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

By Luke Wallace, Arko Lucieer, Z. Malenovsky, Darren Turner, Petr Vopenka. 2016

685 citations recorded by the source corpus.

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 30 × 50 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 m2 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.

Subfields: Environmental Engineering, Geology, Insect Science

View Paper: https://www.semanticscholar.org/paper/143b5ed8be2fbfa4edd35e7cd91f018ff3f4a780

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Xiaoyu Chen
2. Rongjun Qin
3. H. Yao
4. Lin Cao
5. Luke Wallace
6. Honghua Ruan
7. Hao Liu
8. Zhengnan Zhang

In Geology

1. Xiaoyu Chen
2. Rongjun Qin
3. H. Yao
4. Lin Cao
5. Luke Wallace

In Insect Science

1. Lin Cao
2. Honghua Ruan
3. Hao Liu
4. Zhengnan Zhang
5. Xiaoyao Fu

Citations in the corpus

• Comparison of UAV LiDAR and Digital Aerial Photogrammetry Point Clouds for Estimating Forest Structural Attributes in Subtropical Planted Forests (2019, methodology): “As reported by Wallace et al. (2016) [43] with respect to the estimation of forest attributes, more forest structural attributes should be examined with the rapid development of sensor technology and the application of new analysis methods to data collected from UAVs [34,64].”
• Unmanned Aerial Vehicle for Remote Sensing Applications - A Review (2019, background): “Soil property estimation [135]; crop / vegetation management [136,137]; forest structure assessment [138].”
• Forestry applications of UAVs in Europe: a review (2017, background): “Nevertheless, progress in the field of computer vision has allowed the development of a wide range of imaging techniques, such as the SfM, which allow the 3D geometry reconstruction from a series of well-overlapped 2D images (Wallace et al. 2016).”