What is it about?
A simulation study is performed to compare the TLS-based estimators corrected and uncorrected for non-detection with the Horvitz–Thompson estimator based on conventional plot sampling, in which all the trees within plots are recorded.
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Why is it important?
Results show that single-scan TLS provides more efficient estimators with respect to those provided by the conventional plot sampling in the case of low-density forests when no distance sampling correction is performed. In low-density forests, uncorrected estimators lead to a small bias (1%–6%), increasing with plot size. Therefore, care must be taken in enlarging the plot radius too much. The bias increases in forests with clustered spatial structures and in dense forests, where the bias levels (30%–50%) deteriorate the performance of uncorrected estimators. Even if the bias-corrected estimators prove to be effective in reducing the bias (below 15%), these reductions are not sufficient to outperform conventional plot sampling. There is no convenience in using single-scan TLS-based forest inventory estimation in high-density forests.
Perspectives
To effectively exploit the advantage of TLS under permanent forest inventory applications, due to the possibility of a suitable monumentalization of the sample plots, advancement of multi-scan or mobile TLS approaches must be sought, in terms of both measurement and processing cost-effectiveness. Distinctively, mobile TLS coupled by simultaneous localization and mapping methods currently seems to be the most promising option.
Piermaria Corona
CREA Research Centre for Forestry and Wood
Read the Original
This page is a summary of: A Monte Carlo appraisal of tree abundance and stand basal area estimation in forest inventories based on terrestrial laser scanning, Canadian Journal of Forest Research, January 2019, Canadian Science Publishing,
DOI: 10.1139/cjfr-2017-0462.
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