Estimating growing stock volume in a Bangladesh forest site using Landsat TM and field-measured data

Abstract

ABSTRACT Estimation of forest Growing Stock (GS) is important in understanding the ecological dynamics and productive capacity of forests. Instead of the traditional cost-effective and time consuming ground based measurements, satellite images are being increasingly used in estimating many forest parameters including GS. This study estimates forest GS at Khadimnagar national park, Sylhet, Bangladesh using regression relationship of vegetation indices (VIs) of Landsat Thematic Mapper (TM) image with field-measured GS. Among the VIs, NDVI (Normalized Difference Vegetation Index) was found to be the best predictor of forest GS with workable accuracy (r 2 = 0.77, P <0.000), while IRI (Infra-red Index) was the poorest estimator (r 2 = 0.38, P < 0.001). This approach could be operationally used for wider scale estimation of GS in similar forest areas of Bangladesh

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