Extraction of Forestry Parameters Based on Multi-Platform LiDAR

Zhengjun Liu,Yiming Chen,Jianchang Chen

doi:10.1109/access.2022.3151685

Abstract

Quick and accurate acquisition of tree height (TH) and diameter at breast height (DBH) plays a very important role in forestry surveys. These parameters can be collected rapidly and accurately with LiDAR. In this paper, an accurate tree parameters extraction method with combining the use of Unmanned Aerial Vehicle Laser Scanning (UAVLS) to extract TH and Terrestrial Laser Scanning (TLS) to extract DBH was proposed. To verify the applicability of this method, this paper collected LiDAR data in the Laohugou forest area (a natural forest) and Saihanba forest area (an artificial forest), Hebei Province, China. For the extraction of TH, both forest areas had overestimated. The coefficient of determination R 2 of TH in Laohugou forest area was 0.9458 and the root mean square error (RMSE) was 0.7 m, while in Saihanba forest area R 2 was 0.95 and the RMSE was 0.65 m. A method based on point density analysis was proposed to automatically extract DBH. First, the data by TLS was normalized and made four-centimeter slices at 1.3 m. Then, branches, weeds and outliers were eliminated using an improved K-means algorithm. Finally, point density analysis was performed on all sections, and threshold values were set to automatically complete the extraction of DBH. The automatic DBH extraction by this paper proposed method was consistent with the actual measurements, and the mean intersection over union (MIOU) reached 89%. The R 2 of DBH in the Laohugou forest area was 0.9941 and the RMSE was 0.65 cm; the R 2 of DBH in the Saihanba forest area was 0.99 and the RMSE was 0.43 cm. These results confirm that the accurate extraction of DBH in two forest areas with different growth conditions and different tree species.

Highlights

The increase in population, the burning of fossil fuels, and deforestation of forest resources have caused an excess of carbon dioxide in the atmosphere, intensifying the problem of global warming [1,2,3]
For the Laohugou forest plot, the Tree height (TH) obtained by LiDAR ranged from 6.8 to 14.72 m and the average TH was 11.47 m
The above studies obtain forestry parameters from LiDAR on different platforms, they had the disadvantages of complex extraction of forestry parameters, low accuracy, and single test area

Summary

Introduction

The increase in population, the burning of fossil fuels, and deforestation of forest resources have caused an excess of carbon dioxide in the atmosphere, intensifying the problem of global warming [1,2,3]. Forests mainly absorb carbon dioxide from the atmosphere, regulate the carbon-water balance, and play an important role in mitigating global warming and balance ecosystems [4]. Tree height (TH) and diameter at breast height (DBH) are one of the most important attributes in forest resource surveys. These two parameters and other tree parameters (tree species, crown width, etc.) are often used to predict forest storage capacity and carbon sequestration capacity [5, 6]. Fast and accurate acquisition of forestry parameter is of great significance to forestry resource assessment and management

Methods

Results

Discussion

Conclusion