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Results of a PhD study aimed at developing a system for land cover monitoring in tropical rain forest areas, based on ERS-1 SAR images.
With an increasing demand for the wise and sustainable management of forests, there is a growing need for up-to-date information on the location and extent of the forests and the surrounding land cover and of the changes occurring. Radar remote sensing can provide a viable solution for mapping and monitoring such areas. The system for land cover monitoring in tropical rain forest areas, presented in the thesis, is based on ERS-1 SAR images. The system was developed for an area in the Colombian Amazon. Because of its generic structure, the system can be applied to a variety of other areas as well.
Prior to classification, the ERS-1 images were divided into segments with the RCSEG segmentation algorithm. Each segmented image was classified by the subsequent application of two sets of rules and also taking into account the classification result of the previous image. The first set of rules is based on the relation between land cover structure class and backscatter level, as well as the maximum change in backscatter level over three subsequent images. The second set of rules describes the possible changes in land cover between two moments in time as calculated by the BOSTOS model. Using this second set of rules enables unlikely changes to be excluded and the monitoring result becomes more accurate. The study shows that it is possible to monitor land cover in a tropical rain forest area with ERS-1 images.