Using airborne lidar to retrieve crop structural parameters

Abstract

Airborne LIDAR (Light Detection and Ranging) is an active remote sensing technique that measures the properties of scattered light to determine the range and intensity information of a distant target. Many studies have been reported on estimating a suite of forest characteristics such as fractional vegetation cover, leaf area index and canopy height using LIDAR data. The three characteristics of crop canopy also play key roles in vegetation radiative transfer models and yield estimation. But crops are so small and low that more than 95% pulses have ground hit, it is difficult to separate the crop and soil completely, so the methods used in forest may not be suitable for crops. In this paper, based on theoretical analysis, we propose a new method, trying to derive gap fraction of crop field using the airborne LIDAR intensity of ground hits, so we can manage to retrieve the fractional vegetation cover, LAI and the height of crop canopy. We choose corn field as study object, field validation shows that our method can accurately retrieve the three structural parameters of corn field. This study documents the great potential of LIDAR remote sensing for accurately characterizing crop canopies.