DocumentCode :
2136167
Title :
Data fusion approach for change detection in multi-temporal ERS-SAR images
Author :
Bujor, F.T. ; Valet, L. ; Trouvw, E. ; Mauris, G. ; Classeau, N. ; Rudant, J.P.
Author_Institution :
Ecole Superieure d´´Ingenieurs d´´Annecy, Univ. de Savoie, Annecy, France
Volume :
6
fYear :
2001
fDate :
2001
Firstpage :
2590
Abstract :
This paper presents a new method to detect changes in multi-temporal satellite SAR images. The proposed approach consists in an extraction step-specific change measures reveal the presence of changing features-followed by a fusion step where these measures and a priori information such as geographical map are merged to detect changes. The method is applied to the detection of deforested areas in tropical rain forest of French Guiana. Results obtained with SAR images from satellites ERS 1/2 are presented at two different scales: on a macroscopic scale for the detection of zones presenting a strong deforestation probability and on a microscopic scale for a segmentation of the main deforested parcels
Keywords :
feature extraction; forestry; image recognition; radar imaging; remote sensing by radar; sensor fusion; spaceborne radar; synthetic aperture radar; vegetation mapping; French Guiana; change detection; change measures; data fusion; deforestation probability; deforested areas; deforested parcels; extraction step; geographical map; macroscopic scale; microscopic scale; multi-temporal ERS-SAR images; satellite SAR images; segmentation; tropical rain forest; Data mining; Geophysical measurements; Image edge detection; Image resolution; Image segmentation; Optical microscopy; Radiometry; Rain; Roads; Satellite broadcasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-7031-7
Type :
conf
DOI :
10.1109/IGARSS.2001.978098
Filename :
978098
Link To Document :
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