Airborne lidar for forest understory profiles: validating with terrestrial lidar data - Howard, Shiona (The University of Edinburgh, 2019)
Lidar is an effective active remote sensing instrument with potential for use in forest management for fire mitigation by accurately measuring vegetation profiles, or foliage density, height and composition. Lidar is additionally effective at looking for ladder fuels within the understory over large areas. Terrestrial laser scanners (TLS) are currently used in forestry due to their high accuracy in measurements. Yet, are unable to measure large areas at once. Airborne laser scanners (ALS) data could potentially be used in forest management in order to accurately distinguish understory in mixed canopies in large spatial and remote areas. This study assesses discrete-returned ALS data against accurate TLS data in a mixed canopy setting for the detection of understory. ALS data was compared to TLS data in a high voxel resolution to assess the comparison of leaf area index (LAI) measurements between two data sources. A Simple Pearson’s correlation of -0.009 showed that there is no relationship between the ALS and TLS measurements at lower elevations. This lack of agreement between the ALS and TLS results are potentially due to high occlusion of signals from fire smoke, dense vegetation, tree trunks or all, along with differences in instrument scan angles. These differences in LAI measurements, and lack of agreeability, show that the feasibility of using discrete-returned ALS to accurately measure understory needs to be further studied.
Keywords: Lidar; Forest Management; ALS; TLS