One Method of Estimating Vegetation Leaf Area Index from ENVISAT-ASAR Data

One method of estimating vegetation Leaf Area Index (LAI) using ENVISAT-ASAR data was presented based on the ground experiment data in Heihe district, northwest China. Firstly, the vegetation species was analyzed and classified in this area and the category covered the cultural vegetation, shrub, grass, desert, needle forests, and broadleaf forests. With support of experiment data and other materials, the vegetation categories were parameterized and input the MIMICS ( Michigan Microwave Canopy Scattering) model to simulate the backscattering coefficients. The incident angle, water content, and LAI was mainly studied and the dataset was constructed based on the simulation data. Secondly, the accuracy of the dataset was evaluated compared with ground measured data and reference material, and the sensitive difference for different polarized data was calculated. Finally, the method of Look-Up Table (LUT) was used to invert the LAI for all vegetation types and the indicators including inversion errors, uncertainties and Retrieved Index (RI) were acquired and analyzed at the same time. The final result revealed that there are advantages for this method especially for high LAI value and in the cloudy and rainy area.