USAGE OF LIDAR DATA FOR LEAF AREA INDEX ESTIMATION

Abstract

Leaf area index (LAI) can be measured either directly, using destructive methods, or indirectly using optical methods that are based on the tight relationship between LAI and canopy light transmittance. Third, innovative approach for LAI measuring is usage of remote sensing data, especially airborne laser scanning (ALS) data shows itself as a advisable source for purposes of LAI modelling in large areas. Until now there has been very little research to compare LAI estimated by the two different approaches. Indirect measurements of LAI using hemispherical photography are based on the transmission of solar radiation through the vegetation. It can thus be assumed that the same is true for the penetration of LiDAR laser beams through the vegetation canopy. In this study we use ALS based LiDAR penetration index (LPI) and ground based measurement of LAI obtained from hemispherical photographs as a reference in-situ method. Several regression models describing the corellation LAI and LPI were developed with various coefficients of determination ranging up to 0,81. All models were validated and based on the tests performed, no errors were drawn that would affect their credibility.