Jianbo Tang
Biographic Data
| ID | 3635382 |
|---|---|
| NAME | Jianbo Tang |
| GIVEN NAMES | Jianbo |
| FAMILY NAME | Tang |
| SIGNATURE | TANG J |
| AFFILIATIONS | Central South University |
| ORCID | 0000-0002-9780-0439 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 4 |
| WORKS AS AUTHOR | 12 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Function-intensive urban form exacerbates spatial inequality of urban service accessibility
Three-Dimensional Outdoor Pedestrian Road Network Map Construction Based on Crowdsourced Trajectory Data
Due to the complexity of outdoor environments, we still face challenges in collecting up-to-date outdoor road network maps because of high data collection costs, resulting in a lack of navigation road network maps in outdoor scenarios. Existing road network extraction methods are mainly divided into trajectory data-based and remote sensing image-based methods. Due to factors such as tree occlusion, methods based on remote sensing images struggle …
A Building Group Recognition Method Integrating Spatial and Semantic Similarity
Recognition and detection of building groups are core tasks in cartographic research. Current recognition methods that rely on spatial and geometric features often neglect semantic aspects, failing to account for the complex relationships between buildings and their real-world semantic associations. This limitation hampers the ability to fully capture human understanding of the real world. Based on this, this paper proposes a novel method for bui…
Revealing Urban Spatial Interaction Characteristics and Crowd Travel Patterns from Trajectory Data
The accelerated urbanization process has raised higher demands for urban planning and management, and a precise understanding of urban spatial interaction characteristics is fundamental to these efforts. How to uncover the frequent interaction patterns between urban spaces, especially those that exhibit stability over time, and reveal the underlying semantic information, remains a pressing challenge, however. This study proposes a time-sliced mul…
Geographical Scene
Geographical analysis often faces challenges in selecting appropriate analysis units due to spatial heterogeneity, autocorrelation, and the modifiable areal unit problem (MAUP). Traditional spatial partitioning or aggregation methods using grids, administrative zones, and traffic analysis zones rely heavily on spatial correlations while neglecting semantic relationships between geographical elements. This limitation hinders their ability to captu…
Coupling Hyperbolic GCN with Graph Generation for Spatial Community Detection and Dynamic Evolution Analysis
Spatial community detection is a method that divides geographic spaces into several sub-regions based on spatial interactions, reflecting the regional spatial structure against the background of human mobility. In recent years, spatial community detection has attracted extensive research in the field of geographic information science. However, mining the community structures and their evolutionary patterns from spatial interaction data remains ch…
Identifying up-to-date urban land-use patterns with visual and semantic features based on multisource geospatial data
Modeling Covid-19 spread using multi-agent simulation with small-world network approach
Our methodology emphasizes the crucial role of timely epidemic interventions in curbing the spread of infectious diseases, notably in the predictive assessment and evaluation of lockdown strategies. Furthermore, this approach adeptly forecasts the influence of varying intervention timings on peak infection rates and total case numbers, accurately reflecting real-world virus transmission patterns. This highlights the importance of proactive measur…
Exploring Crowd Travel Demands Based on the Characteristics of Spatiotemporal Interaction between Urban Functional Zones
As a hot research topic in urban geography, spatiotemporal interaction analysis has been used to detect the hotspot mobility patterns of crowds and urban structures based on the origin-destination (OD) flow data, which provide useful information for urban planning and traffic management applications. However, existing methods mainly focus on the detection of explicit spatial interaction patterns (such as spatial flow clusters) in OD flow data, wi…
Detecting Urban Commercial Districts by Fusing Points of Interest and Population Heat Data with Region-Growing Algorithms
Reasonable urban commercial planning must clarify the location and scope of urban commercial districts (UCDs). However, existing studies typically detect spurious UCDs owing to the bias in a single data source while ignoring the continuity and ambiguity of commercial district boundaries. Therefore, in this study, we designed a two-stage approach for detecting UCDs. First, points of interest and population heat data were fused through hotspot and …
Revealing spatiotemporal correlation of urban roads via traffic perturbation simulation
Recognizing building groups for generalization
Recognition of building groups is a critical step in building generalization. To find building groups, various approaches have been developed based on the principles of grouping (or the Gestalt laws of grouping), and the effectiveness of these approaches needs to be evaluated. This study presents a comparative analysis of nine typical such approaches, including three approaches that only consider proximity principle and six approaches that consid…
Geographical Scene
Geographical analysis often faces challenges in selecting appropriate analysis units due to spatial heterogeneity, autocorrelation, and the modifiable areal unit problem (MAUP). Traditional spatial partitioning or aggregation methods using grids, administrative zones, and traffic analysis zones rely heavily on spatial correlations while neglecting semantic relationships between geographical elements. This limitation hinders their ability to captu…
Recognizing building groups for generalization
Recognition of building groups is a critical step in building generalization. To find building groups, various approaches have been developed based on the principles of grouping (or the Gestalt laws of grouping), and the effectiveness of these approaches needs to be evaluated. This study presents a comparative analysis of nine typical such approaches, including three approaches that only consider proximity principle and six approaches that consid…
Recognizing building groups for generalization
Recognition of building groups is a critical step in building generalization. To find building groups, various approaches have been developed based on the principles of grouping (or the Gestalt laws of grouping), and the effectiveness of these approaches needs to be evaluated. This study presents a comparative analysis of nine typical such approaches, including three approaches that only consider proximity principle and six approaches that consid…
Revealing spatiotemporal correlation of urban roads via traffic perturbation simulation
Exploring Crowd Travel Demands Based on the Characteristics of Spatiotemporal Interaction between Urban Functional Zones
As a hot research topic in urban geography, spatiotemporal interaction analysis has been used to detect the hotspot mobility patterns of crowds and urban structures based on the origin-destination (OD) flow data, which provide useful information for urban planning and traffic management applications. However, existing methods mainly focus on the detection of explicit spatial interaction patterns (such as spatial flow clusters) in OD flow data, wi…
Detecting Urban Commercial Districts by Fusing Points of Interest and Population Heat Data with Region-Growing Algorithms
Reasonable urban commercial planning must clarify the location and scope of urban commercial districts (UCDs). However, existing studies typically detect spurious UCDs owing to the bias in a single data source while ignoring the continuity and ambiguity of commercial district boundaries. Therefore, in this study, we designed a two-stage approach for detecting UCDs. First, points of interest and population heat data were fused through hotspot and …
Coupling Hyperbolic GCN with Graph Generation for Spatial Community Detection and Dynamic Evolution Analysis
Spatial community detection is a method that divides geographic spaces into several sub-regions based on spatial interactions, reflecting the regional spatial structure against the background of human mobility. In recent years, spatial community detection has attracted extensive research in the field of geographic information science. However, mining the community structures and their evolutionary patterns from spatial interaction data remains ch…
Identifying up-to-date urban land-use patterns with visual and semantic features based on multisource geospatial data
Modeling Covid-19 spread using multi-agent simulation with small-world network approach
Our methodology emphasizes the crucial role of timely epidemic interventions in curbing the spread of infectious diseases, notably in the predictive assessment and evaluation of lockdown strategies. Furthermore, this approach adeptly forecasts the influence of varying intervention timings on peak infection rates and total case numbers, accurately reflecting real-world virus transmission patterns. This highlights the importance of proactive measur…
Three-Dimensional Outdoor Pedestrian Road Network Map Construction Based on Crowdsourced Trajectory Data
Due to the complexity of outdoor environments, we still face challenges in collecting up-to-date outdoor road network maps because of high data collection costs, resulting in a lack of navigation road network maps in outdoor scenarios. Existing road network extraction methods are mainly divided into trajectory data-based and remote sensing image-based methods. Due to factors such as tree occlusion, methods based on remote sensing images struggle …
A Building Group Recognition Method Integrating Spatial and Semantic Similarity
Recognition and detection of building groups are core tasks in cartographic research. Current recognition methods that rely on spatial and geometric features often neglect semantic aspects, failing to account for the complex relationships between buildings and their real-world semantic associations. This limitation hampers the ability to fully capture human understanding of the real world. Based on this, this paper proposes a novel method for bui…
Revealing Urban Spatial Interaction Characteristics and Crowd Travel Patterns from Trajectory Data
The accelerated urbanization process has raised higher demands for urban planning and management, and a precise understanding of urban spatial interaction characteristics is fundamental to these efforts. How to uncover the frequent interaction patterns between urban spaces, especially those that exhibit stability over time, and reveal the underlying semantic information, remains a pressing challenge, however. This study proposes a time-sliced mul…
Geographical Scene
Geographical analysis often faces challenges in selecting appropriate analysis units due to spatial heterogeneity, autocorrelation, and the modifiable areal unit problem (MAUP). Traditional spatial partitioning or aggregation methods using grids, administrative zones, and traffic analysis zones rely heavily on spatial correlations while neglecting semantic relationships between geographical elements. This limitation hinders their ability to captu…
Function-intensive urban form exacerbates spatial inequality of urban service accessibility
Computer Science (11 works) · Geography (7 works) · Human Mobility and Location-Based Analysis (6 works) · Artificial Intelligence (5 works) · Data mining (5 works) · Mathematics (5 works) · Geographic Information Systems Studies (4 works) · Cartography (3 works) · Engineering (3 works) · Land Use and Ecosystem Services (3 works)