Abstract: In this study, approaches of retrieving forest canopy LAI (leaf area index) were investigated using remote sensing data over Wuying forest in the Lesser Khingan as a case study. We firstly calculated the forest canopy reflectivity using 4-Scale model in combination of MODIS (Moderate Resolution Imaging Spectroradiometer) BRDF (bidirectional reflectance distribution function) product. And then three wellknown vegetation indices (VIs) were obtained from the forest canopy reflectivity. Finally, four models were examined in the forest canopy LAI retrieving using the canopy VIs and onsite canopy LAI measurements. The results showed that the model using quadratic polynomial and simple ratio (SR) VI was  the best LAI retrieving model among the four models. Furthermore, the accuracy of LAI estimate could be improved using canopy reflectivity instead of the whole surface reflectivity, with the coefficient of determination (R²) increasing from 0.38 to 0.54. The mean canopy LAI in the study area ranges from 2.38 to 12.67, with an average of 6.52, and the relatively higher LAI values were found in the deciduous forest area.

Key words: index system, China., regionalization plan, soil environmental quality regionalization, soil environmental function