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Proceedings Paper

Automatic landslide and mudflow detection method via multichannel sparse representation
Author(s): Chen Chao; Jianjun Zhou; Zhuo Hao; Bo Sun; Jun He; Fengxiang Ge
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Paper Abstract

Landslide and mudflow detection is an important application of aerial images and high resolution remote sensing images, which is crucial for national security and disaster relief. Since the high resolution images are often large in size, it’s necessary to develop an efficient algorithm for landslide and mudflow detection. Based on the theory of sparse representation and, we propose a novel automatic landslide and mudflow detection method in this paper, which combines multi-channel sparse representation and eight neighbor judgment methods. The whole process of the detection is totally automatic. We make the experiment on a high resolution image of ZhouQu district of Gansu province in China on August, 2010 and get a promising result which proved the effective of using sparse representation on landslide and mudflow detection.

Paper Details

Date Published: 20 October 2015
PDF: 7 pages
Proc. SPIE 9644, Earth Resources and Environmental Remote Sensing/GIS Applications VI, 96441J (20 October 2015); doi: 10.1117/12.2194239
Show Author Affiliations
Chen Chao, Naval Academy of Armament (China)
Jianjun Zhou, Naval Academy of Armament (China)
Zhuo Hao, Beijing Normal Univ. (China)
Bo Sun, Beijing Normal Univ. (China)
Jun He, Beijing Normal Univ. (China)
Fengxiang Ge, Beijing Normal Univ. (China)


Published in SPIE Proceedings Vol. 9644:
Earth Resources and Environmental Remote Sensing/GIS Applications VI
Ulrich Michel; Karsten Schulz; Manfred Ehlers; Konstantinos G. Nikolakopoulos; Daniel Civco, Editor(s)

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