NDLI: Local Spectrum-Trend Similarity Approach for Detecting Land-Cover Change by Using SPOT-5 Satellite Images

Content Provider	IEEE Xplore Digital Library
Author	Penglin Zhang Zhiyong Lv Wenzhong Shi
Copyright Year	2004
Abstract	Spectra-based change detection (CD) methods, such as image difference method and change vector analysis, have been widely used for land-cover CD using remote sensing data. However, the spectra-based approach suffers from a strict requirement of radiometric consistency in the multitemporal images. This letter proposes a new image feature named spectrum trend, which is explored from the spectral values of the image in a local geographic area (e.g., a 3 × 3 sliding window) through raster encoding and curve fitting techniques. The piecewise similarity between the paired local areas in the multitemporal images is calculated by using a sliding window centered at the pixel to generate the change magnitude image. Finally, CD is achieved by a threshold decision or a classified method. This proposed approach, called “local spectrum-trend similarity,” is applied and validated by a case study of land-cover CD in Wuqin District, Tianjin City, China, by using SPOT-5 satellite images. Accuracies of “change” versus “no-change” detection are assessed. Experimental results confirm the feasibility and adaptability of the proposed approach in land-cover CD.
Sponsorship	IEEE Geoscience and Remote Sensing Society
Starting Page	738
Ending Page	742
Page Count	5
File Size	723704
File Format	PDF
ISSN	1545598X
Volume Number	11
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Market research Remote sensing Accuracy Satellites Vectors Earth Educational institutions remote sensing image Change detection (CD) land cover local spectrum-trend similarity (LSTS)
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology

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