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Proceedings Paper

A method of detecting land use change of remote sensing images based on texture features and DEM
Author(s): Dong-ming Huang; Chun-tao Wei; Jun-chen Yu; Jian-lin Wang
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Paper Abstract

In this paper, a combination method, between the neural network and textures information, is proposed to remote sensing images classification. The methodology involves an extraction of texture features using the gray level co-occurrence matrix and image classification with BP artificial neural network. The combination of texture features and the digital elevation model (DEM) as classified bands to neural network were used to recognized different classes. This scheme shows high recognition accuracy in the classification of remote sensing images. In the experiments, the proposed method was successfully applied to remote sensing image classification and Land Use Change Detection, in the meanwhile, the effectiveness of the proposed method was verified.

Paper Details

Date Published: 9 December 2015
PDF: 6 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 980822 (9 December 2015); doi: 10.1117/12.2214637
Show Author Affiliations
Dong-ming Huang, Chongqing Jiaotong Univ. (China)
Chun-tao Wei, Chongqing Jiaotong Univ. (China)
Guilin Univ. of Technology (China)
Jun-chen Yu, Chongqing Jiaotong Univ. (China)
Jian-lin Wang, Chongqing Jiaotong Univ. (China)

Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)

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