731
Views
14
CrossRef citations to date
0
Altmetric
Articles

Estimating tree stem density and diameter distribution in single-scan terrestrial laser measurements of field plots: a simulation study

ORCID Icon & ORCID Icon
Pages 365-377 | Received 22 Jun 2017, Accepted 06 Aug 2017, Published online: 06 Sep 2017
 

ABSTRACT

The single-scan setup of terrestrial laser scanning of a forest field plot has advantages compared to the multi-scan setup: the speed of operation and that there is no need of a co-registration of the different scans. However in a single-scan setup some of the trees are shaded by others and therefore not detected in the scan. A field inventory solution must take this fact into account. This simulation study shows how different plot sizes and tree stand densities influence the stem visibility giving nonlinear effects especially for large trees and high stem numbers. These effects can be counteracted by using an edge or center stem point detection criteria when analyzing the results or by weighting the detected trees by their visibility. It is shown that the stem density and diameter distribution can be estimated from the visible areas of the plot in case the stem positions are Poisson distributed.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was financed by the ÅForsk foundation and the Advanced SAR project of the European Community's Seventh Framework Programme ([FP7/2007-2013]) under grant agreement no 606971.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 133.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.