Three-Dimensional Deformation Estimation from Multi-Temporal Real-Scene Models for Landslide Monitoring

Autor: Ke Xi, Pengjie Tao, Zhuangqun Niu, Xiaokun Zhu, Yansong Duan, Tao Ke, Zuxun Zhang
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Remote Sensing, Vol 16, Iss 15, p 2705 (2024)
Druh dokumentu: article
ISSN: 2072-4292
DOI: 10.3390/rs16152705
Popis: This study proposes a three-dimensional (3D) deformation estimation framework based on the integration of shape and texture information for real-scene 3D model matching, effectively addressing the issue of deformation assessment in large-scale geological landslide areas. By extracting and merging the texture and shape features of matched points, correspondences between points in multi-temporal real-scene 3D models are established, resolving the difficulties faced by existing methods in achieving robust and high-precision 3D point matching over landslide areas. To ensure the complete coverage of the geological disaster area while enhancing computational efficiency during deformation estimation, a voxel-based thinning method to generate interest points is proposed. The effectiveness of the proposed method is validated through tests on a dataset from the Lijie north hill geological landslide area in Gansu Province, China. Experimental results demonstrate that the proposed method significantly outperforms existing classic and advanced methods in terms of matching accuracy metrics, and the accuracy of our deformation estimates is close to the actual measurements obtained from GNSS stations, with an average error of only 2.2 cm.
Databáze: Directory of Open Access Journals
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