APPLICATION OF BACKSCATTER AND COHERENCE DATA ON C AND L BAND FOR LANDCOVER IDENTIFICATION IN TROPICS

Use of coherence data from operational satellite based SAR sensors has been experimented both on C and L band to identify landcover in tropics. While coherence data proved useful to improve accuracy in landcover identification, such data are not readily available. On the other hand, integrated use of backcatter data by multiple satellites is readily feasible. The very question to be asked is whether integration of backscatter data on multiple bands (e.g. C and L band) is either inferior or superior to use of coherence data. We therefore still do not have a solid clue to answer to the very question. The aim of this study is to evaluate the performance of "integrated use" of backscatter data on C and L band (by ERS and JERS respectively) to identify landcover, vis-a-vis the same by combination of backscatter and coherence data by single satellite. The study was carried out for an area in the southern part of the Sumatra Island, Indonesia. The area has been intensively converted from natural forest into plantation. Five categories of landcover exist in this study area. By ERS-1, only 2 or 3 classes may be identified with the backscatter data alone, while adding the coherence data could delineate 4 classes. By JERS-1, only 3 to 4 classes may be identified with the backscatter data alone, while 4 classes could be clearly delineated by adding the coherence data. By integrating backscatter data on two bands, 4 to 5 classes may be identified. It represents the best results among cases examined. The outcome of the study suggests that integrated use of backscatter data on two bands by ERS and JERS is as powerful as use of backscatter and coherence data on single band by one of these satellite.