Road Network Generalization Method Constrained by Residential Areas
Bibliographic Data
| ID | 22033900 |
|---|---|
| Authors | Zheng Lyu (0000-0001-6641-4423, PLA Information Engineering University), Qun Sun (0000-0002-4372-8865, Institute of Geospatial Information, Information Engineering University, Zhengzhou 450000, China), Sun Qun (PLA Information Engineering University), Jingzhen Ma (0000-0002-2195-0131, PLA Information Engineering University, corresponding author), Qing Xu (0000-0002-8243-6670, PLA Information Engineering University), Yuanfu Li (0000-0003-3709-3733, PLA Information Engineering University), Fubing Zhang (0000-0001-5119-7446, PLA Information Engineering University) |
| Year | 2022 |
| Volume | 11 |
| Issue | 3 |
| Pages | 159 |
| Publication date | 2022-02-22 |
| 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/ijgi11030159 |
| OpenAlex | W4213446930 |
| Language | EN |
| Citations received | 3 |
| References cited | 14 |
Residential areas and road networks have a strong geographical correlation. The development of a single geographical feature could destroy the geographical correlation. It is necessary to establish collaborative generalization models suitable for multiple features. However, existing road network generalization methods for mapping purposes do not fully consider residential areas. Compared with road networks, residential areas have a higher priority in cartographic generalization. In this regard, this study proposes a road network generalization method constrained by residential areas. First, the roads and settlements obtained from clustering residential areas were classified. Next, the importance of the settlements was evaluated and certain settlements were selected as the control features. Subsequently, a geographical network with the settlements as the nodes was built, and the traffic paths between adjacent settlements were searched. Finally, redundant paths between the settlements were simplified, and the visual continuity and topological connectivity were checked. The data of a 1:50,000 road network and residential areas were used as the experimental data. The experimental results demonstrated that the proposed method preserves the overall structure and relative density characteristics of the road network, as well as the geographical correlation between the road network and residential areas
Cartographic generalization · Cartography · Civil engineering · Cluster analysis · Generalization · Geography · Human settlement · Residential area · Transport engineering · Automated Road and Building Extraction · Computer Science · Data Management and Algorithms · Engineering · Geographic Information Systems Studies · Mathematics · Artificial Intelligence
| Unique citing works | 3 |
|---|---|
| Citations per year | 1 |
| Citation span | 2023 - 2024 (2) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |