3D Forest Mapping Using A Low-Cost UAV Laser Scanning System: Investigation and Comparison

Xiaoyao Fu,Lin Cao,Jianping Li,Yangzi Cong,Bisheng Yang,Zhen Dong

doi:10.3390/rs11060717

Abstract

Automatic 3D forest mapping and individual tree characteristics estimation are essential for forest management and ecosystem maintenance. The low-cost unmanned aerial vehicle (UAV) laser scanning (ULS) is a newly developed tool for cost-effectively collecting 3D information and attempts to use it for 3D forest mapping have been made, due to its capability to provide 3D information with a lower cost and higher flexibility than the standard ULS and airborne laser scanning (ALS). As the direct georeferenced point clouds may suffer from distortion caused by the poor performance of a low-cost inertial measurement unit (IMU), and 3D forest mapping using low-cost ULS poses a great challenge. Therefore, this paper utilized global navigation satellite system (GNSS) and IMU aided Structure-from-Motion (SfM) for trajectory estimation, and, hence, overcomes the poor performance of low-cost IMUs. The accuracy of the low-cost ULS point clouds was compared with the ground truth data collected by a commercial ULS system. Furthermore, the effectiveness of individual trees segmentation and tree characteristics estimation derived from the low-cost ULS point clouds were accessed. Experiments were undertaken in Dongtai forest farm, Yancheng City, Jiangsu Province, China. The results showed that the low-cost ULS achieved good point clouds quality from visual inspection and comparable individual tree segmentation results (P = 0.87, r = 0.84, F= 0.85) with the commercial system. Individual tree height estimation performed well (coefficient of determination (R2 ) = 0.998, root-mean-square error (RMSE) = 0.323 m) using the low-cost ULS. As for individual tree crown diameter estimation, low-cost ULS achieved good results (R2 = 0.806, RMSE = 0.195 m) after eliminating outliers. In general, such results illustrated the high potential of the low-cost ULS in 3D forest mapping, even though 3D forest mapping using the low-cost ULS requires further research.

Highlights

Forests, one of the main terrestrial ecosystems on Earth, play a vital role in climate change, conservation of biological diversity, and terrestrial ecosystems itself. 3D forest mapping at individual tree level is becoming essential for forest management and ecosystem sustainability [1]
mobile laser scanning (MLS) is restricted by the global navigation satellite system (GNSS) shadows in forests
The trajectory was estimated by integrating image sequence, inertial measurement unit (IMU) and GNSS data

Summary

Introduction

One of the main terrestrial ecosystems on Earth, play a vital role in climate change, conservation of biological diversity, and terrestrial ecosystems itself. 3D forest mapping at individual tree level is becoming essential for forest management and ecosystem sustainability [1]. Accurate, efficient, and cost-effective methods for accessing the individual tree structure are of great importance [4,5]. Applications of terrestrial laser scanning (TLS) using the single-scan and multi-scan approach for forest inventory have been thoroughly investigated [2]. To further improve the efficiency of data collection using TLS, mobile laser scanning (MLS) is used in forestry surveys because of its ability to measure complex forest areas [6,7]. Complementing TLS and MLS in different observational perspectives, airborne laser scanning (ALS) has a high potential in forest applications, providing a good solution for accessing various forest characteristics, such as tree height [8], crown diameter [9], wood volume [10], and biomass [11]. The spatial and temporal resolutions of the ALS system is limited because of the inflexibility and the high costs

Objectives

Results

Conclusion