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Development of Willow Tree Yield-Mapping Technology
With today’s environmental challenges, developing sustainable energy sources is crucial. From this perspective, woody biomass has been, and continues to be, a significant research interest. The goal of this research was to develop new technology for mapping willow tree yield grown in a short-rotatio...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7249128/ https://www.ncbi.nlm.nih.gov/pubmed/32384703 http://dx.doi.org/10.3390/s20092650 |
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author | Leclerc, Maxime Adamchuk, Viacheslav Park, Jaesung Lachapelle-T., Xavier |
author_facet | Leclerc, Maxime Adamchuk, Viacheslav Park, Jaesung Lachapelle-T., Xavier |
author_sort | Leclerc, Maxime |
collection | PubMed |
description | With today’s environmental challenges, developing sustainable energy sources is crucial. From this perspective, woody biomass has been, and continues to be, a significant research interest. The goal of this research was to develop new technology for mapping willow tree yield grown in a short-rotation forestry (SRF) system. The system gathered the physical characteristics of willow trees on-the-go, while the trees were being harvested. Features assessed include the number of trees harvested and their diameter. To complete this task, a machine-vision system featuring an RGB-D stereovision camera was built. The system tagged these data with the corresponding geographical coordinates using a Global Navigation Satellite System (GNSS) receiver. The proposed yield-mapping system showed promising detection results considering the complex background and variable light conditions encountered in the outdoors. Of the 40 randomly selected and manually observed trees in a row, 36 were successfully detected, yielding a 90% detection rate. The correctly detected tree rate of all trees within the scenes was actually 71.8% since the system tended to be sensitive to branches, thus, falsely detecting them as trees. Manual validation of the diameter estimation function showed a poor coefficient of determination and a root mean square error (RMSE) of 10.7 mm. |
format | Online Article Text |
id | pubmed-7249128 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72491282020-06-10 Development of Willow Tree Yield-Mapping Technology Leclerc, Maxime Adamchuk, Viacheslav Park, Jaesung Lachapelle-T., Xavier Sensors (Basel) Article With today’s environmental challenges, developing sustainable energy sources is crucial. From this perspective, woody biomass has been, and continues to be, a significant research interest. The goal of this research was to develop new technology for mapping willow tree yield grown in a short-rotation forestry (SRF) system. The system gathered the physical characteristics of willow trees on-the-go, while the trees were being harvested. Features assessed include the number of trees harvested and their diameter. To complete this task, a machine-vision system featuring an RGB-D stereovision camera was built. The system tagged these data with the corresponding geographical coordinates using a Global Navigation Satellite System (GNSS) receiver. The proposed yield-mapping system showed promising detection results considering the complex background and variable light conditions encountered in the outdoors. Of the 40 randomly selected and manually observed trees in a row, 36 were successfully detected, yielding a 90% detection rate. The correctly detected tree rate of all trees within the scenes was actually 71.8% since the system tended to be sensitive to branches, thus, falsely detecting them as trees. Manual validation of the diameter estimation function showed a poor coefficient of determination and a root mean square error (RMSE) of 10.7 mm. MDPI 2020-05-06 /pmc/articles/PMC7249128/ /pubmed/32384703 http://dx.doi.org/10.3390/s20092650 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Leclerc, Maxime Adamchuk, Viacheslav Park, Jaesung Lachapelle-T., Xavier Development of Willow Tree Yield-Mapping Technology |
title | Development of Willow Tree Yield-Mapping Technology |
title_full | Development of Willow Tree Yield-Mapping Technology |
title_fullStr | Development of Willow Tree Yield-Mapping Technology |
title_full_unstemmed | Development of Willow Tree Yield-Mapping Technology |
title_short | Development of Willow Tree Yield-Mapping Technology |
title_sort | development of willow tree yield-mapping technology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7249128/ https://www.ncbi.nlm.nih.gov/pubmed/32384703 http://dx.doi.org/10.3390/s20092650 |
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