at different spatial scales. The spatial distribution of the coefficient estimates shows significant regional differences and numerical variations. In China’s economically developed coastal regions, there is relatively balanced development among cities, with advanced manufacturing and producer service industries acting as significant drivers of mobility. In inland regions of China, city size is the most influential variable, directing a substantial flow of human and economic resources towards regional socio-economic hubs such as provincial capitals. The main contribution of this study is the re-examination of the relationship between inter-city population movement and socio-economic factors from the perspective of spatial scales. This approach will help China to consider the heterogeneity of different regions more extensively when formulating regional development policies, thereby facilitating the targeted promotion of regional element flow. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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25 pages, 9966 KiB

Open AccessArticle

Balancing Flood Control and Economic Development in Flood Detention Areas of the Yangtze River Basin

by Siyuan Liao, Chao Wang, Renke Ji, Xiang Zhang, Zhifei Wang, Wei Wang and Nengcheng Chen

ISPRS Int. J. Geo-Inf. 2024, 13(4), 122; https://doi.org/10.3390/ijgi13040122 - 8 Apr 2024

Cited by 1 | Viewed by 1880

Abstract

Serving as a crucial part of the Yangtze River Basin (YRB)’s flood control system, Flood Detention Areas (FDAs) are vital in mitigating large-scale floods. Urbanization has led to the development of urban FDAs, but significant losses could ensue if these FDAs are activated. [...] Read more.

Serving as a crucial part of the Yangtze River Basin (YRB)’s flood control system, Flood Detention Areas (FDAs) are vital in mitigating large-scale floods. Urbanization has led to the development of urban FDAs, but significant losses could ensue if these FDAs are activated. With improved reservoirs and embankments, flood pressure in the middle reaches has lessened, posing challenges in balancing flood control and economic benefits. This paper presents a comparative analysis of land use, GDP, and population in FDAs and adjacent cities, enhancing our understanding of their disparities and interrelations. Using the Analytic Hierarchy Process (AHP)–Entropy Weight Method (EW)–Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) comprehensive evaluation method, we assess changes in flood control and economic values in FDAs. The results show a conflict between flood control and economic policies in FDAs, highlighting their underestimated economic potential, especially in urban areas. This study identifies differences in economic development across FDAs and a strong correlation between flood control value and inundation rates. Based on evaluations and simulations of the 1954 flood, we provide recommendations for the FDAs’ construction plan, which serves the development and flood management of the YRB and offer insights for similar assessments elsewhere. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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29 pages, 12972 KiB

Open AccessArticle

How Does the 2D/3D Urban Morphology Affect the Urban Heat Island across Urban Functional Zones? A Case Study of Beijing, China

by Shouhang Du, Yuhui Wu, Liyuan Guo, Deqin Fan and Wenbin Sun

ISPRS Int. J. Geo-Inf. 2024, 13(4), 120; https://doi.org/10.3390/ijgi13040120 - 4 Apr 2024

Cited by 5 | Viewed by 1868

Abstract

Studying driving factors of the urban heat island phenomenon is vital for enhancing urban ecological environments. Urban functional zones (UFZs), key for planning and management, have a substantial impact on the urban thermal environment through their two-dimensional (2D)/three-dimensional (3D) morphology. Despite prior research [...] Read more.

Studying driving factors of the urban heat island phenomenon is vital for enhancing urban ecological environments. Urban functional zones (UFZs), key for planning and management, have a substantial impact on the urban thermal environment through their two-dimensional (2D)/three-dimensional (3D) morphology. Despite prior research on land use and landscape patterns, understanding the effects of 2D/3D urban morphology in different UFZs is lacking. This study employs Landsat-8 remote sensing data to retrieve the land surface temperature (LST). A method combining supervised and unsupervised classification is proposed for UFZ mapping, utilizing multi-source geospatial data. Subsequently, parameters defining the 2D/3D urban morphology of UFZs are established. Finally, the Pearson correlation analysis and GeoDetector are used to analyze the driving factors. The results indicate the following: (1) In the Fifth Ring Road area of Beijing, the residential zones exhibit the highest LST, followed by the industrial zones. (2) In 2D urban morphology, the percentage of built-up landscape (built-PLAND) and Shannon’s diversity index (SHDI) are the main factors influencing LST. In 3D urban morphology, building density, the sky view factor (SVF), and the area-weighted mean shape index (shape index) are the main factors influencing LST. Therefore, low-density buildings with simple and dispersed shapes contribute to mitigating LST, while fragmented distributions of trees, grasslands, and water bodies also play important roles in alleviating LST. (3) In the interactive detection results, all UFZs show the highest interaction detection results with the built-PLAND. (4) Spatial variations are observed in the impact of different UFZs on LST. For instance, in the residential zones, industrial zones, green space zones, and public service zones, the SVF is negatively correlated with LST, while in the commercial zones, the SVF exhibits a positive correlation with LST. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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21 pages, 12915 KiB

Open AccessArticle

An Integrated Duranton and Overman Index and Local Duranton and Overman Index Framework for Industrial Spatial Agglomeration Pattern Analysis

by Yupu Huang, Li Zhuo and Jingjing Cao

ISPRS Int. J. Geo-Inf. 2024, 13(4), 116; https://doi.org/10.3390/ijgi13040116 - 29 Mar 2024

Viewed by 1519

Abstract

Accurately measuring industrial spatial agglomeration patterns is crucial for promoting regional economic development. However, few studies have considered both agglomeration degrees and cluster locations of industries. Moreover, the traditional multi-scale cluster location mining (MCLM) method still has limitations in terms of accuracy, parameter [...] Read more.

Accurately measuring industrial spatial agglomeration patterns is crucial for promoting regional economic development. However, few studies have considered both agglomeration degrees and cluster locations of industries. Moreover, the traditional multi-scale cluster location mining (MCLM) method still has limitations in terms of accuracy, parameter setting, calculation efficiency, etc. This study proposes a new framework for analyzing industrial spatial agglomeration patterns, which uses the Duranton and Overman (DO) index for estimating agglomeration degrees and a newly developed local DO (LDO) index for mining cluster locations. The MCLM-LDO method was proposed by incorporating the LDO index into the MCLM method, and it was validated via comparisons with three baseline methods based on two synthetic datasets. The results proved that the MCLM-LDO method can achieve accuracies of 0.945 and 1 with computational times of 0.15 s and 0.11 s on two datasets, which are superior to existing MCLM methods. The proposed framework was further applied to analyze the spatial agglomeration patterns of the industry of computer, communication, and other electronic equipment manufacturing in Guangdong Province, China. The results showed that the framework gives a more holistic perspective of spatial agglomeration patterns, which can serve as more meaningful references for industrial sustainable development. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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19 pages, 34847 KiB

Open AccessArticle

Distinguishing the Intervalley Plain from the Intermountain Flat for Landform Mapping Using the Sightline Algorithm

by Ge Yan, Guoan Tang, Dingyang Lu, Junfei Ma, Xin Yang and Fayuan Li

ISPRS Int. J. Geo-Inf. 2024, 13(3), 86; https://doi.org/10.3390/ijgi13030086 - 8 Mar 2024

Viewed by 1432

Abstract

The intervalley plain is an important type of landform for mapping, and it has good connectivity for urban construction and development on the Loess Plateau. During the global landform mapping of the Deep-time Digital Earth (DDE) Big Science Program, it was found that [...] Read more.

The intervalley plain is an important type of landform for mapping, and it has good connectivity for urban construction and development on the Loess Plateau. During the global landform mapping of the Deep-time Digital Earth (DDE) Big Science Program, it was found that slope and relief amplitude hardly distinguished intervalley plains from intermountain flats. This study established a novel descriptive method based on a digital elevation model to describe the difference between intervalley plains and intermountain flats. With the proposed method, first the pattern of variation in the elevation angle is described using a sight line on the terrain profile, and the lowest elevation angle (LEA) is extracted. The maximum value of the LEA is subsequently used among multiple terrain profiles to represent the maximum velocity of the elevation decrease, that is, the three-dimensional lowest elevation angle (3D LEA), to represent the intervalley plains with lower 3D LEA values. The sight parameters of the 3D LEA are evaluated to optimize the intervalley plain mapping. The functional mechanism of the sight parameters is presented from a mathematical perspective and a comparative analysis of the 3D LEA is performed for the relief amplitude and slope angle at multiple scales. This study explores sight-line analysis in a novel way, providing a new terrain factor for landform mapping involving intervalley plains. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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18 pages, 7602 KiB

Open AccessArticle

A Knowledge-Guided Intelligent Analysis Method of Geographic Digital Twin Models: A Case Study on the Diagnosis of Geometric Deformation in Tunnel Excavation Profiles

by Ce Liang, Jun Zhu, Jinbin Zhang, Qing Zhu, Jingyi Lu, Jianbo Lai and Jianlin Wu

ISPRS Int. J. Geo-Inf. 2024, 13(3), 78; https://doi.org/10.3390/ijgi13030078 - 29 Feb 2024

Viewed by 1911

Abstract

It is essential to establish a digital twin scene, which helps to depict the dynamically changing geographical environment accurately. Digital twins could improve the refined management level of intelligent tunnel construction; however, research on geographical twin models primarily focuses on modeling and visual [...] Read more.

It is essential to establish a digital twin scene, which helps to depict the dynamically changing geographical environment accurately. Digital twins could improve the refined management level of intelligent tunnel construction; however, research on geographical twin models primarily focuses on modeling and visual description, which has low analysis efficiency. This paper proposes a knowledge-guided intelligent analysis method for the geometric deformation of tunnel excavation profile twins. Firstly, a dynamic data-driven knowledge graph of tunnel excavation twin scenes was constructed to describe tunnel excavation profile twin scenes accurately. Secondly, an intelligent diagnosis algorithm for geometric deformation of tunnel excavation contour twins was designed by knowledge guidance. Thirdly, multiple visual variables were jointly used to support scene fusion visualization of tunnel excavation profile twin scenes. Finally, a case was selected to implement the experimental analysis. The experimental results demonstrate that the method in this article can achieve an accurate description of objects and their relationships in tunnel excavation twin scenes, which supports rapid geometric deformation analysis of the tunnel excavation profile twin. The speed of geometric deformation diagnosis is increased by more than 90% and the cognitive efficiency is improved by 70%. The complexity and difficulty of the deformation analysis operation are reduced, and the diagnostic analysis ability and standardization of the geographic digital twin model are effectively improved. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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28 pages, 16332 KiB

Open AccessArticle

Supporting Asset Management with GIS and Business Intelligence Technologies: The Case Study of the University of Turin

by Paola Gasbarri, Daniele Accardo, Elisa Cacciaguerra, Silvia Meschini and Lavinia Chiara Tagliabue

ISPRS Int. J. Geo-Inf. 2024, 13(3), 65; https://doi.org/10.3390/ijgi13030065 - 21 Feb 2024

Viewed by 2104

Abstract

Despite the promising outcomes achieved over time in Asset Management, data accessibility, correlation, analysis, and visualization still represent challenges. The integration, readability, and interpretation of heterogeneous information by different stakeholders is a further concern, especially at the urban scale, where spatial data integration [...] Read more.

Despite the promising outcomes achieved over time in Asset Management, data accessibility, correlation, analysis, and visualization still represent challenges. The integration, readability, and interpretation of heterogeneous information by different stakeholders is a further concern, especially at the urban scale, where spatial data integration is required to correlate virtual information with the real world. The Geographic Information System (GIS) allows these connections, representing and digitizing extensive areas with significant benefits for asset analysis, management, and decision-making processes. Such benefits are central for managing large and widespread university campuses as they are comparable to small cities, covering a wide urban region and including resources highly integrated into the urban context. The paper presents how GIS integrated into Business Intelligence (BI) tools can support university Asset Management System (AMS) creation for the optimal use of resources, illustrating the University of Turin case study. The results discussion considers the relationship between the different elements of the assets and their synergy with the city. It focuses on four themes, dealing with the asset identification of buildings and resources, especially the educational ones, asset spatiotemporal evolution, and buildings’ distances for proximity analysis. The benefits achievable through the AMS, related challenges, and possible future developments are highlighted. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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23 pages, 19627 KiB

Open AccessArticle

A Spatiotemporal Hierarchical Analysis Method for Urban Traffic Congestion Optimization Based on Calculation of Road Carrying Capacity in Spatial Grids

by Dong Jiang, Wenji Zhao, Yanhui Wang and Biyu Wan

ISPRS Int. J. Geo-Inf. 2024, 13(2), 59; https://doi.org/10.3390/ijgi13020059 - 15 Feb 2024

Cited by 1 | Viewed by 2592

Abstract

Traffic congestion is a globally widespread problem that causes significant economic losses, delays, and environmental impacts. Monitoring traffic conditions and analyzing congestion factors are the first, challenging steps in optimizing traffic congestion, one of the main causes of which is regional spatiotemporal imbalance. [...] Read more.

Traffic congestion is a globally widespread problem that causes significant economic losses, delays, and environmental impacts. Monitoring traffic conditions and analyzing congestion factors are the first, challenging steps in optimizing traffic congestion, one of the main causes of which is regional spatiotemporal imbalance. In this article, we propose an improved spatiotemporal hierarchical analysis method whose steps include calculating road carrying capacity based on geospatial data, extracting vehicle information from remote sensing images to reflect instantaneous traffic demand, and analyzing the spatiotemporal matching degree between roads and vehicles in theory and in practice. First, we defined and calculated the ratio of carrying capacity in a regional road network using a nine-cell-grid model composed of nested grids of different sizes. By the conservation law of flow, we determined unbalanced areas in the road network configuration using the ratio of the carrying capacity of the central cell to that of the nine grid cells. Then, we designed a spatiotemporal analysis method for traffic congestion using real-time traffic data as the dependent variables and five selected spatial indicators relative to the spatial grids as the independent variables. The proposed spatiotemporal analysis method was applied to Chengdu, a typical provincial capital city in China. The relationships among regional traffic, impact factors, and spatial heterogeneity were analyzed. The proposed method effectively integrates GIS, remote sensing, and deep learning technologies. It was further demonstrated that our method is reliable and effective and enhances the coordination of congested areas by virtue of a fast calculation speed and an efficient local balance adjustment. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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14 pages, 1799 KiB

Open AccessArticle

Evaluation of the Accessibility of Children’s Spaces at the Community Scale: The Case Study of Hangzhou

by Yuanzheng Cui, Qiuting Wang, Guixiang Zha, Yunxiao Dang, Xuejun Duan, Lei Wang and Ming Luo

ISPRS Int. J. Geo-Inf. 2024, 13(2), 55; https://doi.org/10.3390/ijgi13020055 - 12 Feb 2024

Cited by 1 | Viewed by 2220

Abstract

The safety, inclusivity, accessibility, and green communities emphasized in the United Nations’ Sustainable Development Goals (SDGs) play a vital role in the establishment of child-friendly cities. The governments are actively promoting the development of sustainable, child-friendly cities that prioritize people’s needs and aim [...] Read more.

The safety, inclusivity, accessibility, and green communities emphasized in the United Nations’ Sustainable Development Goals (SDGs) play a vital role in the establishment of child-friendly cities. The governments are actively promoting the development of sustainable, child-friendly cities that prioritize people’s needs and aim to enhance the well-being of residents, from children to families. However, there is limited research utilizing GIS analysis techniques and internet big data to analyze spatial equity in children’s spatial accessibility. Therefore, this study introduces an innovative approach focusing on the community level. Drawing on data from the popular social networking platform mobile application “Xiaohongshu” and employing network analysis methods based on walking and driving modes, this study analyzed and investigated the accessibility of children’s spaces in the city of Hangzhou, China. Regarding spatial characteristics, the distribution of children’s space resources in the main urban area of Hangzhou exhibited a “peripheral low and central high” trend, which was closely linked to the distribution of population space. This pattern indicates potential significant disparities in the allocation of children’s space resources. Notably, the core area of Hangzhou demonstrated the highest level of accessibility to children’s spaces, with Gongshu District exhibiting the best accessibility. Conversely, non-core urban areas generally had relatively poor accessibility. Furthermore, different types of children’s spaces, such as indoor cultural spaces, indoor entertainment spaces, outdoor parks, and outdoor nature areas, all exhibited the highest accessibility in the city center, which gradually decreased towards the periphery. Additionally, this study evaluated the convenience of children’s spaces in various communities by combining population size and accessibility levels. The findings revealed that communities in the core area had higher accessibility levels in the northwest–southeast direction, while accessibility decreased towards the northeast–southwest direction. Consequently, the relative convenience of these communities tended to be lower. By examining spatial equity, this study provides valuable insights into the promotion of sustainable, child-friendly cities that prioritize people’s needs and contribute to the well-being of residents, from children to families. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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19 pages, 719 KiB

Open AccessArticle

Online Decision Support Infrastructures for Integrating Spatial Planning and Flood Risk Management Policies

by Jing Ran and Zorica Nedovic-Budic

ISPRS Int. J. Geo-Inf. 2024, 13(2), 53; https://doi.org/10.3390/ijgi13020053 - 11 Feb 2024

Viewed by 1681

Abstract

Accessible geospatial data are crucial for informed decision making and policy development in urban planning, environmental governance, and hazard mitigation. Spatial data infrastructures (SDIs) have been implemented to facilitate such data access. However, with the rapid advancements in geospatial software and modelling tools, [...] Read more.

Accessible geospatial data are crucial for informed decision making and policy development in urban planning, environmental governance, and hazard mitigation. Spatial data infrastructures (SDIs) have been implemented to facilitate such data access. However, with the rapid advancements in geospatial software and modelling tools, it is important to re-visit the theoretical discussion about the different roles of data-focused SDIs and decision support and modelling tools, particularly in relation to their different impacts on policy making and policy integration. This research focuses on addressing this issue within the specific context of policy integration in spatial planning and flood risk management. To investigate this, an experiment was conducted comparing a data-focused SDI, the Myplan Viewer, with a prototype Internet-based Spatially Integrated Policy Infrastructure (SIPI). The findings reveal that the SIPI, which provides access to both data and decision support and modelling tools, significantly enhances policy integration compared to the Myplan Viewer. Moreover, drawing upon communicative action theory, this study underscores that while data-focused SDIs support instrumental goals, they possess limitations in facilitating trade-offs and balancing diverse interests in the policy-making process, particularly in supporting strategic and communicative actions. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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23 pages, 6524 KiB

Open AccessArticle

Semantic-Enhanced Graph Convolutional Neural Networks for Multi-Scale Urban Functional-Feature Identification Based on Human Mobility

by Yuting Chen, Pengjun Zhao, Yi Lin, Yushi Sun, Rui Chen, Ling Yu and Yu Liu

ISPRS Int. J. Geo-Inf. 2024, 13(1), 27; https://doi.org/10.3390/ijgi13010027 - 11 Jan 2024

Cited by 5 | Viewed by 2595

Abstract

Precise identification of spatial unit functional features in the city is a pre-condition for urban planning and policy-making. However, inferring unknown attributes of urban spatial units from data mining of spatial interaction remains a challenge in geographic information science. Although neural-network approaches have [...] Read more.

Precise identification of spatial unit functional features in the city is a pre-condition for urban planning and policy-making. However, inferring unknown attributes of urban spatial units from data mining of spatial interaction remains a challenge in geographic information science. Although neural-network approaches have been widely applied to this field, urban dynamics, spatial semantics, and their relationship with urban functional features have not been deeply discussed. To this end, we proposed semantic-enhanced graph convolutional neural networks (GCNNs) to facilitate the multi-scale embedding of urban spatial units, based on which the identification of urban land use is achieved by leveraging the characteristics of human mobility extracted from the largest mobile phone datasets to date. Given the heterogeneity of multi-modal spatial data, we introduced the combination of a systematic data-alignment method and a generative feature-fusion method for the robust construction of heterogeneous graphs, providing an adaptive solution to improve GCNNs’ performance in node-classification tasks. Our work explicitly examined the scale effect on GCNN backbones, for the first time. The results prove that large-scale tasks are more sensitive to the directionality of spatial interaction, and small-scale tasks are more sensitive to the adjacency of spatial interaction. Quantitative experiments conducted in Shenzhen demonstrate the superior performance of our proposed framework compared to state-of-the-art methods. The best accuracy is achieved by the inductive GraphSAGE model at the scale of 250 m, exceeding the baseline by 25.4%. Furthermore, we innovatively explained the role of spatial-interaction factors in the identification of urban land use through the deep learning method. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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40 pages, 28745 KiB

Open AccessArticle

Bayesian Structural Time Series and Geographically Weighted Logistic Regression Modelling Impacts of COVID-19 Lockdowns on the Spatiotemporal Patterns of London’s Crimes

by Rui Wang and Yijing Li

ISPRS Int. J. Geo-Inf. 2024, 13(1), 18; https://doi.org/10.3390/ijgi13010018 - 4 Jan 2024

Viewed by 2820

Abstract

Given the paramount impacts of COVID-19 on people’s lives in the capital of the UK, London, it was foreseeable that the city’s crime patterns would have undergone significant transformations, especially during lockdown periods. This study aims to testify the crime patterns’ changes in [...] Read more.

Given the paramount impacts of COVID-19 on people’s lives in the capital of the UK, London, it was foreseeable that the city’s crime patterns would have undergone significant transformations, especially during lockdown periods. This study aims to testify the crime patterns’ changes in London, using data from March 2020 to March 2021 to explore the driving forces for such changes, and hence propose data-driven insights for policy makers and practitioners on London’s crime deduction and prevention potentiality in post-pandemic era. (1) Upon exploratory data analyses on the overall crime change patterns, an innovative BSTS model has been proposed by integrating restriction-level time series into the Bayesian structural time series (BSTS) model. This novel method allows the research to evaluate the varied effects of London’s three lockdown periods on local crimes among the regions of London. (2) Based on the predictive results from the BSTS modelling, three regression models were deployed to identify the driving forces for respective types of crime experiencing significant increases during lockdown periods. (3) The findings solidified research hypotheses on the distinct factors influencing London’s specific types of crime by period and by region. In light of the received evidence, insights on a modified policing allocation model and supporting the unemployed group was proposed in the aim of effectively mitigating the surges of crimes in London. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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17 pages, 3385 KiB

Open AccessArticle

Detecting the Spatial Association between Commercial Sites and Residences in Beijing on the Basis of the Colocation Quotient

by Lei Zhou and Chen Wang

ISPRS Int. J. Geo-Inf. 2024, 13(1), 7; https://doi.org/10.3390/ijgi13010007 - 26 Dec 2023

Cited by 1 | Viewed by 1803

Abstract

Identifying the spatial association between commercial sites and residences is important for urban planning. However, (1) the patterns of spatial association between commercial sites and residences across an urban space and (2) how the spatial association patterns of each commercial format and different [...] Read more.

Identifying the spatial association between commercial sites and residences is important for urban planning. However, (1) the patterns of spatial association between commercial sites and residences across an urban space and (2) how the spatial association patterns of each commercial format and different levels of residences vary remain unclear. To address these gaps, this study used point-of-interest data of commercial sites and residences in Beijing, China, to calculate colocation quotients, which were used for identifying the spatial association characteristics and patterns of commercial sites and residences in the city. The results show that (1) the global colocation quotient of commercial sites and residences in Beijing is below 1, indicating relatively weak spatial association. The spatial association between each commercial format and residences varies greatly and shows the characteristics of integration of high-frequency consumption and separation of low-frequency consumption. Additionally, the spatial associations between high-grade residences and commercial formats are relatively weak, whereas those between low-grade residences and commercial formats are relatively strong. (2) The local spatial association patterns of various commercial formats and residences exhibit obvious spatial heterogeneity. Overall, the proportions of various commercial formats attracted by residences are considerably higher than those of residences attracted by various commercial formats, revealing spatial asymmetry. Within the Fourth Ring Road, commercial formats are mainly attracted by residences, showing a spatial association pattern of “distribute commercial sites according to the location of residences”. The proportions of residences attracted by commercial formats increase outside the Fourth Ring Road, presenting a spatial association pattern of “commercial formats attracting residences”. The findings offer valuable insights into the development mechanisms of commercial and residential spaces and provide valuable information for urban planning. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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23 pages, 92608 KiB

Open AccessArticle

Assessing the Defensibility of Medieval Fortresses on the Mediterranean Coast: A Study of Algerian and Spanish Territories

by Mohand Oulmas, Amina Abdessemed-Foufa, Angel Benigno Gonzalez Avilés and José Ignacio Pagán Conesa

ISPRS Int. J. Geo-Inf. 2024, 13(1), 2; https://doi.org/10.3390/ijgi13010002 - 19 Dec 2023

Viewed by 2373

Abstract

This study focuses on assessing the defensiveness of medieval fortresses situated along the Mediterranean coast, including the Northern Algerian coast and Southeastern Spain. The proposed methodology involved a two-fold process comprising identification and evaluation. Initially, we identified and geolocated our case studies, deriving [...] Read more.

This study focuses on assessing the defensiveness of medieval fortresses situated along the Mediterranean coast, including the Northern Algerian coast and Southeastern Spain. The proposed methodology involved a two-fold process comprising identification and evaluation. Initially, we identified and geolocated our case studies, deriving their locations from archival sources. We then seamlessly integrated them into a Geographic Information System (GIS) for precise georeferencing on a rasterized landscape. Subsequently, we conducted assessments of visibility, intervisibility, and elevation, which we consider pivotal in determining the degree of defensibility of the fortified sites. Specifically, the aim of this research was to investigate the intricate relationship between natural landscapes and architectural defensive features, with a focus on discerning the influence that the chosen location has on the strategic and defensive significance of the studied fortresses. Our findings reveal that the evolution of those defensive systems within our study context is intricately tied to the physical elements comprising the landscape. These natural constituents have served as a foundation for the architectural and defensive characteristics adopted by medieval builders. Furthermore, we delineated two distinct typologies: the isolated type, intentionally designed to obscure visibility, and the exposed type, characterized by a higher visibility index. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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23 pages, 13895 KiB

Open AccessArticle

A Web-Based Geodesign Tool for Evaluating the Integration of Transport Infrastructure, Public Spaces, and Human Activities

by Liu Yang

ISPRS Int. J. Geo-Inf. 2023, 12(12), 504; https://doi.org/10.3390/ijgi12120504 - 17 Dec 2023

Viewed by 2267

Abstract

The need for addressing the adverse impacts of transport infrastructure on public spaces and human activities (TSH) emphasizes the importance of designing integrated TSH system, thereby necessitating tailored planning support systems (PSS). This study begins by assessing the demand for PSS using surveys [...] Read more.

The need for addressing the adverse impacts of transport infrastructure on public spaces and human activities (TSH) emphasizes the importance of designing integrated TSH system, thereby necessitating tailored planning support systems (PSS). This study begins by assessing the demand for PSS using surveys and interviews to uncover the need for robust analysis and evaluation support, particularly through the use of geographical information systems (GIS). On this basis, a prototype GIS platform is proposed for analyzing and evaluating the integration of the TSH system at the block scale. This user-friendly geodesign tool encompasses a customizable evaluation index (includes seven KPAs and KPIs), allowing for combined quantitative and qualitative assessments. Notably, it introduces a buffer effect index to quantify transport–space interaction. The proposed tool serves as a dedicated platform for evaluating TSH systems, offering 2D/3D visualization capabilities and two analysis units and facilitating cross-platform collaboration. Applied to a case study in Nanjing, China, it effectively assessed the interdependence among different TSH system components and block integration around expressways, railways, and main roads. This tool holds promise in offering invaluable insights into urban planning and (re)development, thereby enhancing the integration of transport infrastructure and public spaces. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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21 pages, 7098 KiB

Open AccessArticle

What Drives the Spatial Heterogeneity of Urban Leisure Activity Participation? A Multisource Big Data-Based Metrics in Nanjing, China

by Shaojun Liu, Xiawei Chen, Fengji Zhang, Yiyan Liu and Junlian Ge

ISPRS Int. J. Geo-Inf. 2023, 12(12), 499; https://doi.org/10.3390/ijgi12120499 - 12 Dec 2023

Cited by 2 | Viewed by 2195

Abstract

With the rapid pace of urbanization, enhancing the quality of life has become an urgent demand for the general public in both developed and developing countries. This study addresses the pressing need to understand the spatial distribution and underlying mechanisms of urban leisure [...] Read more.

With the rapid pace of urbanization, enhancing the quality of life has become an urgent demand for the general public in both developed and developing countries. This study addresses the pressing need to understand the spatial distribution and underlying mechanisms of urban leisure activity participation. To achieve this, we propose a novel methodological framework that integrates diverse big data sources, including mobile phone signaling data, urban geospatial data, and web-crawled data. By applying this framework to the urban area of Nanjing, our study reveals both the temporal and spatial patterns of urban leisure activity participation in the city. Notably, leisure activity participation is significantly higher on weekends, with distinctive daily peaks. Moreover, we identify spatial heterogeneity in leisure activity participation across the study area. Leveraging the OLS regression model, we design and quantify a comprehensive set of 12 internal and external indicators to explore the formation mechanisms of leisure participation for different leisure activity types. Our findings offer valuable guidance for urban planners and policymakers to optimize the allocation of resources, enhance urban street environments, and develop leisure resources in a rational and inclusive manner. Ultimately, this study contributes to the ongoing efforts to improve the quality of urban life and foster vibrant and sustainable cities. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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27 pages, 870 KiB

Open AccessArticle

Internet in the Middle of Nowhere: Performance of Geoportals in Rural Areas According to Core Web Vitals

by Karol Król and Wojciech Sroka

ISPRS Int. J. Geo-Inf. 2023, 12(12), 484; https://doi.org/10.3390/ijgi12120484 - 29 Nov 2023

Cited by 2 | Viewed by 2037

Abstract

The spatial planning system in Poland is undergoing a fundamental reform. It emphasises the digital representation of spatial data. Low performance of geoportals, no Internet access, or poor connectivity can contribute to the exclusion from the spatial planning process, and consequently to the [...] Read more.

The spatial planning system in Poland is undergoing a fundamental reform. It emphasises the digital representation of spatial data. Low performance of geoportals, no Internet access, or poor connectivity can contribute to the exclusion from the spatial planning process, and consequently to the exclusion from a specific part of public life. Considering these developments, the present study seems relevant by pointing out the issue with geoportal performance and availability of quality Internet in rural areas. The primary contribution of the article is (1) results of performance measurements for selected geoportals; (2) presentation of measuring tools and performance indices combined with methods for ad-hoc performance measuring; and (3) presentation of potential actions to improve geoportal performance on the device with which it is used. The article offers case studies where the performance of selected geoportals was tested in rural mountainous areas with limited Internet access. Five geoportals were tested with PageSpeed Insights (PSI), WebPageTest, GTmetrix, Pingdom, and GiftOfSpeed. Core Web Vitals indices were analysed: Largest Contentful Paint (LCP), First Input Delay (FID), Cumulative Layout Shift (CLS), and First Contentful Paint (FCP). The author verified values of the Speed Index and Fully Loaded Time along with other performance indices, like GTmetrix Structure. The study failed to provide unambiguous evidence that radio link users in rural areas could experience problems with geoportal performance, although the results seem to suggest it indirectly. PSI Lab Data and Field Data tests revealed a relatively low performance of the geoportals. The Performance index remained below 50 in most cases, which is ‘Poor’ according to the PSI scale. The fully loaded time exceeded 10 s for all the geoportals and 20 s in some cases (Lab Data). It means that the perceived performance of the tested geoportals on a radio link in rural areas is most probably even lower. The case studies demonstrated further that the user has limited possibilities to speed up map applications. It is possible to slightly improve the geoportal experience through the optimisation of the device locally, but the responsibility to ensure geoportal performance is mainly the publisher’s. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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17 pages, 40798 KiB

Open AccessArticle

A GIS-Based Damage Evaluation Method for Explosives Road Transportation Accidents

by Jing Zhao, Ning Liu, Junhui Li, Xi Guo, Hongtao Deng and Jinshan Sun

ISPRS Int. J. Geo-Inf. 2023, 12(12), 470; https://doi.org/10.3390/ijgi12120470 - 21 Nov 2023

Viewed by 1872

Abstract

The road transportation of explosives is highly concerning due to its substantial impact on social safety. For the safety management of explosive transportation, e.g., transport route planning and emergency rescue, explosion consequence evaluation is of paramount importance. The consequence evaluation of explosion accidents [...] Read more.

The road transportation of explosives is highly concerning due to its substantial impact on social safety. For the safety management of explosive transportation, e.g., transport route planning and emergency rescue, explosion consequence evaluation is of paramount importance. The consequence evaluation of explosion accidents is affected by many factors, especially spatial features, such as the location of transport vehicles, the distribution of buildings, and the presence of individuals around the road, etc. However, there is still a lack of quantification methods for building damage evaluation, human casualty evaluation that considers real-time population density, and efficient interactive damage evaluation methods. In this paper, we formalize three typical scenarios of damage evaluation for explosive road transportation accidents, i.e., explosion point-based, road segment-based, and route-based damage evaluation. For each scenario, we propose a Height-aware Hierarchical Building Damage (HHBD) model and a Shelter-aware Human Casualty (SHC) model for building damage evaluation and human casualty evaluation, respectively. We also develop a GIS-based interactive visualization platform that integrates multi-source geospatial data and that enables efficient geospatial computation. In addition, a case study of liquefied natural gas (LNG) transportation in Wuhan is demonstrated in order to verify the effectiveness and efficiency of the proposed system. The research results can support the decision-making process of explosive transportation safety warnings and emergency rescue. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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28 pages, 3338 KiB

Open AccessArticle

Evaluation and Spatiotemporal Differentiation of Cultural Tourism Development Potential: The Case of the Middle and Lower Reaches of the Yellow River

by Yuying Chen, Yajie Li, Xiangfeng Gu, Qing Yuan, Nan Chen and Qi Jin

ISPRS Int. J. Geo-Inf. 2023, 12(11), 461; https://doi.org/10.3390/ijgi12110461 - 12 Nov 2023

Viewed by 2445

Abstract

Cultural tourism development potential (CTDP) is the future value and supporting force of the environmental value, economic and social efficiency, innovation ability and supporting system of cultural tourism. At present, there are few relevant studies on CTDP, but the research results on the [...] Read more.

Cultural tourism development potential (CTDP) is the future value and supporting force of the environmental value, economic and social efficiency, innovation ability and supporting system of cultural tourism. At present, there are few relevant studies on CTDP, but the research results on the tourism development potential of cultural heritage are relatively rich, and the existing evaluation methods lack comprehensiveness, dynamics and visualization. Based on systems theory and sustainable development theory, this article attempts to innovate and collect time series data through the entropy method, multi-index comprehensive evaluation method, spatial kernel density estimation method, and centroid transferring model. The temporal and spatial evolution characteristics and the CTDP of 43 cities in the middle and lower reaches of the Yellow River are examined and analyzed. It is found that the CTDP in the middle and lower reaches of the Yellow River is divided into five levels; the overall potential intensity of the research area is small and has significant spatial differences; influenced by the time factor, the interaction and spatial correlation of within the research area are significant; the development of regional cultural tourism has strong regional dependence in the short range. The center of potential gradually moves to the geometric center. This study is significant for promoting the sustainable development of economic tourism in cradles of world civilization. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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19 pages, 16455 KiB

Open AccessArticle

Spatial and Temporal Evolution of the Characteristics of Spatially Aggregated Elements in an Urban Area: A Case Study of Wuhan, China

by Zhihao Sun, Dezhi Kang, Hongzan Jiao, Ya Yang, Wei Xue, Hao Wu, Lingbo Liu, Yuwei Su and Zhenghong Peng

ISPRS Int. J. Geo-Inf. 2023, 12(11), 448; https://doi.org/10.3390/ijgi12110448 - 31 Oct 2023

Cited by 1 | Viewed by 2007

Abstract

Urban spatial elements present agglomeration and dispersion geographic processes in the urban development. Identifying the characteristics of their distribution changes and accurately capturing the evolution of the urban spatial structure is of great significance to urban construction and management. This study takes Wuhan [...] Read more.

Urban spatial elements present agglomeration and dispersion geographic processes in the urban development. Identifying the characteristics of their distribution changes and accurately capturing the evolution of the urban spatial structure is of great significance to urban construction and management. This study takes Wuhan as a case study and focuses on the spatial agglomeration distribution of urban elements. Point of Interest (POI) data from 2017 to 2021 were collected, and the Block2Vec model was employed to extract the comprehensive geographic information from various elements within the traffic analysis zones (TAZs). Subsequently, identification and division were carried out to access the level of urban spatial element agglomeration. Finally, the spatial–temporal evolution characteristics of urban aggregated elements in the Wuhan metropolitan development area over five years were compared and analyzed. The results indicate the following: (1) urban elements present an obvious circle structure in their spatial agglomeration, with distinct differences observed among different element types; (2) from 2017 to 2021, the Wuhan urban development zone experienced obvious expansion in urban space; (3) increased agglomeration of spatial elements mainly occurred in the surrounding areas of the city, while some areas in the city center displayed weaker element agglomeration and a reduction in various service facilities. The results demonstrate that the method used in this study could effectively identify the spatial agglomeration distribution of urban elements, as well as accurately distinguishing regions with distinct development characteristics. This approach could provide robust support for optimizing land use and urban spatial planning. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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23 pages, 13304 KiB

Open AccessArticle

Identifying Spatiotemporal Patterns of Multiscale Connectivity in the Flow Space of Urban Agglomeration in the Yellow River Basin

by Yaohui Chen, Caihui Cui, Zhigang Han, Feng Liu, Qirui Wu and Wangqin Yu

ISPRS Int. J. Geo-Inf. 2023, 12(11), 447; https://doi.org/10.3390/ijgi12110447 - 30 Oct 2023

Cited by 1 | Viewed by 1965

Abstract

The United Nations Sustainable Development Goals (SDGs) and the rise of global sustainability science have led to the increasing recognition of basins as the key natural geographical units for human–land system coupling and spatial coordinated development. The effective measurement of spatiotemporal patterns of [...] Read more.

The United Nations Sustainable Development Goals (SDGs) and the rise of global sustainability science have led to the increasing recognition of basins as the key natural geographical units for human–land system coupling and spatial coordinated development. The effective measurement of spatiotemporal patterns of urban connectivity within a basin has become a key issue in achieving basin-related SDGs. Meanwhile, China has been actively working toward co-ordinated regional development through in-depth implementation of the Yellow River Basin’s ecological protection and high-quality development. Urban connectivity has been trending in urban planning, and significant progress has been made on different scales according to the flow space theory. Nevertheless, few studies have been conducted on the multiscale spatiotemporal patterns of urban agglomeration connectivity. In this study, the urban network in the Yellow River Basin was constructed using Tencent population migration data from 2015 and 2019. It was then divided into seven distinct communities to enable analysis at both the basin and community scales. Centrality, symmetry, and polycentricity indices were employed, and the multiscale spatiotemporal patterns of urban agglomerations in the Yellow River Basin were identified using community detection, complex networks, and the migration kaleidoscope method. Community connectivity was notably concentrated at the basin scale with a centripetal pattern and spatial heterogeneity. Additionally, there was a symmetrical and co-ordinated relationship in population migration between the eastern and western regions of the basin, as well as between the internal and external parts of the basin. At the community scale, there was significant variation in the extent of central agglomeration among different communities, with few instances of similar-level, long-distance, and interregional bilateral links. The utilization of multiscale spatiotemporal patterns has the potential to enhance the comprehension of economic cooperation between various cities and urban agglomerations. This understanding can aid decision-makers in formulating sustainable development policies that foster the spatial integration of the basin. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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38 pages, 31524 KiB

Open AccessArticle

Comparative Hotspot Analysis of Urban Living Environments and Transit-Oriented Development (TOD) Strategies: A Case Study of Beijing and Xi’an

by Yuchen Dai, Shouhang Du and Hanqing Min

ISPRS Int. J. Geo-Inf. 2023, 12(11), 446; https://doi.org/10.3390/ijgi12110446 - 30 Oct 2023

Cited by 3 | Viewed by 2763

Abstract

The quality of urban living environments has become a focal point for local governments and citizens. By conducting a thorough analysis of the human settlement environment, the study can not only gain an intuitive insight into the quality of life of residents but [...] Read more.

The quality of urban living environments has become a focal point for local governments and citizens. By conducting a thorough analysis of the human settlement environment, the study can not only gain an intuitive insight into the quality of life of residents but also propose forward-thinking and sustainable suggestions for areas of improvement. This study optimizes and analyzes open platform data closely related to residents and assesses the suitability of different areas for living from diverse perspectives and methodologies. This study has chosen Beijing and Xi’an as the primary case studies. The local living environment is categorized into residential, living, recreational environment, transportation convenience, and safety. Our evaluation combines subjective and objective analysis methods and considers hotspot and cold spot analyses. This study employs the Analytic Hierarchy Process (AHP) as a subjective analysis method and the entropy method for objective analysis. By integrating both methods, it assesses the living environment conditions of Beijing and Xi’an. Furthermore, using GIS software, hotspot analysis is conducted for both cities, identifying areas of high and low quality. Detailed analysis is subsequently carried out for the low-quality clusters. Ultimately, this study, grounded in the theory of Transit-Oriented Development (TOD), presents recommendations for sustainable development aimed at representative rural towns and streets. City centers in Beijing and Xi’an have high-quality environments, while the outskirts show declining quality. Xi’an has uneven resource distribution, while Beijing is more balanced, with hotspot analyses indicating specific high- and low-quality cluster locations in both cities. These disparities and characteristics of the low-quality clusters offer insights for future urban development. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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25 pages, 9203 KiB

Open AccessArticle

Observed Equity and Driving Factors of Automated External Defibrillators: A Case Study Using WeChat Applet Data

by Shunyi Liao, Feng Gao, Lei Feng, Jiemin Wu, Zexia Wang and Wangyang Chen

ISPRS Int. J. Geo-Inf. 2023, 12(11), 444; https://doi.org/10.3390/ijgi12110444 - 30 Oct 2023

Cited by 2 | Viewed by 2321

Abstract

Out-of-hospital cardiac arrest (OHCA) causes a high mortality rate each year, which is a threat to human well-being and health. An automated external defibrillator (AED) is an effective device for heart attack-related diseases and is a panacea to save OHCA. Most relevant literature [...] Read more.

Out-of-hospital cardiac arrest (OHCA) causes a high mortality rate each year, which is a threat to human well-being and health. An automated external defibrillator (AED) is an effective device for heart attack-related diseases and is a panacea to save OHCA. Most relevant literature focuses on the spatial distribution, accessibility, and configuration optimization of AED devices, which all belong to the characteristics of the spatial distribution of AED devices. Still, there is a lack of discussion on related potential influencing factors. In addition, analysis of AED facilities involving multiple city comparisons is less considered. In this study, data on AED facilities in two major cities in China were obtained through the WeChat applet. Then, the AED equity at the city and block scales and its socioeconomic factors were analyzed using the Gini coefficient, Lorenz curve, and optimal parameters-based geo-graphical detector (OPGD) model. Results show that the number of AEDs in Shenzhen was about eight-times that of in Guangzhou. The distribution of AEDs in Shenzhen was more equitable with a global Gini of 0.347, higher than that in Guangzhou with a global Gini of 0.504. As for the determinants of AED equity, residential density was the most significant determinant in both Guangzhou and Shenzhen from the perspective of individual effects on AED equity. Differently, due to the aging population in Guangzhou, the proportion of the elderly in blocks was influential to local AED equity. The local economic development level was crucial to local AED equity in Shenzhen. The results of the interaction detector model illustrate that relatively equitable AED distributions were found in the high-density residential areas with a balance of employment and housing, high-aging residential areas, and high-mobility residential areas in Guangzhou. The area with a high level of local economic development, dense population, and large mobility was the area with a relatively equitable distribution of AEDs in Shenzhen. The results of this paper are conducive to understanding the equity of AEDs and its socio-economic determinants, providing scientific reference for the optimization and management of AEDs. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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19 pages, 1379 KiB

Open AccessArticle

Evaluation of the Resilience of the Catering Industry in Hong Kong before and after the COVID-19 Outbreak Based on Point-of-Interest Data

by Yijia Liu, Wenzhong Shi, Yue Yu, Linya Peng and Anshu Zhang

ISPRS Int. J. Geo-Inf. 2023, 12(11), 443; https://doi.org/10.3390/ijgi12110443 - 27 Oct 2023

Cited by 2 | Viewed by 3524

Abstract

COVID-19 has caused a serious economic shock which challenges the resilience of businesses around the world. Understanding the spatial distribution pattern of business resilience, as well as identifying factors that promote business resilience, is crucial to economic recovery. Most existing studies mainly analyze [...] Read more.

COVID-19 has caused a serious economic shock which challenges the resilience of businesses around the world. Understanding the spatial distribution pattern of business resilience, as well as identifying factors that promote business resilience, is crucial to economic recovery. Most existing studies mainly analyze one side of the concept of resilience, such as how businesses closed, expanded, and innovated, while no studies take all the characteristics of resilience into account and analyze them from a geographical view. To fill this gap, this study first relates the method of calculating stability in ecology to geography, and proposes a point of interest (POI)-based index to evaluate an industry’s resilience in a city. Then, with the catering industry in Hong Kong as an example, the spatial distribution of resilience in June 2020 and December 2020 is investigated using the local indicators of spatial association (LISA) approach. An ordinary least squares (OLS) regression model is adopted to identify impactful factors on resilience. The results reveal that the resilience of restaurants is quite stable in local central areas, but areas near the checking points at Shenzhen in mainland China are severely affected. Most traditional location factors had the benefit of stabilization, while hospitals had negative responses. The presented analysis framework is possible to be easily generalized to other industries or cities. The overall result of the study provides a spatial understanding which would be essential as a reference for future urban planning regarding post-pandemic recovery. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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25 pages, 11815 KiB

Open AccessArticle

Revealing the Spatio-Temporal Heterogeneity of the Association between the Built Environment and Urban Vitality in Shenzhen

by Zhitao Li and Guanwei Zhao

ISPRS Int. J. Geo-Inf. 2023, 12(10), 433; https://doi.org/10.3390/ijgi12100433 - 22 Oct 2023

Cited by 6 | Viewed by 2371

Abstract

Sensing urban vitality is a useful method for understanding urban development. However, the spatio-temporal characteristics of the association between the built environment and urban vitality in Shenzhen, the youngest mega-city in China, have not yet been explored. In this paper, we examined the [...] Read more.

Sensing urban vitality is a useful method for understanding urban development. However, the spatio-temporal characteristics of the association between the built environment and urban vitality in Shenzhen, the youngest mega-city in China, have not yet been explored. In this paper, we examined the effects of built environment indicators on urban vitality by using spatial regression models and multi-source geospatial data. The main research findings were as follows. Firstly, urban vitality displayed a consistent high–low pattern during both weekdays and weekends. Differences in the distribution of urban vitality with time between weekdays and weekends were more significant. Secondly, the effects of various built environment indicators on urban vitality exhibited significant temporal disparities. Within a day, population density, building density, bus station density, and distance to metro stations all exhibited positive effects, while distance to the central business district (CBD) exhibited negative effects, with pronounced diurnal differences. Moreover, the effects of road network density and functional mix on urban vitality were both positive and negative throughout the day. Thirdly, besides population density and building density, road network density, functional mix, bus stop density, and distance from metro stations exhibited positive and negative disparities within the study area. Overall, distance to the CBD had a negative effect on urban vitality. This concludes that planning for urban vitality should consider the spatio-temporal heterogeneity of the association between the built environment and urban vitality. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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18 pages, 5031 KiB

Open AccessArticle

The Analyses of Land Use and Prevention in High-Density Main Urban Areas under the Constraint of Karst Ground Subsidence: Study of Wuhan City, China

by Lin Gao, Yan Shi, Yang Qiu, Chuanming Ma and Aiguo Zhou

ISPRS Int. J. Geo-Inf. 2023, 12(10), 425; https://doi.org/10.3390/ijgi12100425 - 16 Oct 2023

Viewed by 1614

Abstract

The development and utilization of land in the main urban area have significantly impacted the stability of the regional geological environment through various means, such as increased load and subway construction, primarily manifested as rock and soil mass deformation leading to geological hazards. [...] Read more.

The development and utilization of land in the main urban area have significantly impacted the stability of the regional geological environment through various means, such as increased load and subway construction, primarily manifested as rock and soil mass deformation leading to geological hazards. Therefore, it is worth exploring how to reduce the occurrence of karst ground subsidence (KGS) through reasonable land development and control measures in the main urban areas with large-scale developments of buried karst formations. This study focuses on the main urban area of Wuhan City. An evaluation model for KGS was constructed using the analytic hierarchy process (AHP) and comprehensive index evaluation method by analyzing the geological conditions that affect KGS. The susceptibility zoning of KGS was obtained with GIS spatial analysis technology. The results show that the susceptible areas can be divided into extreme, high, medium, and weak susceptibility, accounting for 4.93%, 15.30%, 33.21%, and 46.56%, respectively, which are consistent with the distribution density of past KSGs. Furthermore, by selecting the subway construction as a human activity type, it indirectly discusses the influence of land development intensity on KGS. The results show that past KSGs are mainly concentrated in areas with high engineering construction density and significant land development intensity. Based on the above, strategies for regional land development and prevention and control of KGSs are proposed. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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19 pages, 15347 KiB

Open AccessArticle

A Knowledge-Guided Fusion Visualisation Method of Digital Twin Scenes for Mountain Highways

by Ranran Tang, Jun Zhu, Ying Ren, Yongzhe Ding, Jianlin Wu, Yukun Guo and Yakun Xie

ISPRS Int. J. Geo-Inf. 2023, 12(10), 424; https://doi.org/10.3390/ijgi12100424 - 15 Oct 2023

Cited by 5 | Viewed by 2368

Abstract

Informatization is an important trend in the field of mountain highway management, and the digital twin is an effective way to promote mountain highway information management due to the complex and diverse terrain of mountainous areas, the high complexity of mountainous road scene [...] Read more.

Informatization is an important trend in the field of mountain highway management, and the digital twin is an effective way to promote mountain highway information management due to the complex and diverse terrain of mountainous areas, the high complexity of mountainous road scene modeling and low visualisation efficiency. It is challenging to construct the digital twin scenarios efficiently for mountain highways. To solve this problem, this article proposes a knowledge-guided fusion expression method for digital twin scenes of mountain highways. First, we explore the expression features and interrelationships of mountain highway scenes to establish the knowledge graph of mountain highway scenes. Second, by utilizing scene knowledge to construct spatial semantic constraint rules, we achieve efficient fusion modeling of basic geographic scenes and dynamic and static ancillary facilities, thereby reducing the complexity of scene modeling. Finally, a multi-level visualisation publishing scheme is established to improve the efficiency of scene visualisation. On this basis, a prototype system is developed, and case experimental analysis is conducted to validate the research. The results of the experiment indicate that the suggested method can accomplish the fusion modelling of mountain highway scenes through knowledge guidance and semantic constraints. Moreover, the construction time for the model fusion is less than 5.7 ms; meanwhile, the dynamic drawing efficiency of the scene is maintained above 60 FPS. Thus, the construction of twinned scenes can be achieved quickly and efficiently, the effect of replicating reality with virtuality is accomplished, and the informatisation management capacity of mountain highways is enhanced. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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18 pages, 4124 KiB

Open AccessArticle

The Spatiotemporal Pattern Evolution and Driving Force of Tourism Information Flow in the Chengdu–Chongqing City Cluster

by Yang Zhao, Zegen Wang, Zhiwei Yong, Peng Xu, Qian Wang and Xuemei Du

ISPRS Int. J. Geo-Inf. 2023, 12(10), 414; https://doi.org/10.3390/ijgi12100414 - 10 Oct 2023

Cited by 2 | Viewed by 2039

Abstract

In recent years, the tourism industry has developed rapidly. However, traditional tourism information has the disadvantages of slow response speed and limited information content, which cannot reflect the evolution trend of spatial and temporal patterns of tourism information in time. Here, based on [...] Read more.

In recent years, the tourism industry has developed rapidly. However, traditional tourism information has the disadvantages of slow response speed and limited information content, which cannot reflect the evolution trend of spatial and temporal patterns of tourism information in time. Here, based on the Baidu Index, we construct an evaluation framework to analyse the spatial and temporal flow of tourism information in the Chengdu–Chongqing urban cluster from 2011 to 2021. Then, we analyse the urban links between different network levels from the evolution pattern. Finally, we use the geodetector model to analyse its driving mechanism. The results show that Chengdu and Chongqing are the most active cities in the study area in terms of tourism information. The unbalanced development of tourism information between Chengdu and Chongqing and other cities in the region gradually deepens during the period 2011–2019 (polarization effect), but the unbalanced development moderates after 2019. On the other hand, cities in the middle of the Chengdu–Chongqing cluster always have weak agglomeration effects of tourism information. Cities with high tourism information outflow rates in the Chengdu–Chongqing city cluster are mainly concentrated around Chengdu. The average outflow rate of Deyang is the highest, at 27.8%. Cities with low tourist information outflow rates are primarily located in the west, central and south. Ya’an is the city with the lowest outflow rate, with an average of −62.2%. Specifically, Chengdu is the dominant and most radiantly influential city. The tourism information of the Chengdu–Chongqing urban cluster shows a radial network with Chengdu and Chongqing as the core. The driving force analysis shows that the push factor of tourist source, such as the number of people buying pension insurance, is the core driving mechanism, while the pull factor of destination, such as the park green area, and resistance factors such as psychological distance, are in the secondary position. In general, this paper uses Internet tourism data to expand the traditional tourism information research of the Chengdu–Chongqing urban cluster, which can better respond to the changes and needs of the tourism market and provide reference for the spatial optimization of tourism destinations. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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22 pages, 21410 KiB

Open AccessArticle

A High-Resolution Spatial Distribution-Based Integration Machine Learning Algorithm for Urban Fire Risk Assessment: A Case Study in Chengdu, China

by Yulu Hao, Mengdi Li, Jianyu Wang, Xiangyu Li and Junmin Chen

ISPRS Int. J. Geo-Inf. 2023, 12(10), 404; https://doi.org/10.3390/ijgi12100404 - 3 Oct 2023

Cited by 5 | Viewed by 2043

Abstract

The development and functional perfection of urban areas have led to increasingly severe fire risks in recent decades. Previous urban fire risk assessment methods relied on subjective judgment, rough data collection, simple linear statistical methods, etc. These drawbacks can lead to low robustness [...] Read more.

The development and functional perfection of urban areas have led to increasingly severe fire risks in recent decades. Previous urban fire risk assessment methods relied on subjective judgment, rough data collection, simple linear statistical methods, etc. These drawbacks can lead to low robustness of evaluation and inadequate generalization ability. To resolve these problems, this paper selects the indicator and regression models based on the high-resolution data of the spatial distribution characteristics of Longquanyi distinct in Chengdu, China. and proposes an integrated machine learning algorithm for fire risk assessment. Firstly, the kernel density analysis is used to map the fourteen urban characteristics related to fire risks. The contributions of these indicators (characteristics) to fire risk and its corresponding index are determined by Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and eXtreme Gradient Boosting (XGBoost). Then, the spatial correlation of fire risks is determined through Moran’s I, and the spatial distribution pattern of indicator weights is clarified through the raster coefficient space analysis. Finally, with these selected indicators, we test the regression performance with a backpropagation neural network (BPNN) algorithm and a geographically weighted regression (GWR) model. The results indicate that numerical variables are more suitable than dummy variables for estimating micro-scale fire risks. The main factors with a high contribution are all numerical variables, including roads, gas pipelines, GDP, hazardous chemical enterprises, petrol and charging stations, cultural heritage protection units, assembly occupancies, and high-rise buildings. The machine learning algorithm integrating RF and BPNN shows the best performance (R² = 0.97), followed by the RF-GWR integrated algorithm (R² = 0.87). Compared with previous methods, this algorithm reduces the subjectivity of the traditional assessment models and shows the ability to automatically obtain the key indicators of urban fire risks. Hence, this new approach provides us with a more robust tool for assessing the future fire safety level in urban areas. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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24 pages, 9305 KiB

Open AccessArticle

Portraying the Influence Factor of Urban Vibrancy at Street Level Using Multisource Urban Data

by Rujuan Lu, Liang Wu and Deping Chu

ISPRS Int. J. Geo-Inf. 2023, 12(10), 402; https://doi.org/10.3390/ijgi12100402 - 1 Oct 2023

Cited by 2 | Viewed by 2771

Abstract

Exploring the factors influencing urban vibrancy can help policy development and advance urban planning and sustainable development. Previous studies have typically focused on the effects of physical environmental factors (e.g., built environment, urban landscape) on urban vibrancy, ignoring the role of non-physical environmental [...] Read more.

Exploring the factors influencing urban vibrancy can help policy development and advance urban planning and sustainable development. Previous studies have typically focused on the effects of physical environmental factors (e.g., built environment, urban landscape) on urban vibrancy, ignoring the role of non-physical environmental factors (e.g., urban psychological perceptions). In addition, these studies remain focused on relatively coarse spatial units and lack the exploration of finer-grained spatial structures. In this study, a novel framework is proposed to analyze urban vibrancy and its influencing factors at a more fine-grained street level. Firstly, two types of urban sensing data, POIs and Weibo check-ins, are integrated to portray the spatial distribution patterns of urban vibrancy on the streets. Secondly, a full convolutional network (FCN-8s) is used to segment the streetscape images of Beijing and use them as a basis to extract potential visual–spatial features and urban psychological perceptual features that influence urban vibrancy. Thirdly, we reveal the deeper causes of the impact of psychological perception on urban vibrancy. Finally, an improved ridge regression model is proposed to model the relationship between features and vibrancy, reducing the covariance between features while avoiding the reduction of important features. Satisfactory regression model performances were attained with adjusted R² values of 0.706, 0.743, and 0.807 at each characteristic level. The results of the study show that: Urban vibrancy is highly dependent on the proposed visual–spatial and urban psychological perception characteristics at the street level. In particular, positive urban psychological perceptions (safety, lively, wealthy) are positively correlated with urban vibrancy, while negative street perceptions (boring) are negatively correlated with urban vibrancy. Unlike previous research scales, our study shows that urban vibrancy portrayal based on the street scale has a greater potential to demonstrate fine-grained vibrancy distribution compared to the neighborhood scale. These findings may provide important insights for people-oriented urban development and planning. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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17 pages, 18947 KiB

Open AccessArticle

Assessing the Influence of Land Cover and Climate Change Impacts on Runoff Patterns Using CA-ANN Model and CMIP6 Data

by Mahfuzur Rahman, Md. Monirul Islam, Hyeong-Joo Kim, Shamsher Sadiq, Mehtab Alam, Taslima Siddiqua, Md. Al Mamun, Md. Ashiq Hossen Gazi, Matiur Rahman Raju, Ningsheng Chen, Md. Alamgir Hossain and Ashraf Dewan

ISPRS Int. J. Geo-Inf. 2023, 12(10), 401; https://doi.org/10.3390/ijgi12100401 - 1 Oct 2023

Cited by 2 | Viewed by 2329

Abstract

Dhaka city is experiencing rapid land cover changes, and the effects of climate change are highly visible. Investigating their combined influence on runoff patterns is vital for sustainable urban planning and water resources management. In this work, multi-date land cover classification was performed [...] Read more.

Dhaka city is experiencing rapid land cover changes, and the effects of climate change are highly visible. Investigating their combined influence on runoff patterns is vital for sustainable urban planning and water resources management. In this work, multi-date land cover classification was performed using a random forest (RF) algorithm. To validate accuracy of land cover classification, an assessment was conducted by employing kappa coefficient, which ranged from 85 to 96%, indicating a high agreement between classified images and the reference dataset. Future land cover changes were forecasted with cellular automata-artificial neural network (CA-ANN) model. Further, soil conservation service -curve number (SCS-CN) rainfall-runoff model combined with CMIP6 climate data was employed to assess how changes in land cover impact runoff within Dhaka metropolitan development plan (DMDP) area. Over the study period (2020–2100), substantial transformations of land cover were observed, i.e., built-up areas expanded to 1146.47 km² at the end of 2100, while agricultural areas and bare land diminished considerably. Consequently, monsoon runoff increased from 350.14 to 368.24 mm, indicating elevated hydrological responses. These findings emphasized an intricate interplay between urban dynamics and climatic shifts in shaping runoff patterns, underscoring urgency of incorporating these factors into urban planning strategies for sustainable water resources management in a rapidly growing city such as Dhaka. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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29 pages, 5144 KiB

Open AccessArticle

Assessment of Urban Resilience and Detection of Impact Factors Based on Spatial Autocorrelation Analysis and GeoDetector Model: A Case of Hunan Province

by Jianhong Chen, Hongcai Ma, Shan Yang, Zhiyong Zhou, Jianhui Huang and Licheng Chen

ISPRS Int. J. Geo-Inf. 2023, 12(10), 391; https://doi.org/10.3390/ijgi12100391 - 27 Sep 2023

Cited by 3 | Viewed by 1903

Abstract

The rapid development of urbanization has led to increasing uncertainties related to urban safety risks, which has brought certain challenges to the sustainable development of cities. The concept of urban resilience has found a new way to improve the ability of a city [...] Read more.

The rapid development of urbanization has led to increasing uncertainties related to urban safety risks, which has brought certain challenges to the sustainable development of cities. The concept of urban resilience has found a new way to improve the ability of a city to absorb and resolve risks. However, the existing literature on the evaluation of urban resilience is mostly developed from a static perspective, lacking a systematic and dynamic understanding of the level of urban resilience. Therefore, this paper takes Hunan Province as the research object, determines the resilience evaluation indicators, collects the data of each indicator by using the observation method and the literature method, then chooses the comprehensive index method and other methods to measure the urban resilience level of Hunan Province in the years of 2010–2021, and observes the dynamic changes in the resilience level. And, we use the GeoDetector model to detect the dominant factors affecting the urban resilience level and the interaction between these factors. The results of this study show that: (1) The level of urban resilience in Hunan Province shows a steady upward trend from 2010 to 2021, but cities with low resilience levels hold a dominant position. Among all subsystems, the level of urban economic resilience is the highest. (2) From 2010 to 2021, the level of urban resilience in Hunan Province indicates a stepwise spatial structure in the spatial pattern, gradually decreasing from east to west. (3) The urban resilience of Hunan Province from 2010 to 2021 has a significant spatial agglomeration effect, mainly manifested as “L-H type” agglomeration and “L-L type” agglomeration. (4) The spatio-temporal differentiation of urban resilience is mainly caused by economic and social factors, while ecological, institutional, and infrastructure factors have a relatively small influence on the level of urban resilience. The interaction of impact factors will have a more significant influence on urban resilience. The research results of this article are of great significance for urban resilience construction in Hunan Province and even the whole country. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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22 pages, 4047 KiB

Open AccessArticle

Nonlinear Hierarchical Effects of Housing Prices and Built Environment Based on Multiscale Life Circle—A Case Study of Chengdu

by Yandi Song, Shaoyao Zhang and Wei Deng

ISPRS Int. J. Geo-Inf. 2023, 12(9), 371; https://doi.org/10.3390/ijgi12090371 - 6 Sep 2023

Cited by 3 | Viewed by 2082

Abstract

Determining the optimal planning scale for urban life circles and analyzing the associated built environment factors are crucial for comprehending and regulating residential differentiation. This study aims to bridge the current research void concerning the nonlinear hierarchical relationships between the built environment and [...] Read more.

Determining the optimal planning scale for urban life circles and analyzing the associated built environment factors are crucial for comprehending and regulating residential differentiation. This study aims to bridge the current research void concerning the nonlinear hierarchical relationships between the built environment and residential differentiation under the multiscale effect. Specifically, six indicators were derived from urban crowdsourcing data: diversity of built environment function (DBEF1), density of built environment function (DBEF2), blue–green environment (BGE), traffic accessibility (TA), population vitality (PV), and shopping vitality (SV). Then, a gradient boosting decision tree (GBDT) was applied to derive the analysis of these indicators. Finally, the interpretability of machine learning was leveraged to quantify the relative importance and nonlinear relationships between built environment indicators and housing prices. The results indicate a hierarchical structure and inflection point effect of the built environment on residential premiums. Notably, the impact trend of the built environment on housing prices within a 15 min life circle remains stable. The effect of crowd behavior, as depicted by PV and SV, on housing prices emerges as the most significant factor. Furthermore, this study also categorizes housing into common and high-end residences, thereby unveiling that distinct residential neighborhoods exhibit varying degrees of dependence on the built environment. The built environment exerts a scale effect on the formation of residential differentiation, with housing prices exhibiting increased sensitivity to the built environment at a smaller life circle scale. Conversely, the effect of the built environment on housing prices is amplified at a larger life circle scale. Under the dual influence of the scale and hierarchical effect, this framework can dynamically adapt to the uncertainty of changes in life circle planning policies and residential markets. This provides strong theoretical support for exploring the optimal life circle scale, alleviating residential differentiation, and promoting group fairness. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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23 pages, 10144 KiB

Open AccessArticle

LBS Tag Cloud: A Centralized Tag Cloud for Visualization of Points of Interest in Location-Based Services

by Xiaoqiang Cheng, Zhongyu Liu, Huayi Wu and Haibo Xiao

ISPRS Int. J. Geo-Inf. 2023, 12(9), 360; https://doi.org/10.3390/ijgi12090360 - 1 Sep 2023

Cited by 1 | Viewed by 2130

Abstract

Taking location-based service (LBS) as the research scenario and aiming at the limitation of visualizing LBS points of interest (POI) in conventional web maps, this article proposes a visualization method of LBS-POI based on tag cloud, which is called “LBS tag cloud”. In [...] Read more.

Taking location-based service (LBS) as the research scenario and aiming at the limitation of visualizing LBS points of interest (POI) in conventional web maps, this article proposes a visualization method of LBS-POI based on tag cloud, which is called “LBS tag cloud”. In this method, the user location is taken as the layout center, and the name of the POI is converted into a text tag and then placed around the center. The tags’ size, color, and placement location are calculated based on other attributes of the POI. The calculation of placement location is at the core of the LBS tag cloud. Firstly, the tag’s initial placement position and layout priority are calculated based on polar coordinates, and the tags are placed in the initial placement position in the order of layout priority. Then, based on the force-directed model, a repulsive force is applied to the tag from the layout center to make it move to a position without overlapping with other tags. During the move, the quadtree partition of the text glyph is used to optimize the detection of overlaps between tags. Taking scenic spots as an example, the experimental results show that the LBS tag cloud can present the attributes and distribution of POIs completely and intuitively and can effectively represent the relationship between the POIs and user location, which is a new visualization form suitable for spatial cognition. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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32 pages, 34096 KiB

Open AccessArticle

Proposing Optimal Locations for Runoff Harvesting and Water Management Structures in the Hami Qeshan Watershed, Iraq

by Omeed Al-Kakey, Arsalan Ahmed Othman, Mustafa Al-Mukhtar and Volkmar Dunger

ISPRS Int. J. Geo-Inf. 2023, 12(8), 312; https://doi.org/10.3390/ijgi12080312 - 30 Jul 2023

Cited by 3 | Viewed by 2130

Abstract

Iraq, including the investigated watershed, has endured destructive floods and drought due to precipitation variability in recent years. Protecting susceptible areas from flooding and ensuring water supply is essential for maintaining basic human needs, agricultural production, and industry development. Therefore, locating and constructing [...] Read more.

Iraq, including the investigated watershed, has endured destructive floods and drought due to precipitation variability in recent years. Protecting susceptible areas from flooding and ensuring water supply is essential for maintaining basic human needs, agricultural production, and industry development. Therefore, locating and constructing storage structures is a significant initiative to alleviate flooding and conserve excessive surface water for future growth. This study aims to identify suitable locations for Runoff Harvesting (RH) and dam construction in the Hami Qeshan Watershed (HQW), Slemani Governorate, Iraq. We integrated in situ data, remotely sensed images, and Multi-Criteria Decision Analysis (MCDA) approaches for site selection within the Geographical Information Systems (GIS) environment. A total of ten criteria were employed to generate the RH suitability maps, including topographic position index, lithology, slope, precipitation, soil group, stream width, land cover, elevation, distance to faults, and distance to town/city. The weights of the utilized factors were determined via Weighted Linear Combination (WLC) and Analytic Hierarchy Process (AHP). The resulting RH maps were validated through 16 dam sites preselected by the Ministry of Agriculture and Water Resources (MAWR). Findings showed that the WLC method slightly outperformed AHP regarding efficiency and exhibited a higher overall accuracy. WLC achieved a higher average overall accuracy of 69%; consequently, it was chosen to locate new multipurpose dams for runoff harvesting in the study area. The overall accuracy of the 10 suggested locations in HQW ranged between 66% and 87%. Two of these sites align with the 16 locations MAWR has recommended: sites 2 and 5 in the northwest of HQW. It is noteworthy that all MAWR dam sites were situated in medium to excellent RH zones; however, they mostly sat on ineffective geological localities. It is concluded that a careful selection of the predictive factors and their respective weights is far more critical than the applied methods. This research offers decision-makers a practical and cost-effective tool for screening site suitability in data-scarce rugged terrains. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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20 pages, 50471 KiB

Open AccessArticle

Exploring the Correlation between Streetscape and Economic Vitality Using Machine Learning: A Case Study in the Old Urban District of Xuzhou, China

by Keran Li and Yan Lin

ISPRS Int. J. Geo-Inf. 2023, 12(7), 267; https://doi.org/10.3390/ijgi12070267 - 4 Jul 2023

Cited by 1 | Viewed by 2486

Abstract

The streetscapes of old urban districts record the changes in urban space and the vitality of socio-economic entities like storefronts. However, prior studies of urban vitality have preferred the demand end of crowd agglomeration to the supply end of commercial businesses, while the [...] Read more.

The streetscapes of old urban districts record the changes in urban space and the vitality of socio-economic entities like storefronts. However, prior studies of urban vitality have preferred the demand end of crowd agglomeration to the supply end of commercial businesses, while the refined application of street-view images (SVIs) and the spatial heterogeneity resulting from sectional differences among elements deserve further research. Under this context, this paper took both the alive and the closed storefronts as the objects and developed an analytical framework based on machine learning and SVIs to analyze the characteristics of the streetscape and the economic vitality, followed by a regression analysis between them with a multiscale geographically weighted regression (MGWR) model. Our findings comprise three aspects: (1) despite the sum of the storefronts being more often used, combining the alive and the closed businesses is beneficial to reflect the real economic vitality; (2) as a reflection of the spatial heterogeneity and sectional differences of elements, the asymmetric streetscape has a significant influence on the economic vitality; and (3) although different factors from the streetscape can influence economic vitality differently, based on varied proxies of the vitality, three factors, namely, higher difference value of the signboards, higher sum of glass interfaces, and lower difference value of the glass interfaces, can benefit the economic vitality. This research can support urban physical examination and the regeneration of old urban districts for urban planners, designers, and decision-makers, and provide new perspectives and proxies as well as a more fine-grained analysis among the traditional studies on economic vitality. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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30 pages, 4786 KiB

Open AccessSystematic Review

The Application of Space Syntax to Enhance Sociability in Public Urban Spaces: A Systematic Review

by Reza Askarizad, Patxi José Lamíquiz Daudén and Chiara Garau

ISPRS Int. J. Geo-Inf. 2024, 13(7), 227; https://doi.org/10.3390/ijgi13070227 - 28 Jun 2024

Cited by 6 | Viewed by 3770

Abstract

Public urban spaces are vital settings for fostering social interaction among people. However, understanding how spatial layouts can promote positive social behaviors remains a critical and debated challenge for urban designers and planners aiming to create socially sustainable environments. Space syntax, a well-established [...] Read more.

Public urban spaces are vital settings for fostering social interaction among people. However, understanding how spatial layouts can promote positive social behaviors remains a critical and debated challenge for urban designers and planners aiming to create socially sustainable environments. Space syntax, a well-established theory and research method, explores the influence of spatial configurations on social aspects. Despite its significant contributions, there is a lack of comprehensive systematic reviews evaluating its effectiveness in enhancing social interaction within urban public spaces. This study aims to identify the existing scientific gaps in the domain of space syntax studies, with a primary focus on sociability in public urban spaces. Following the PRISMA framework, a thorough literature search was conducted in the Scopus database, yielding 1107 relevant articles. After applying screening and eligibility criteria, 26 articles were selected for in-depth review. This review adopted a novel approach to synthesizing and analyzing the findings for identifying underexplored scientific gaps. The findings suggested a wide variety of research gaps to address, encompassing evidence, knowledge, practical, methodological, empirical, theoretical, and target populations to provide a thorough overview of the current state of knowledge in this field. In conclusion, by exploring the interplay between space syntax and design elements such as the urban infrastructure, landscaping, and microclimate in these areas, future research can bridge this gap, particularly when considering a cross-cultural lens. This study underscores the importance of space syntax in promoting social interaction in urban public spaces, offering a robust foundation for future research and practical applications to create more socially engaging environments. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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