Multi-sensor monitoring of humid tropical forests: A case study of Jambi, Sumatra

This paper describes a pre-launch evaluation of ADEOS II Global Imager (GLI) for the assessment of biomass and carbon amount in humid tropical forests and associated ecosystems. Since most of the GLI wavebands correspond to the visible wavelength region, cloud cover will prohibit optimum use of the data unless it can be combined on a periodic basis with radar imagery for cloud-penetration. The research examines the six visible waveband of LANDSAT TM corresponding to those of GLI, in conjunction with radar data from ERS-SAR to provide an algorithm for identifying forest ecosystems in a study area in Central Sumatra. The findings show that ERS data can improve the accuracy of land cover class identification in tropical forest ecosystems as well as update information on deforestation.