The JERS Amazon Multi-season Mapping Study (JAMMS): observation strategies and data characteristics

The Japanese Earth Resources Satellite (JERS-1) Amazon Multiseason Mapping Study (JAMMS), part of the Global Rain Forest Mapping (GRFM) project led by the National Space Development Agency of Japan (NASDA), had an ambitious agenda to map the entire Amazon river floodplain (and surrounding areas) twice at high resolution. The observation strategy carried out by NASDA for the JAMMS project and the other elements of the GRFM project (1995-1997) constituted the first time that a spaceborne Synthetic Aperture Radar (SAR) successfully implemented a continental scale, coordinated seasonal mapping campaign. This observation strategy, chosen around the flooding cycle of the major river systems, was designed to provide the first high-resolution measurement of inundation extent by the Amazon river and its tributaries. In order for the scientific community at large to be able to exploit this dataset, the characteristics of the data (resolution, radiometric and geometric calibration, coverage, and ability to be mosaicked) must be well understood. We find that the quantization of the Alaska SAR Facility (ASF) imagery impacts the range of backscatter values that may be observed, in contrast to the NASDA processed imagery. The noise equivalent sigma(0) is -15 dB at worst, but improves to about -20 dB at the centre of the swath. The resolution of the ASF imagery is slightly worse than that processed by NASDA. The initial geolocation accuracy of the ASF processed imagery is quite poor, but may be improved during the mosaicking process. The relative radiometric calibration of the data may be improved to about 0.2 dB by comparing the calibration of overlapping imagery, and through a careful analysis of cross-track trends in the data.