NDLI: OBJECT-BASED FOREST CHANGE DETECTION USING HIGH RESOLUTION SATELLITE IMAGES

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OBJECT-BASED FOREST CHANGE DETECTION USING HIGH RESOLUTION SATELLITE IMAGES

Content Provider	Scilit
Author	Chehata, N. Orny, C. Boukir, S. Guyon, D.
Copyright Year	2013
Description	An object-based approach for forest disaster change detection using High Resolution (HR) satellite images is proposed. An automatic feature selection process is used to optimize image segmentation via an original calibration-like procedure. A multitemporal classification then enables the separation of wind-fall from intact areas based on a new descriptor that depends on the level of fragmentation of the detected regions. The mean shift algorithm was used in both the segmentation and the classification processes. The method was tested on a high resolution Formosat-2 multispectral satellite image pair acquired before and after the Klaus storm. The obtained results are encouraging and the contribution of high resolution images for forest disaster mapping is discussed.
Ending Page	54
Page Count	6
Starting Page	49
e-ISSN	21949034
DOI	10.5194/isprsarchives-xxxviii-3-w22-49-2011
Alternate Webpage(s)	https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-3-W22/49/2011/isprsarchives-XXXVIII-3-W22-49-2011.pdf
Journal	The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Volume Number	XXXVIII-3/
Language	English
Publisher	Copernicus GmbH
Publisher Date	2013-04-26
Access Restriction	Open
Subject Keyword	Cybernetical Science Satellite Images High Resolution
Content Type	Text
Resource Type	Article

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