Comparison of estimating forest above-ground biomass over montane area by two non-parametric methods

Forest biomass reflects the ecological succession and human disturbance of the forest, and can fully embody the quality of forest ecosystem environment. The Qilian Mountain forest reserve at upper reaches of the Heihe River Basin was selected for the study. Landsat Thematic Mapper 5 (TM) images were selected as the source data, which were rectified by SCS + C terrain radiometric correction. Forest above-ground biomass was estimated using k-nearest neighbor (k-NN) method and support vector regression (SVR) method, respectively. The results show that spectral information of remote sensing image was recovered by the sun-canopy-sensor plus the C (SCS+C) terrain correction which can effectively improve the estimation accuracy of the models regardless of k-NN or SVR. The optimal k-NN method (R
²
=0.54, RMSE=26.62ton/ha) performs better than the optimal SVR method (R
²
=0.51, RMSE=27.45ton/ha).