<![CDATA[This work aims to estimate Above Ground biomass (AGB) of a tropicalrainforest in East Kalimantan, Indonesia using equation derived from the standvolume prediction and to study the spatial distribution of AGB over aforest area.The potential of remote sensing and field measurement data to predict standvolume and AGB were studied Landsat ElM data were atmospherically correctedusing Dark Object Subtraction (DOS) technique, and topographic corrections wereconducted using C-correction method Stand volume was estimated using field dataand remote sensing data using Levenberg-Marquardt neural networks. Standvolume data was converted into the above ground biomass using available volume- AGB equations. Spatial distribution of the AGB and the error estimate were theninterpolated using kriging. Validated with observation data, the stand volumeestimate showed integration of field measurement and remote sensing data hasbetter prediction than the solitary uses of those data. The AGB estimate showedgood correlations with stand volume, number of stems, and basal area.]]>
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