Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest

Timber assortments are some of the most important goods provided by forests worldwide. To quantify the amount and type of timber assortment is strongly important for socio-economic purposes, but also for accurate assessment of the carbon stored in the forest ecosystems, regardless of their main func...

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Autores principales:	Cesar Alvites, Giovanni Santopuoli, Markus Hollaus, Norbert Pfeifer, Mauro Maesano, Federico Valerio Moresi, Marco Marchetti, Bruno Lasserre
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	timber assortment roundwood mixed-species point cloud stem modelling Science Q
Acceso en línea:	https://doaj.org/article/b18d770a577c478f823ba96d87423edc
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spelling	oai:doaj.org-article:b18d770a577c478f823ba96d87423edc2021-11-11T18:52:08ZTerrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest10.3390/rs132142652072-4292https://doaj.org/article/b18d770a577c478f823ba96d87423edc2021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4265https://doaj.org/toc/2072-4292Timber assortments are some of the most important goods provided by forests worldwide. To quantify the amount and type of timber assortment is strongly important for socio-economic purposes, but also for accurate assessment of the carbon stored in the forest ecosystems, regardless of their main function. Terrestrial laser scanning (TLS) became a promising tool for timber assortment assessment compared to the traditional surveys, allowing reconstructing the tree architecture directly and rapidly. This study aims to introduce an approach for timber assortment assessment using TLS data in a mixed and multi-layered Mediterranean forest. It consists of five steps: (1) pre-processing, (2) timber-leaf discrimination, (3) stem detection, (4) stem reconstruction, and (5) timber assortment assessment. We assume that stem form drives the stem reconstruction, and therefore, it influences the timber assortment assessment. Results reveal that the timber-leaf discrimination accuracy is 0.98 through the Random Forests algorithm. The overall detection rate for all trees is 84.4%, and all trees with a diameter at breast height larger than 0.30 m are correctly identified. Results highlight that the main factors hindering stem reconstruction are the presence of defects outside the trunk, trees poorly covered by points, and the stem form. We expect that the proposed approach is a starting point for valorising the timber resources from unmanaged/managed forests, e.g., abandoned forests. Further studies to calibrate its performance under different forest stand conditions are furtherly required.Cesar AlvitesGiovanni SantopuoliMarkus HollausNorbert PfeiferMauro MaesanoFederico Valerio MoresiMarco MarchettiBruno LasserreMDPI AGarticletimber assortmentroundwoodmixed-speciespoint cloudstem modellingScienceQENRemote Sensing, Vol 13, Iss 4265, p 4265 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	timber assortment roundwood mixed-species point cloud stem modelling Science Q
spellingShingle	timber assortment roundwood mixed-species point cloud stem modelling Science Q Cesar Alvites Giovanni Santopuoli Markus Hollaus Norbert Pfeifer Mauro Maesano Federico Valerio Moresi Marco Marchetti Bruno Lasserre Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest
description	Timber assortments are some of the most important goods provided by forests worldwide. To quantify the amount and type of timber assortment is strongly important for socio-economic purposes, but also for accurate assessment of the carbon stored in the forest ecosystems, regardless of their main function. Terrestrial laser scanning (TLS) became a promising tool for timber assortment assessment compared to the traditional surveys, allowing reconstructing the tree architecture directly and rapidly. This study aims to introduce an approach for timber assortment assessment using TLS data in a mixed and multi-layered Mediterranean forest. It consists of five steps: (1) pre-processing, (2) timber-leaf discrimination, (3) stem detection, (4) stem reconstruction, and (5) timber assortment assessment. We assume that stem form drives the stem reconstruction, and therefore, it influences the timber assortment assessment. Results reveal that the timber-leaf discrimination accuracy is 0.98 through the Random Forests algorithm. The overall detection rate for all trees is 84.4%, and all trees with a diameter at breast height larger than 0.30 m are correctly identified. Results highlight that the main factors hindering stem reconstruction are the presence of defects outside the trunk, trees poorly covered by points, and the stem form. We expect that the proposed approach is a starting point for valorising the timber resources from unmanaged/managed forests, e.g., abandoned forests. Further studies to calibrate its performance under different forest stand conditions are furtherly required.
format	article
author	Cesar Alvites Giovanni Santopuoli Markus Hollaus Norbert Pfeifer Mauro Maesano Federico Valerio Moresi Marco Marchetti Bruno Lasserre
author_facet	Cesar Alvites Giovanni Santopuoli Markus Hollaus Norbert Pfeifer Mauro Maesano Federico Valerio Moresi Marco Marchetti Bruno Lasserre
author_sort	Cesar Alvites
title	Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest
title_short	Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest
title_full	Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest
title_fullStr	Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest
title_full_unstemmed	Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest
title_sort	terrestrial laser scanning for quantifying timber assortments from standing trees in a mixed and multi-layered mediterranean forest
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/b18d770a577c478f823ba96d87423edc
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Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest

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