Vector water body type recognition integrating terrain features and spatial relationships

Peirong Jia; Nina Meng

doi:10.1117/12.3032134

3 June 2024 Vector water body type recognition integrating terrain features and spatial relationships

Peirong Jia, Nina Meng

Proceedings Volume 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024); 131700A (2024) https://doi.org/10.1117/12.3032134
Event: Third International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 2024, Wuhan, China

Abstract

Aiming at the problem of intelligent generation of semantic information of vector planar water bodies, a graph neural network method that integrates morphological features, terrain characteristics, and spatial relationship features is studied. This method can generate more detailed type information under the broad category of planar water bodies, including Three categories: lakes, reservoirs, and ponds. Experimental results show that this method can effectively distinguish types of planar water bodies and has higher accuracy than existing methods, providing a new idea for the intelligent generation of semantic information about water bodies.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Peirong Jia and Nina Meng "Vector water body type recognition integrating terrain features and spatial relationships", Proc. SPIE 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 131700A (3 June 2024); https://doi.org/10.1117/12.3032134

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