Simulation on Different Patterns of Mobile Laser Scanning with Extended Application on Solar Beam Illumination for Forest Plot

Abstract

Light detection and ranging (LiDAR) technology has become a mainstream tool for forest surveys, significantly contributing to the improved accuracy of forest inventories. However, the accuracy of the scanned data and tree properties derived using LiDAR technology may differ depending on the occlusion effect, scanning configurations, various scanning patterns, and vegetative characteristics of forest plots. Hence, this paper presents a computer simulation program to build a digital forest plot composed of many tree models constructed based on in situ measurement information and two mobile scanning patterns, i.e., airborne laser scanning (ALS) and ground-based mobile laser scanning (MLS). Through the adjustment of scanning parameters and the velocity of vehicle loading LiDAR sensors, the points scanned using two scanning patterns were compared with the original sampling points, derived from the constructed digital forest plots. The results show that only 2% of sampling points were collected by LiDAR sensors with the fastest vehicle speed (10 m/s) and coarsest scanning angular resolution (horizontal angular resolution 0.16° and vertical angular resolution 1.33°), and approximately 50% of sampling points were collected by LiDAR sensors with slow vehicle velocity (1.25 m/s) and a finer scanning angular resolution (horizontal angular resolution 0.08° and vertical angular resolution 0.33°). Meanwhile, the potential extended application of the proposed computer simulation program as a light model of forest plots was discussed to underpin the creation of the forest digital twin. Three main conclusions are drawn: (1) the collected points from airborne laser scanning (ALS) are higher than those collected from ground-based mobile laser scanning (MLS); (2) reducing the vehicle velocity is more efficient at improving the high density of the point cloud data than by increasing the scanning angular resolution; (3) the lateral extension of crown area increasing the light beams’ receptor area and the clumped leaf dispersion augmenting the light penetration with vertical elongation are the two paramount factors influencing the light transmittance of tree crowns.

CNTCB-YOLOv7: An Effective Forest Fire Detection Model Based on ConvNeXtV2 and CBAM

“…This expansion will not only enhance the generalizability of our findings, but also allow us to assess the model's performance under different scenarios and conditions. In addition, we will explore the applicability of our model in diverse domains by considering additional data types, such as LiDAR (Light detection and ranging) data [41,42]. This broader range of datasets will enable us to thoroughly test and validate the robustness and versatility of our model across various fields.…”

Synthetic Forest Stands and Point Clouds for Model Selection and Feature Space Comparison

“…There is also the added advantage of testing multiple configurations with little to no added expense, other than computational time, allowing for the manipulation of simulation parameters, such as scanning resolution, occlusion effects, and sensor characteristics, to understand their impact on results. Jiang et al [47] demonstrated this by introducing a simulation program to create digital forest plots and simulating aerial and mobile laser scanning. By adjusting scanning parameters and vehicle speed, the scanned points were compared to original sampling points from the digital forest plots.…”