Assessment of Forest Structure Using Two UAV Techniques: A Comparison of Airborne Laser Scanning and Structure from Motion (SfM) Point Clouds

Abstract

This study investigates the potential of unmanned aerial vehicles (UAVs) to measure and monitor structural properties of forests. Two remote sensing techniques, airborne laser scanning (ALS) and structure from motion (SfM) were tested to capture three-dimensional structural information from a small multi-rotor UAV platform. A case study is presented through the analysis of data collected from a 30ˆ50 m plot in a dry sclerophyll eucalypt forest with a spatially varying canopy cover. The study provides an insight into the capabilities of both technologies for assessing absolute terrain height, the horizontal and vertical distribution of forest canopy elements, and information related to individual trees. Results indicate that both techniques are capable of providing information that can be used to describe the terrain surface and canopy properties in areas of relatively low canopy closure. However, the SfM photogrammetric technique underperformed ALS in capturing the terrain surface under increasingly denser canopy cover, resulting in point density of less than 1 ground point per m 2 and mean difference from ALS terrain surface of 0.12 m. This shortcoming caused errors that were propagated into the estimation of canopy properties, including the individual tree height (root mean square error of 0.92 m for ALS and 1.30 m for SfM). Differences were also seen in the estimates of canopy cover derived from the SfM (50%) and ALS (63%) pointclouds. Although ALS is capable of providing more accurate estimates of the vertical structure of forests across the larger range of canopy densities found in this study, SfM was still found to be an adequate low-cost alternative for surveying of forest stands.

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

“…LAStools ground extraction algorithm is based on an iterative grid simplification and has been previously effective in producing DTMs from LiDAR in a Mediterranean forest environment [40,41], and has been applied to dense point clouds produced from UAV SfM in densely forested environments, albeit with limited success because SfM techniques do not easily penetrate overlying vegetation [42]. However, in this study, UAV SfM was not used to survey densely vegetated unburned areas.…”

Optimizing the Processing of UAV-Based Thermal Imagery

“…In agricultural and horticultural studies, it has proven to be a reliable tool for estimating crop [9,10] or tree [11] height. Similarly, the method has been embraced by forest engineers because it can provide high-quality forest inventory data, which is otherwise very time-consuming to assess from the ground [12][13][14][15][16]. In addition, SfM has become the standard tool for high-precision mapping (orthophoto generation) of agricultural and natural ecosystems e.g., [10,17,18].…”

Cicada (<i>Magicicada</i>) Tree Damage Detection Based on UAV Spectral and 3D Data

“…Better positional control and additional processing can improve the structure from motion calculations [48,51,53] or the imagery can be Natural Science combined with Lidar data to better capture the range of elevation values. This is primarily due to the laser pulses ability to penetrate canopy or understory features [26,28,54]. However, with Lidar there is a significant time and money investment required to acquire the technology especially when the structure from motion may suffice [52,55].…”

“…An example of surface reconstruction has been in forest structure [29]. Studies have shown that UAVs can help with species identification [30,31], tree height [26,32], crown delineation [26,33,34], and forest health [35][36][37]. The use of UAVs has great potential for analyzing tree branch conditions as an early detection of tree health [35].…”

“…The main advantages of the UAV are the low cost of acquisition [19,20], possibility of frequent monitoring [21,22], adaptability to carry various sensors, as thermal, infrared and multispectral cameras or even Lidar scanners [19,[23][24][25], the high resolution obtained [19,23,26], and the development of processing software focused on the automatic reconstruction of surfaces using the UAV data [27,28]. An example of surface reconstruction has been in forest structure [29].…”