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Proceedings Paper

Change detection and backscatter modeling applied to forest monitoring by SAR
Author(s): Shaun Quegan; K. D. Grover
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Paper Abstract

The use of the ERS-1 C band SAR for monitoring tropical forest areas is assessed, using three ERS images from the Tapajos region of Amazonia gathered in 1992. Forest areas display a very stable RCS, while non-forest areas in some cases exhibit changes which appear to be associated with soil moisture variations. Discrimination between forest and non-forest is greatest after a dry period. Because of distortions in RCS caused by topography, change detection provides a more useful discrimination approach than RCS differences on single images. A number of automatic change detection techniques are compared and their ability to classify forest and non-forest are quantitatively assessed, assuming that a forest map inferred from a 1992 Landsat TM image is correct. Block averaging followed by image ratioing provides a reasonable approach to detecting the large scale structure of the image, but simulated annealing provides improved performance at a computational cost which is becoming competitive with simpler methods. Approximately 50% of the non-forest region can be detected from the ERS-1 images. This figure may be improved by more frequent image acquisition, but there are fundamental limitations in using C band data, which would be lessened by using longer wavelengths.

Paper Details

Date Published: 21 November 1995
PDF: 11 pages
Proc. SPIE 2584, Synthetic Aperture Radar and Passive Microwave Sensing, (21 November 1995); doi: 10.1117/12.227133
Show Author Affiliations
Shaun Quegan, Univ. of Sheffield (United Kingdom)
K. D. Grover, Univ. of Sheffield (United Kingdom)

Published in SPIE Proceedings Vol. 2584:
Synthetic Aperture Radar and Passive Microwave Sensing
Giorgio Franceschetti; Christopher John Oliver; James C. Shiue; Shahram Tajbakhsh, Editor(s)

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