Forest Structural Complexity Tool—An Open Source, Fully-Automated Tool for Measuring Forest Point Clouds

Forest mensuration remains critical in managing our forests sustainably, however, capturing such measurements remains costly, time-consuming and provides minimal amounts of information such as diameter at breast height (DBH), location, and height. Plot scale remote sensing techniques show great prom...

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Autores principales:	Sean Krisanski, Mohammad Sadegh Taskhiri, Susana Gonzalez Aracil, David Herries, Allie Muneri, Mohan Babu Gurung, James Montgomery, Paul Turner
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	deep learning segmentation forest point cloud lidar photogrammetry Science Q
Acceso en línea:	https://doaj.org/article/7cfe1b6b06fd4369bdb4710e66673be1
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id	oai:doaj.org-article:7cfe1b6b06fd4369bdb4710e66673be1
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spelling	oai:doaj.org-article:7cfe1b6b06fd4369bdb4710e66673be12021-11-25T18:55:22ZForest Structural Complexity Tool—An Open Source, Fully-Automated Tool for Measuring Forest Point Clouds10.3390/rs132246772072-4292https://doaj.org/article/7cfe1b6b06fd4369bdb4710e66673be12021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/22/4677https://doaj.org/toc/2072-4292Forest mensuration remains critical in managing our forests sustainably, however, capturing such measurements remains costly, time-consuming and provides minimal amounts of information such as diameter at breast height (DBH), location, and height. Plot scale remote sensing techniques show great promise in extracting detailed forest measurements rapidly and cheaply, however, they have been held back from large-scale implementation due to the complex and time-consuming workflows required to utilize them. This work is focused on describing and evaluating an approach to create a robust, sensor-agnostic and fully automated forest point cloud measurement tool called the Forest Structural Complexity Tool (FSCT). The performance of FSCT is evaluated using 49 forest plots of terrestrial laser scanned (TLS) point clouds and 7022 destructively sampled manual diameter measurements of the stems. FSCT was able to match 5141 of the reference diameter measurements fully automatically with mean, median and root mean squared errors (RMSE) of 0.032 m, 0.02 m, and 0.103 m respectively. A video demonstration is also provided to qualitatively demonstrate the diversity of point cloud datasets that the tool is capable of measuring. FSCT is provided as open source, with the goal of enabling plot scale remote sensing techniques to replace most structural forest mensuration in research and industry. Future work on this project will seek to make incremental improvements to this methodology to further improve the reliability and accuracy of this tool in most high-resolution forest point clouds.Sean KrisanskiMohammad Sadegh TaskhiriSusana Gonzalez AracilDavid HerriesAllie MuneriMohan Babu GurungJames MontgomeryPaul TurnerMDPI AGarticledeep learningsegmentationforestpoint cloudlidarphotogrammetryScienceQENRemote Sensing, Vol 13, Iss 4677, p 4677 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	deep learning segmentation forest point cloud lidar photogrammetry Science Q
spellingShingle	deep learning segmentation forest point cloud lidar photogrammetry Science Q Sean Krisanski Mohammad Sadegh Taskhiri Susana Gonzalez Aracil David Herries Allie Muneri Mohan Babu Gurung James Montgomery Paul Turner Forest Structural Complexity Tool—An Open Source, Fully-Automated Tool for Measuring Forest Point Clouds
description	Forest mensuration remains critical in managing our forests sustainably, however, capturing such measurements remains costly, time-consuming and provides minimal amounts of information such as diameter at breast height (DBH), location, and height. Plot scale remote sensing techniques show great promise in extracting detailed forest measurements rapidly and cheaply, however, they have been held back from large-scale implementation due to the complex and time-consuming workflows required to utilize them. This work is focused on describing and evaluating an approach to create a robust, sensor-agnostic and fully automated forest point cloud measurement tool called the Forest Structural Complexity Tool (FSCT). The performance of FSCT is evaluated using 49 forest plots of terrestrial laser scanned (TLS) point clouds and 7022 destructively sampled manual diameter measurements of the stems. FSCT was able to match 5141 of the reference diameter measurements fully automatically with mean, median and root mean squared errors (RMSE) of 0.032 m, 0.02 m, and 0.103 m respectively. A video demonstration is also provided to qualitatively demonstrate the diversity of point cloud datasets that the tool is capable of measuring. FSCT is provided as open source, with the goal of enabling plot scale remote sensing techniques to replace most structural forest mensuration in research and industry. Future work on this project will seek to make incremental improvements to this methodology to further improve the reliability and accuracy of this tool in most high-resolution forest point clouds.
format	article
author	Sean Krisanski Mohammad Sadegh Taskhiri Susana Gonzalez Aracil David Herries Allie Muneri Mohan Babu Gurung James Montgomery Paul Turner
author_facet	Sean Krisanski Mohammad Sadegh Taskhiri Susana Gonzalez Aracil David Herries Allie Muneri Mohan Babu Gurung James Montgomery Paul Turner
author_sort	Sean Krisanski
title	Forest Structural Complexity Tool—An Open Source, Fully-Automated Tool for Measuring Forest Point Clouds
title_short	Forest Structural Complexity Tool—An Open Source, Fully-Automated Tool for Measuring Forest Point Clouds
title_full	Forest Structural Complexity Tool—An Open Source, Fully-Automated Tool for Measuring Forest Point Clouds
title_fullStr	Forest Structural Complexity Tool—An Open Source, Fully-Automated Tool for Measuring Forest Point Clouds
title_full_unstemmed	Forest Structural Complexity Tool—An Open Source, Fully-Automated Tool for Measuring Forest Point Clouds
title_sort	forest structural complexity tool—an open source, fully-automated tool for measuring forest point clouds
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/7cfe1b6b06fd4369bdb4710e66673be1
work_keys_str_mv	AT seankrisanski foreststructuralcomplexitytoolanopensourcefullyautomatedtoolformeasuringforestpointclouds AT mohammadsadeghtaskhiri foreststructuralcomplexitytoolanopensourcefullyautomatedtoolformeasuringforestpointclouds AT susanagonzalezaracil foreststructuralcomplexitytoolanopensourcefullyautomatedtoolformeasuringforestpointclouds AT davidherries foreststructuralcomplexitytoolanopensourcefullyautomatedtoolformeasuringforestpointclouds AT alliemuneri foreststructuralcomplexitytoolanopensourcefullyautomatedtoolformeasuringforestpointclouds AT mohanbabugurung foreststructuralcomplexitytoolanopensourcefullyautomatedtoolformeasuringforestpointclouds AT jamesmontgomery foreststructuralcomplexitytoolanopensourcefullyautomatedtoolformeasuringforestpointclouds AT paulturner foreststructuralcomplexitytoolanopensourcefullyautomatedtoolformeasuringforestpointclouds
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Forest Structural Complexity Tool—An Open Source, Fully-Automated Tool for Measuring Forest Point Clouds

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