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Proceedings Paper

Landslides detection: a case study in Conghua city of Pearl River delta
Author(s): Jie Dou; Junping Qian; Hongou Zhang; Shuisen Chen; Xiaozhan Zheng; Junfeng Zhu; Zhilin Xie; Yi Zou
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Paper Abstract

Landslide is a typical geological disaster that has adverse effect on lives and properties, generating both direct and indirect economic losses in mountainous regions every year. Comparing to other geological disasters, landslides are considerably smaller in scale and more dispersed. The characteristics of landslide render detection and identification of landslides challenging. In this paper, object-based image analysis is used to detect landslide sites using remote sensing images. Firstly, multi-scale image segmentation was performed on the 0.61-meter Quickbird (QB) image of the study area and over tens of spatial, spectral, shape and texture features were extracted based on the segmented image objects. Secondly, 11 optimized features for landslides classification was selected using genetic algorithm (GA), which gives the best fitness value for landslides classification. Thirdly, in-situ landslides observation results were used as typical cases and cased-based-reasoning (CBR) classification was applied on all segmented image objects, from large scale to small scale. Finally, classification accuracy was evaluated over the whole study area. In conclusion, CBR method is able to detect landslides successfully using high resolution images. The CBR method proposed in this paper could achieve better classification accuracy than traditional supervised classification.

Paper Details

Date Published: 9 October 2009
PDF: 11 pages
Proc. SPIE 7471, Second International Conference on Earth Observation for Global Changes, 74711K (9 October 2009); doi: 10.1117/12.836328
Show Author Affiliations
Jie Dou, Guangzhou Institute of Geography (China)
Guangzhou Institute of Geochemistry, CAS (China)
Graduate Univ. of the Chinese Academy of Sciences (China)
Junping Qian, Guangzhou Institute of Geography (China)
Hongou Zhang, Guangzhou Institute of Geography (China)
Geospatial Information Technology and Application of Public Lab. of Guangdong (China)
Shuisen Chen, Guangzhou Institute of Geography (China)
Xiaozhan Zheng, Guangzhou Institute of Geography (China)
Junfeng Zhu, Guangzhou Institute of Geography (China)
Zhilin Xie, Guangzhou Institute of Geography (China)
Yi Zou, Guangzhou Institute of Geochemistry, CAS (China)
Graduate Univ. of the Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 7471:
Second International Conference on Earth Observation for Global Changes
Xianfeng Zhang; Jonathan Li; Guoxiang Liu; Xiaojun Yang, Editor(s)

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