Abstract: Leaf area index (LAI) is one of the most important structural parameters of terrestrial ecosystem, while the remote sensing retrieval  and the ground optical instrument measurement  and based on canopy gap modelare the effective approaches to rapidly obtain LAI. However, these two approaches can only acquire effective LAI(LAI_e), due to the clumping of vegetation canopy. Taking the experimental forest farm of Northeast Forestry University at Maoershan Mountain in Heilongjiang Province of Northeast China as study site, this paper measured the forest canopy LAI_e by LAI2000, and estimated the LAI by the combination of TRAC (tracing radiation and architecture of canopies) measurement of foliage clumping index. A LAI remote sensing retrieval model was constructed through the analysis of the relationships between different vegetation indices calculated from Landsat5-TM and measured LAI_e. The results showed that at the study site, the LAIof broad leaved forests was close to the LAI_e, but the LAIof needle leaved forests was 27% larger than the LAI_e. Reduced simple ratio index (RSR) had the highest relationship with measured LAI_e (R²=0.763, n=23), which could be used as the best predictor of LAI. The LAI at study site increased rapidly with increasing elevation when the elevation was below 400 m, but had a slow increase when the elevation was from 400 m to 750 m. When the elevation was above 750 m, the LAI decreased. There was a significant correlation between the forest canopy LAI and aboveground biomass.

Key words: leaf area index, foliage clumping index, LAI2000, TRAC, Greater Xing’an Mountains, burned area, restoration, carbon storage.