Retrieval and Validation of Vertical Forest Lai Profile from Airborne Lidar Data

Abstract

Leaf area index (LAI) is an important vegetation parameter. The vertical profile of forest LAI is critical for understanding the forest carbon, nitrogen, and water cycles and remote sensing radiative transfer processes. This study developed a method to estimate the LAI profile from airborne laser scanning (ALS) data during the leaf-on season. The LAI profile was validated using field measurement data from the digital hemispherical photography (DHP). The results show that both DHP and ALS data can get the vertical distribution of LAI, and similar trends can be obtained. The cumulative LAI derived from ALS data shows a good relationship with that from the DHP (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> =0.84). The LAI profile derived from ALS can be applied to land surface models and remote sensing radiative transfer models.