Abstract

In this study, individual tree height (TH), crown base height (CBH), crown area (CA) and crown volume (CV), which were considered as essential parameters for individual stem volume and biomass estimation, were estimated by both an airborne laser scanner (ALS) and a terrestrial laser scanner (TLS). These ALS- and TLS-derived tree parameters were compared because TLS has been introduced as an instrument to measure objects more precisely. ALS-estimated TH was extracted from the highest value within a crown boundary delineated with the crown height model (CHM). The ALS-derived CBH of individual trees was estimated by k-means clustering method using the ALS data within the boundary. The ALS-derived CA was calculated simply with the crown boundary, after which CV was computed automatically using the crown geometric volume (CGV). On the other hand, all TLS-derived parameters were detected manually and precisely except the TLS-derived CGV. As a result, the ALS-extracted TH, CA, and CGV values were underestimated whereas CBH was overestimated when compared with the TLS-derived parameters. The coefficients of determination (R2) from the regression analysis between the ALS and TLS estimations were approximately 0.94, 0.75, 0.69 and 0.58, and root mean square errors (RMSEs) were approximately 0.0184 m, 0.4929 m, 2.3216 m2 and 13.2087 m3 for TH, CBH, CA and CGV, respectively. Thereby, the error rate decreased to 0.0089, 0.0727 and 0.0875 for TH, CA and CGV via the combination of ALS and TLS data.

Highlights

  • Forest inventory information has always been important with respect to forest management

  • The parameters estimated by the regressed functions were statistically compared with the terrestrial laser scanner (TLS) measurement data using the coefficient of determination (R2) and root mean square error (RMSE)

  • We estimated several tree parameters and developed regression models for improving the accuracy of estimating parameters using airborne laser scanner (ALS) and TLS

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Summary

Introduction

Forest inventory information has always been important with respect to forest management. The crown edge overlapping can cause another error when estimating DBH, CBH, and CD [16] For supplementing such underestimation, many researchers have used regression models using the correlation between field- and ALS-derived biophysical variables. To overcome the drawbacks of both instruments, we tried to combine ALS and TLS data in sample plots in order to estimate forest growth factors such as TH, CBH, CA and crown geometric volume (CGV). These parameters were effectively adopted for individual stem volume and biomass estimation, because it can reduce the difficulties from regression analysis between DBH and CA [5,23]. The study results revealed that more accurate estimates of the examined forest parameters were obtained via the combined ALS and TLS data procedure than when only ALS data were used independently

Study Area
Acquisition of Airborne Laser Scanner Data
Acquisition of Terrestrial Laser Scanner Data
Derivation of Crown Height Model
Crown Delineation
Estimation of Individual Tree Height and Crown Base Height
Estimation of Crown Area and Crown Geometric Volume
Measurement of Tree Height and Crown Base Height
Measurement of Crown Area and Crown Geometric Volume
Regression Analysis and Accuracy Assessment
Tree Height
Crown Base Height
Crown Area
Crown Geometric Volume
Overall Analysis
Conclusions
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