Abstract
Estimation of biophysical variables based on airborne laser scanning (ALS) data using tree detection methods concentrates mainly on delineation of single trees and extraction of their attributes. This study provides new insight regarding the potential and limits of two detection methods and underlines some key aspects regarding the choice of the more appropriate alternative. First, we applied the multisource-based method implemented in reFLex software (National Forest Centre, Slovakia), which uses the information contained in the point cloud and a priori information. Second, we applied the raster-based method implemented in OPALS software (Vienna University of Technology, Austria), which extracts information from several ALS-derived height models. A comparative study was conducted for a part of the university forest in Zvolen (Slovakia, Central Europe). ALS-estimated variables of both methods were compared (1) to the ground reference data within four heterogonous stands with an area size of 7.5 ha as well as (2) to each other within a comprehensive forest unit with an area size of 62 ha. We concluded that both methods can be used to evaluate forest stand and ecological variables. The overall performance of both methods achieved a matching rate within the interval of 52%–64%. The raster-based method provided faster and slightly more accurate estimate of most variables, while the total volume was more precisely estimated using the multisource-based method. Specifically, the relative root mean square errors did not exceed 7.2% for mean height, 8.6% for mean diameter, 21.4% for total volume, 29.0% for stand density index, and 7.2% for Shannon’s diversity index. Both methods provided estimations with differences that were statistically significant, relative to the ground data as well as to each other (p < 0.05).
Highlights
Forest ecosystems are an important base for renewable raw materials and natural resources
This study focused on estimation of forest stand and ecological variables based on airborne laser scanning (ALS) data using individual tree detection approach (ITD)
The overall performance of both methods achieved the matching rate within the interval of 52%–64% and the omission rate ranged from 36% to 48%
Summary
Forest ecosystems are an important base for renewable raw materials and natural resources. Airborne laser scanning (ALS), known as airborne light detection and ranging (airborne LiDAR), as an active RS technology, provides an opportunity to complement ground-based inventories. This is primarily because these systems can penetrate a laser beam through even dense and multi-layered forest canopies to the ground, and they can be used to directly estimate a spatially explicit three-dimensional canopy structure with submeter accuracy in real time [1,2]
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