NDLI: Urban change detection using coherence and intensity characteristics of multi-temporal SAR imagery

Content Provider	IEEE Xplore Digital Library
Author	He, M. He, X.F.
Copyright Year	2009
Description	Author affiliation: Institute of Satellite Navigation & Spatial Information System, Hohai University, China (He, M.; He, X.F.)
Abstract	Change detection using multi-temporal SAR images is one of the most important applications of remote sensing technology. A new method for unsupervised change detection in urban area with multi-temporal SAR images is proposed in this paper. The method operates in two steps: change measures computation and unsupervised 2-D thresholding. In the first step, two change measures, backscattering intensity variation and long-term coherence variation, are defined. In the second step, an unsupervised 2-D thresholding technique based on maximum 2-D Fuzzy entropy criterion is introduced, which is performed on the two difference images derived from the two change measures to produce an accurate change-detection map with two classes “change” and “non-change”. The parameters of Fuzzy entropy are optimized by genetic algorithm (GA). The effectiveness of the new method is validated by four ERS SAR images of Nanjing area acquired in 1997 and 1999.
Starting Page	840
Ending Page	843
File Size	312934
Page Count	4
File Format	PDF
ISBN	9781424427314
DOI	10.1109/APSAR.2009.5374186
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation Urban areas Change detection InSAR Satellite navigation systems Entropy Synthetic aperture radar interferometry Helium Remote sensing Information systems 2-D Fuzzy entropy Layout Coherence GA Backscattering intensity Backscatter
Content Type	Text
Resource Type	Article

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