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Proceedings Paper

Urban change detection using multitemporal ERS-1/2 InSAR data
Author(s): Liming Jiang; Mingsheng Liao; Hui Lin; An Zhao
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Paper Abstract

In this paper, a new approach for unsupervised change-detection using multitemporal InSAR data is proposed, of which the significant characteristics is joint use of backscattering temporal intensity and long-term coherence based on 2-D (two dimensional) Renyi's entropy. The proposed approach is made up of two steps: feature extraction and unsupervised 2-D thresholding. In the first step, two features are based on the concepts of backscattering intensity variation and long-term coherence variation respectively, and are defined according to the analysis of different signal behavior of interferometric SAR in the presence of land-cover classes within urban area. In the second step, an unsupervised 2-D thresholding technique based on maximum 2-D Renyi's entropy criterion is developed. The thresholding is performed on the two difference images derived from the two features to produce an accurate change-detection map with two classes: changed and no-changed. Primary experimental results, which were obtained from a set of six multitemporal ERS-1/2 SAR images within Shanghai city of China, show the effective of the proposed approach and that ERS-1/2 InSAR data could be exploited for detecting urban land-cover changes.

Paper Details

Date Published: 18 October 2005
PDF: 8 pages
Proc. SPIE 5982, Image and Signal Processing for Remote Sensing XI, 59821B (18 October 2005); doi: 10.1117/12.626983
Show Author Affiliations
Liming Jiang, Wuhan Univ. (China)
Mingsheng Liao, Wuhan Univ. (China)
Hui Lin, Chinese Univ. of Hong Kong (Hong Kong China)
An Zhao, Institute of Geographical Sciences and Natural Resources Research (China)

Published in SPIE Proceedings Vol. 5982:
Image and Signal Processing for Remote Sensing XI
Lorenzo Bruzzone, Editor(s)

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