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21 November 1995 Change detection and backscatter modeling applied to forest monitoring by SAR
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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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shaun Quegan and K. D. Grover "Change detection and backscatter modeling applied to forest monitoring by SAR", Proc. SPIE 2584, Synthetic Aperture Radar and Passive Microwave Sensing, (21 November 1995); https://doi.org/10.1117/12.227133
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