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).