Influence of Scanner Position and Plot Size on the Accuracy of Tree Detection and Diameter Estimation Using Terrestrial Laser Scanning on Forest Inventory Plots

Christoph Gollob,Arne Nothdurft,Clemens Wassermann,Tim Ritter

doi:10.3390/rs11131602

Christoph Gollob, Arne Nothdurft + Show 2 more

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https://doi.org/10.3390/rs11131602

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Abstract

This research tested how different scanner positions and sample plot sizes affect the tree detection and diameter measurement in forest inventories. For this, a multistage density-based clustering approach was further developed for the automatic mapping of tree positions and simultaneously applied with automatic measurements of tree diameters. This further development of the algorithm reduced the proportion of falsely detected tree locations by about 64%. The algorithms were tested in different settings with respect to the number and spatial alignment of scanner positions and under manifold forest conditions, covering different age classes and a mixture of scenarios, and representing a broad gradient of structural complexity. For circular sample plots with a maximum radius of 20 m, the tree mapping algorithm showed a detection rate of 82.4% with seven scanner positions at the vertices of a hexagon plus the center coordinates, and 68.3% with four scanner positions aligned in a triangle plus the center. Detection rates were significantly increased with smaller maximum radii. Thus, with a maximum radius of 10 m, the hexagon setting yielded a detection rate of 90.5% and the triangle 92%. Other alignments of scanner positions were also tested, but proved to be either unfavorable or too labor-intensive. The commission rates were on average less than 3%. The root mean square error (RMSE) of the dbh (diameter at breast height) measurement was between 2.66 cm and 4.18 cm for the hexagon and between 3.0 cm and 4.7 cm for the triangle design. The robustness of the algorithm was also demonstrated via tests by means of an international benchmark dataset. It has been shown that the number of stems per hectare had a significant impact on the detection rate.

Highlights

The major purpose of forest inventories is to provide relevant information on the status and changes of forest landscapes
The analysis of the 23 plots showed that the detection rate dr(%) over all scan variants strongly depended on the lower dbh threshold and the sample plot radius applied as a maximum radius (Figure 2)
In order to enable an exact comparison with the results presented in the benchmark study, additional quality metrics were computed according to suggestions by the authors of that study

Summary

Introduction

The major purpose of forest inventories is to provide relevant information on the status and changes of forest landscapes. In order to provide reliable and precise information on traditional attributes, such as average growing stock timber volume or tree count, measurement errors besides the design-based sampling variance should be kept as small as possible. In traditional forest inventories with multiple sample plots, tree attributes and positions are manually measured using mechanical or optical instruments such as calipers, hypsometers, compasses, and measuring tapes [1,2,3,4]. The application of these traditional measurement techniques is time-consuming, cost-intensive, and prone to manifold measurement errors [5,6,7]. Trials to improve efficiency since the beginning of forest inventory have permanently enhanced techniques, instruments, and protocols [6]

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