Optical　methods　are　frequently　used　as　a　routine　method　to　obtain　the　elementary　sampling　unit　(ESU)　leaf　area　index　(LAI)　of　forests.　However,　few　studies　have　attempted　to　evaluate　whether　the　ESU　LAI　obtained　from　optical　methods　matches　the　accuracy　required　by　the　LAI　map　product　validation　community.　In　this　study,　four　commonly　used　optical　methods,　including　digital　hemispherical　photography　(DHP),　digital　cover　photography　(DCP),　tracing　radiation　of　canopy　and　architecture　(TRAC)　and　multispectral　canopy　imager　(MCI),　were　adopted　to　estimate　the　ESU　(25　m　x　25　m)　LAI　of　five　Larix　principis-rupprechtii　forests　with　contrasting　structural　characteristics.　The　impacts　of　three　factors,　namely,　inversion　model,　canopy　element　or　woody　components　clumping　index　(Omega(e)　or　Omega(w))　algorithm,　and　the　woody　components　correction　method,　on　the　ESU　LAI　estimation　of　the　four　optical　methods　were　analyzed.　Then,　the　LAI　derived　from　the　four　optical　methods　was　evaluated　using　the　LAI　obtained　from　litter　collection　measurements.　Results　show　that　the　performance　of　the　four　optical　methods　in　estimating　the　ESU　LAI　of　the　five　forests　was　largely　affected　by　the　three　factors.　The　accuracy　of　the　LAI　obtained　from　the　DHP　and　MCI　strongly　relied　on　the　inversion　model,　the　Omega(e)　or　Omega(w)　algorithm,　and　the　woody　components　correction　method　adopted　in　the　estimation.　Then　the　best　Omega(e)　or　Omega(w)　algorithm,　inversion　model　and　woody　components　correction　method　to　be　used　to　obtain　the　ESU　LAI　of　L.　principis-rupprechtii　forests　with　the　smallest　root　mean　square　error　(RMSE)　and　mean　absolute　error　(MAE)　were　identified.　Amongst　the　three　typical　woody　components　correction　methods　evaluated　in　this　study,　the　woody-to-total　area　ratio　obtained　from　the　destructive　measurements　is　the　most　effective　method　for　DHP　to　derive　the　ESU　LAI　with　the　smallest　RMSE　and　MAE.　In　contrast,　using　the　woody　area　index　obtained　from　the　leaf-off　DHP　or　DCP　images　as　the　woody　components　correction　method　would　result　in　a　large　LAI　underestimation.　TRAC　and　MCI　outperformed　DHP　and　DCP　in　the　ESU　LAI　estimation　of　the　five　forests,　with　the　smallest　RMSE　and　MAE.　All　the　optical　methods,　except　DCP,　are　qualified　to　obtain　the　ESU　LAI　of　L.　principis-rupprechtii　forests　with　an　MAE　of　＜20%　that　is　required　by　the　global　climate　observation　system.　None　of　the　optical　methods,　except　TRAC,　show　the　potential　to　obtain　the　ESU　LAI　of　L.　principis-rupprechtii　forests　with　an　MAE　of　＜5%.