A Method for Intelligent Road Network Selection Based on Graph Neural Network
Bibliographic Data
| ID | 22032700 |
|---|---|
| Authors | Xuan Guo (0000-0002-7969-4257, Zhengzhou University), Junnan Liu (0009-0005-7629-947X, Zhengzhou University, corresponding author), Fang Wu (0000-0002-8436-7293, Zhengzhou University), Haizhong Qian (0000-0002-1255-7872, PLA Information Engineering University) |
| Year | 2023 |
| Volume | 12 |
| Issue | 8 |
| Pages | 336 |
| Publication date | 2023-08-11 |
| 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/ijgi12080336 |
| OpenAlex | W4385758501 |
| Language | EN |
| Citations received | 6 |
| References cited | 26 |
As an essential role in cartographic generalization, road network selection produces basic geographic information across map scales. However, the previous selection methods could not simultaneously consider both attribute characteristics and spatial structure. In light of this, an intelligent road network selection method based on a graph neural network (GNN) is proposed in this paper. Firstly, the selection case is designed to construct a sample library. Secondly, some neighbor sampling and aggregation rules are developed to update road features. Then, a GNN-based selection model is designed to calculate classification labels, thus completing road network selection. Finally, a few comparative analyses with different selection methods are conducted, verifying that most of the accuracy values of the GNN model are stable over 90%. The experiments indicate that this method could aggregate stroke nodes and their neighbors together to synchronously preserve semantic, geometric, and topological features of road strokes, and the selection result is closer to the reference map. Therefore, this paper could bridge the distance between deep learning and cartographic generalization, thus facilitating a more intelligent road network selection method
Artificial neural network · Cartographic generalization · Data mining · Generalization · Graph · Machine learning · Automated Road and Building Extraction · Computer Science · Data Management and Algorithms · Geographic Information Systems Studies · Mathematics · Artificial Intelligence · Theoretical Computer Science
Ve-GCN
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A graph convolutional neural network for classification of building patterns using spatial vector data
Application of AHP to Road Selection
Deep Graph Convolutional Networks for Accurate Automatic Road Network Selection
Integrating Thematic, Geometric, and Topological Information in the Generalization of Road Networks
Analysis of Urban Road Networks to Support Cartographic Generalization
Road network selection for medium scales using an extended stroke-mesh combination algorithm
| Unique citing works | 6 |
|---|---|
| Citations per year | 3 |
| Citation span | 2024 - 2025 (2) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 6 |