Chen Li
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Chen Li has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
- Ruxia Bai
College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
2 shared publications - Xinyu Hu
College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
2 shared publications - Yi Shi
School of Architecture, Southeast University, Nanjing, China
2 shared publications - Beixiang Shi
School of Architecture, Southeast University, Nanjing 210096, China
1 shared publication - Chunyu Zhou
College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
1 shared publication - Haiyi Feng
Beijing Tsinghua Tongheng Planning Design and Research Institute Co., Ltd., Beijing 100085, China
1 shared publication
Latest Publications
- Open Access
Correlations between an Urban Three-Dimensional Pedestrian Network and Service Industry Layouts Based on Graph Convolutional Neural Networks: A Case Study of Xinjiekou, Nanjing
Urban high-density development has led to the emergence of complex three-dimensional pedestrian networks. As a crucial component of city centers, these networks significantly influence the spatial distribution of service industries. Understanding the correlation between pedestrian networks and service industry layouts is vital for effective planning and development. This study proposes a technical framework for analyzing the relationship between three-dimensional pedestrian networks and service industry layouts. Using the Xinjiekou central area in Nanjing as a case study, we constructed a three-dimensional pedestrian network model using the sDNA method. Focusing on catering formats, we introduced a method to study the spatial distribution characteristics of service industries in three-dimensional spaces and employed a graph convolutional network model to systematically analyze the correlation between pedestrian network closeness and betweenness with catering formats. The results indicate that pedestrian network closeness is significantly positively correlated with the number and average spending of catering formats, while betweenness shows almost no correlation. High-closeness areas, due to their traffic convenience and walkability, are more conducive to the concentration of catering formats and higher spending levels. Our findings provide valuable insights for catering format location decisions and the optimization of three-dimensional pedestrian networks, contributing to sustainable urban development.
Open AccessCorrelations between an Urban Three-Dimensional Pedestrian Network and Service Industry Layouts Based on Graph Convolutional Neural Networks: A Case Study of Xinjiekou, Nanjing
Urban high-density development has led to the emergence of complex three-dimensional pedestrian networks. As a crucial component of city centers, these networks significantly influence the spatial distribution of service industries. Understanding the correlation between pedestrian networks and service industry layouts is vital for effective planning and development. This study proposes a technical framework for analyzing the relationship between three-dimensional pedestrian networks and service industry layouts. Using the Xinjiekou central area in Nanjing as a case study, we constructed a three-dimensional pedestrian network model using the sDNA method. Focusing on catering formats, we introduced a method to study the spatial distribution characteristics of service industries in three-dimensional spaces and employed a graph convolutional network model to systematically analyze the correlation between pedestrian network closeness and betweenness with catering formats. The results indicate that pedestrian network closeness is significantly positively correlated with the number and average spending of catering formats, while betweenness shows almost no correlation. High-closeness areas, due to their traffic convenience and walkability, are more conducive to the concentration of catering formats and higher spending levels. Our findings provide valuable insights for catering format location decisions and the optimization of three-dimensional pedestrian networks, contributing to sustainable urban development.
- Open Access
- 25 August 2024
- Published by MDPI AG in ISPRS International Journal of Geo-Information
- Vol. 13 (9) , 301
A Study on the Spatiotemporal Distribution and Usage Pattern of Dockless Shared Bicycles—The Case of Nanjing
Determining the spatiotemporal deployment strategy for dockless shared bicycles in urban blocks has always been a focal point for city managers and planners. Extensive research has delved into the usage patterns in terms of time and space, deduced travel purposes, and scrutinized the relationship between trips and the built environment. The elements of the built environment are significantly correlated with the starting and ending points of dockless shared bicycle trips, leading to a scarcity of shared bicycles in areas that are more frequently used as starting points and an abundance of idle bicycles in areas that serve as endpoints. This paper posits that the idle state of shared bicycles is as important as their usage. Utilizing a case study of Xinjiekou Central District in Nanjing, China, we propose a framework for analyzing the temporal and spatial usage and idleness of shared bicycles. We also discuss the impact of various factors, such as proximity to transit stations, land use, and road accessibility, on the different usage and idle states of dockless shared bicycles. The findings reveal that the public transportation system has a similar influence on both the utilization and idleness of dockless shared bicycles, indicating that areas with a dense concentration of transportation services experience greater demand for shared bicycles as both origins and destinations. The influence of other factors on the usage and idleness of dockless shared bicycles varies significantly, resulting in either a shortage or surplus of these bicycles. Consequently, based on the findings regarding the use and idleness of dockless shared bicycles, we formulate a redistribution and zone-based management strategy for shared bicycles. This paper offers new insights into the spatiotemporal distribution and utilization of shared bicycles under the influence of different built environments, contributing to the further optimization of dockless shared bicycle resource allocation.
- 25 August 2024
- Published by MDPI AG in ISPRS International Journal of Geo-Information
- Vol. 13 (9) , 301
Open AccessA Study on the Spatiotemporal Distribution and Usage Pattern of Dockless Shared Bicycles—The Case of Nanjing
Determining the spatiotemporal deployment strategy for dockless shared bicycles in urban blocks has always been a focal point for city managers and planners. Extensive research has delved into the usage patterns in terms of time and space, deduced travel purposes, and scrutinized the relationship between trips and the built environment. The elements of the built environment are significantly correlated with the starting and ending points of dockless shared bicycle trips, leading to a scarcity of shared bicycles in areas that are more frequently used as starting points and an abundance of idle bicycles in areas that serve as endpoints. This paper posits that the idle state of shared bicycles is as important as their usage. Utilizing a case study of Xinjiekou Central District in Nanjing, China, we propose a framework for analyzing the temporal and spatial usage and idleness of shared bicycles. We also discuss the impact of various factors, such as proximity to transit stations, land use, and road accessibility, on the different usage and idle states of dockless shared bicycles. The findings reveal that the public transportation system has a similar influence on both the utilization and idleness of dockless shared bicycles, indicating that areas with a dense concentration of transportation services experience greater demand for shared bicycles as both origins and destinations. The influence of other factors on the usage and idleness of dockless shared bicycles varies significantly, resulting in either a shortage or surplus of these bicycles. Consequently, based on the findings regarding the use and idleness of dockless shared bicycles, we formulate a redistribution and zone-based management strategy for shared bicycles. This paper offers new insights into the spatiotemporal distribution and utilization of shared bicycles under the influence of different built environments, contributing to the further optimization of dockless shared bicycle resource allocation.
- Open Access
Exploring the Land Cover Material Interaction of Urban Open Space on the Thermal Comfort of Crowds in High-Temperature Environments and Retrofit Strategies: Two Case Studies in the Nanjing Xinjiekou District
The increased frequency of extreme hot weather events in recent years poses a significant threat to the lives and health of urban residents. Consequently, the thermal comfort of urban open areas has garnered growing attention. The ground material in these urban open areas directly impacts the thermal environment, which significantly influences the comfort of crowds. This study aimed to assess the effect of land cover materials in urban center squares on the thermal comfort of people in high-temperature conditions. Eight types of land cover materials were selected from the two urban squares in the central district of Nanjing Xinjiekou. Physiological equivalent temperature (PET) calculations were performed by measuring the surface temperature, the air temperature, the humidity, and other relevant data to evaluate population thermal comfort. The findings indicated that grass provided the highest thermal comfort, with PET scores ranked as follows, from low to high: grass, permeable bricks, granite, concrete, basalt, bluestone, andesite, and asphalt. Additionally, factors such as color, roughness, and shade within the same material also impacted thermal comfort. Subsequently, using the ENVI-met 5.1 software, surface materials exhibiting superior thermal comfort were simulated for replacement, aiming to confirm the experimental results and propose retrofit strategies for improving urban square thermal comfort by optimizing material selection. The outcomes of this study hold significant implications for urban open space design and the overall well-being of city dwellers. The thermal environment in urban centers during high-temperature conditions can be improved by optimizing the choice of land cover materials in urban open areas, thereby enhancing the comfort of the population.
Open AccessExploring the Land Cover Material Interaction of Urban Open Space on the Thermal Comfort of Crowds in High-Temperature Environments and Retrofit Strategies: Two Case Studies in the Nanjing Xinjiekou District
The increased frequency of extreme hot weather events in recent years poses a significant threat to the lives and health of urban residents. Consequently, the thermal comfort of urban open areas has garnered growing attention. The ground material in these urban open areas directly impacts the thermal environment, which significantly influences the comfort of crowds. This study aimed to assess the effect of land cover materials in urban center squares on the thermal comfort of people in high-temperature conditions. Eight types of land cover materials were selected from the two urban squares in the central district of Nanjing Xinjiekou. Physiological equivalent temperature (PET) calculations were performed by measuring the surface temperature, the air temperature, the humidity, and other relevant data to evaluate population thermal comfort. The findings indicated that grass provided the highest thermal comfort, with PET scores ranked as follows, from low to high: grass, permeable bricks, granite, concrete, basalt, bluestone, andesite, and asphalt. Additionally, factors such as color, roughness, and shade within the same material also impacted thermal comfort. Subsequently, using the ENVI-met 5.1 software, surface materials exhibiting superior thermal comfort were simulated for replacement, aiming to confirm the experimental results and propose retrofit strategies for improving urban square thermal comfort by optimizing material selection. The outcomes of this study hold significant implications for urban open space design and the overall well-being of city dwellers. The thermal environment in urban centers during high-temperature conditions can be improved by optimizing the choice of land cover materials in urban open areas, thereby enhancing the comfort of the population.
- Open Access
- 3 February 2024
- Published by MDPI AG in ISPRS International Journal of Geo-Information
- Vol. 13 (2) , 48
Multidimensional Spatial Vitality Automated Monitoring Method for Public Open Spaces Based on Computer Vision Technology: Case Study of Nanjing’s Daxing Palace Square
Assessing the vitality of public open spaces is critical in urban planning and provides insights for optimizing residents’ lives. However, prior research has fragmented study scopes and lacks fine-grained behavioral data segmentation capabilities and diverse vitality dimension assessments. We utilized computer vision technology to collect fine-grained behavioral data and proposed an automated spatial vitality monitoring framework based on discrete trajectory feature points. The framework supported the transformation of trajectory data into four multidimensional vitality indicators: crowd heat, resident behavior ratio, movement speed, and spatial participation. Subsequently, we designed manual validation mechanisms to demonstrate the monitoring framework’s efficacy and utilized the results to explore the changes in vitality, and the influencing factors, in a small public space. Discrete trajectory feature points effectively addressed the literature’s fragmented study scope and limited sample size issues. Spatial boundaries had a significantly positive impact on spatial vitality, confirming the “boundary effect” theory. The peak spatial vitality periods were from 08:30 to 09:30 and from 17:30 to 18:30. A higher enclosure degree and better rest facilities positively impacted spatial vitality, while a lower enclosure degree did not consistently suppress spatial vitality in all situations. Overall, spatial features and spatial vitality have a complex nonlinear relationship.
- 3 February 2024
- Published by MDPI AG in ISPRS International Journal of Geo-Information
- Vol. 13 (2) , 48
Open AccessMultidimensional Spatial Vitality Automated Monitoring Method for Public Open Spaces Based on Computer Vision Technology: Case Study of Nanjing’s Daxing Palace Square
Assessing the vitality of public open spaces is critical in urban planning and provides insights for optimizing residents’ lives. However, prior research has fragmented study scopes and lacks fine-grained behavioral data segmentation capabilities and diverse vitality dimension assessments. We utilized computer vision technology to collect fine-grained behavioral data and proposed an automated spatial vitality monitoring framework based on discrete trajectory feature points. The framework supported the transformation of trajectory data into four multidimensional vitality indicators: crowd heat, resident behavior ratio, movement speed, and spatial participation. Subsequently, we designed manual validation mechanisms to demonstrate the monitoring framework’s efficacy and utilized the results to explore the changes in vitality, and the influencing factors, in a small public space. Discrete trajectory feature points effectively addressed the literature’s fragmented study scope and limited sample size issues. Spatial boundaries had a significantly positive impact on spatial vitality, confirming the “boundary effect” theory. The peak spatial vitality periods were from 08:30 to 09:30 and from 17:30 to 18:30. A higher enclosure degree and better rest facilities positively impacted spatial vitality, while a lower enclosure degree did not consistently suppress spatial vitality in all situations. Overall, spatial features and spatial vitality have a complex nonlinear relationship.