A Novel Method for Forest Leaf Area Index Inversion Using Lidar Data

ABSTRACT

Leaf area index (LAI) is one of the key ecological parameters and can be widely used in the growth situation of vegetation and environmental assessment. LiDAR is a new emerging active remote sensing technology in recent years, which can measure both the vertical and horizontal structure of forested areas effectively with high precision. Meanwhile, with the LiDAR data greatly enriches the observations of land surface targets, which makes it possible to estimate forest structural parameters accurately. Aimed to the shortage of traditional method was influenced by different degrees of saturation and each index could contain less vertical information in general. The paper choose the longhui district of hunan province in china as the study area, Studied the theory and method of using airborne LiDAR data to inversed forest LAI, established the optimum model of LAI inversion, propose a new approach for LAI inversion based on Lidar data. Finally relevant flight experiment and LAI inversion processing are introduced. The result indicate that the method is reliable, shows high accuracy inversion LAI with (R²=0.878, RMSE=0.223), compared with the TM images (R²=0.706, RMSE=0.430), it verified the feasibility and validity of this proposed method in inversion of forest LAI for Environmental assessment.

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