The Inversion Of Leaf Area Index Of Different Forest Types Based On Airborne Laser Scanner(ALS)

As a key canopy structure feature,the leaf area index(LAI)is an important input variable of various ecological and biochemical models,controlling the biological and physical processes of vegetation,such as photosynthesis,respiration,evapotranspiration,carbon cycle and precipitation interception,so it is essential to accurate LAI accurately,quickly and objectively.LiDAR(Light Detection and Ranging,LiDAR)is an active remote sensing technology that has developed very rapidly internationally in recent years,especially airborne laser scanner(ALS).The vertical and horizontal structure parameters of large-area forests can be obtained directly,therefore they are widely used to estimate forest structure parameters such as tree height,biomass and leaf area index.In this paper,3 kinds of laser penetration index(LPI)calculated by ALS echo number and LPI for calculating the echo intensity before and after correction are used to realize the inversion of forest LAI.The results show that the 3 kinds of LPI based on the echo number can effectively invert forest LAI,and the inversion accuracy is not very different.The inversion accuracy of LAI can be improved significantly by the echo strength after distance correction.This paper also uses the above LPI to invert different forest types of LAI based on Beer-Lambert’s law,and finds that the inversion accuracy presents the highest broad-leaved forest(R2=0.884-0.914),the second-in-line(R2=0.871-0.895),and the conifer minimum(R2=0.797-0.859)trend,but the overall inversion accuracy is high(R2=0.8417,RMSE=0.156).Therefore,the ALS data can be used to achieve the high-precision inversion of different forest types LAI,for the future ecological environment research to provide reliable large area basic data.