Biochemical　components　of　Moso　bamboo　(Phyllostachys　pubescens)　are　critical　to　physiological　and　ecological　processes　and　play　an　important　role　in　the　material　and　energy　cycles　of　the　ecosystem.　The　coupled　PROSPECT　with　SAIL　(PROSAIL)　radiative　transfer　model　is　widely　used　for　vegetation　biochemical　component　content　inversion.　However,　the　presence　of　leaf-eating　pests,　such　as　Pantana　phyllostachysae　Chao　(PPC),　weakens　the　performance　of　the　model　for　estimating　biochemical　components　of　Moso　bamboo　and　thus　must　be　considered.　Therefore,　this　study　considered　pest-induced　stress　signals　associated　with　Sentinel-2A/B　images　and　field　data　and　established　multiple　sets　of　biochemical　canopy　reflectance　look-up　tables　(LUTs)　based　on　the　PROSAIL　framework　by　setting　different　parameter　ranges　according　to　infestation　levels.　Quantitative　inversions　of　leaf　area　index　(LAI),　leaf　chlorophyll　content　(LCC),　and　leaf　equivalent　water　thickness　(LEWT)　were　derived.　The　scale　conversions　from　LCC　to　canopy　chlorophyll　content　(CCC)　and　LEWT　to　canopy　equivalent　water　thickness　(CEWT)　were　calculated.　The　results　showed　that　LAI,　CCC,　and　CEWT　were　inversely　related　with　PPC-induced　stress.　When　applying　multiple　LUTs,　the　p-values　were　＜0.01;　the　R2　values　for　LAI,　CCC,　and　CEWT　were　0.71,　0.68,　and　0.65　with　root　mean　square　error　(RMSE)　(normalized　RMSE,　NRMSE)　values　of　0.38　(0.16),　17.56　mu　g　center　dot　cm-2　(0.20),　and　0.02　cm　(0.51),　respectively.　Compared　to　the　values　obtained　for　the　traditional　PROSAIL　model,　for　October,　R2　values　increased　by　0.05　and　0.10　and　NRMSE　decreased　by　0.09　and　0.02　for　CCC　and　CEWT,　respectively　and　RMSE　decreased　by　0.35　mu　g　center　dot　cm-2　for　CCC.　The　feasibility　of　the　inverse　strategy　for　integrating　pest-induced　stress　factors　into　the　PROSAIL　model,　while　establishing　multiple　LUTs　under　different　pest　-induced　damage　levels,　was　successfully　demonstrated　and　can　potentially　enhance　future　vegetation　parameter　inversion　and　monitoring　of　bamboo　forest　health　and　ecosystems.