Abstract

Several methods to conduct single-tree inventories using airborne laser scanning (ALS) have been proposed, and even terrestrial laser scanning (TLS) has recently emerged as a possible tool for the collection of forest inventory data. In the present study, a novel methodological framework for a combined use of ALS and TLS in an inventory was tested and compared to a method without the use of TLS. Single-tree Norway spruce crown biomass was predicted using an ALS-model with training data obtained by TLS. ALS and TLS data were collected for sets of sample trees, including 68 trees with both ALS and TLS data. In total, 29 destructively sampled trees were used to fit a TLS crown biomass model, which then was used to predict crown biomass in a separate set of 68 trees. This dataset was subsequently used to fit an ALS crown biomass model. When validating the model, using a separate dataset with accurately measured crown biomass obtained through destructive sampling, the mean error was 32% of the observed mean biomass. Corresponding crown biomass predictions derived with ALS-predicted diameters and the use of conventional and existing allometric models resulted in a mean error of 35%. Thus, in the present study, a slight improvement, in terms of prediction accuracy, was found when using training data with ground reference values obtained by TLS.

Highlights

  • Forest inventories are essential for the sustainable management of forest resources

  • We propose in the present study a procedure for airborne laser scanning (ALS)-based estimation of single-tree crown biomass using training data with ground reference values obtained through terrestrial laser scanning (TLS)

  • The aim of the present study was to assess the use of TLS in the process of fitting predictive models in an ALS single-tree forest inventory, by predicting crown biomass following each of the two approaches outlined above, and compare the predictions in an independent validation dataset

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Summary

Introduction

While commercial and operational ALS-based forest inventories most frequently are conducted according to the so-called area-based approach, as described by Næsset [2], methods targeting single trees have been proposed [3,4,5,6]. The latter methods usually require ALS data with higher resolution, but intend to give information on a single-tree level, contrary to the area-based information provided by the former. Not as widely used as the area-based method at present, the use of single-tree forest inventories might increase in the future. The potential of estimating single-tree characteristics by ALS has been investigated in several studies, including stem volume [4,7], stem diameter [8], crown base height [9], leaf area index [10] and biomass [8,11,12]

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