UAV-LiDAR Measurement of Vegetation Canopy Structure Parameters and Their Impact on Land–Air Exchange Simulation Based on Noah-MP Model

Abstract

Land surface processes play a vital role in the exchange of momentum, energy, and mass between the land and the atmosphere. However, the current model simplifies the canopy structure using approximately three to six parameters, which makes the representation of canopy radiation and energy distribution uncertain to a large extent. To improve the simulation performance, more specific canopy structure parameters were retrieved by a UAV-LiDAR observation system and updated into the multiparameterization version of the Noah land surface model (Noah-MP) for a typical forest area. Compared with visible-light photogrammetry, LiDAR retrieved a more accurate vertical canopy structure, which had a significant impact on land–air exchange simulations. The LiDAR solution resulted in a 35.0∼48.0% reduction in the range of perturbations for temperature and another 27.8% reduction in the range of perturbations for moisture. This was due to the canopy structure affecting the radiation and heat fluxes of the forest, reducing their perturbation range by 7.5% to 30.1%. To reduce the bias of the land surface interaction simulation, it will be necessary to improve the method of retrieving the canopy morphological parameterization through UAV-LiDAR on a continued basis in the future.

Three-Dimensional Mapping of Habitats Using Remote-Sensing Data and Machine-Learning Algorithms

“…Along with horizontal dimension, vegetation height is also important for habitat classification and three-dimensional (3D) mapping. LiDAR sensors provide measurements of distances (heights) of the top (e.g., canopy height) and the ground surface [8,18,19]. Multiple studies have also used topographic-related features, such as slope, aspect, and roughness, to improve the result of habitat classification.…”