A Heuristic Approach for Resolving Spatial Conflicts of Buildings in Urban Villages
Bibliographic Data
| ID | 22032644 |
|---|---|
| Authors | Wende Li (0000-0003-0097-7308, Lanzhou Jiaotong University), Haowen Yan (0000-0002-2792-3425, Lanzhou Jiaotong University, corresponding author), Xiaomin Lu (0000-0002-6206-251X, Lanzhou Jiaotong University), Yilang Shen (0000-0002-9699-8551, Sun Yat-sen University) |
| Year | 2023 |
| Volume | 12 |
| Issue | 10 |
| Pages | 392 |
| Publication date | 2023-09-27 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi12100392 |
| OpenAlex | W4387119358 |
| Language | EN |
| Citations received | 3 |
| References cited | 33 |
Building displacement is a common operation to resolve the spatial conflicts between map features, and it has important theoretical value and practical application significance for multi-scale mapping. The prerequisite for a successful displacement operation is that there is extra space around the conflicting buildings into which they can be displaced. Otherwise, additional generalization operators need to be combined to resolve spatial conflicts. Based on this idea, this study proposes a new heuristic spatial conflict resolution framework that mainly resolves the spatial conflicts between buildings and other features in urban villages by combining three cartographic generalization operators: selection, displacement, and aggregation. This method first reduces the density of buildings in the block through selection operation, then resolves the spatial conflicts between buildings and other features through displacement operation, and finally, the aggregation operation is performed to eliminate any remaining conflicts and newly generated conflicts. Experiments were carried out using real urban village data, and visual inspection and quantitative analysis were used to evaluate the experimental results. The evaluation results show that the proposed framework can not only resolve spatial conflicts well, but also maintain the spatial distribution and area balance of the buildings in urban villages
Cartographic generalization · Cartography · City block · Data mining · Generalization · Geography · Heuristic · Automated Road and Building Extraction · Computer Science · Data Management and Algorithms · Geographic Information Systems Studies · Mathematics · Artificial Intelligence
Flow-Based Community Search Approach for Functionally Cohesive Building Group Recognition
A Novel Approach to Urban Village Extraction and Generalization from Digital Line Graphics Using the Computational Geometric Method and the Modified Hausdorff Distance
Collaborative Methods of Resolving Road Graphic Conflicts Based on Cartographic Rules and Generalization Operations
A graph convolutional neural network for classification of building patterns using spatial vector data
A Method for Regularizing Buildings through Combining Skeleton Lines and Minkowski Addition
A Zonal Displacement Approach via Grid Point Weighting in Building Generalization
Solving Space Conflicts in Map Generalization
Improving settlement selection for small-scale maps using data enrichment and machine learning
| Unique citing works | 3 |
|---|---|
| Citations per year | 1.5 |
| Citation span | 2024 - 2025 (2) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |