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Grassland health assessment based on indicators monitored by UAVs: a case study at a household scale
Grassland health assessment (GHA) is a bridge of study and management of grassland ecosystem. However, there is no standardized quantitative indicators and long-term monitor methods for GHA at a large scale, which may hinder theoretical study and practical application of GHA. In this study, along wi...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10548208/ https://www.ncbi.nlm.nih.gov/pubmed/37799559 http://dx.doi.org/10.3389/fpls.2023.1150859 |
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author | Luo, Yifei Ji, Wenxiang Wu, Wenjun Liao, Yafang Wei, Xinyi Yang, Yudie Dong, Guoqiang Ma, Qingshan Yi, Shuhua Sun, Yi |
author_facet | Luo, Yifei Ji, Wenxiang Wu, Wenjun Liao, Yafang Wei, Xinyi Yang, Yudie Dong, Guoqiang Ma, Qingshan Yi, Shuhua Sun, Yi |
author_sort | Luo, Yifei |
collection | PubMed |
description | Grassland health assessment (GHA) is a bridge of study and management of grassland ecosystem. However, there is no standardized quantitative indicators and long-term monitor methods for GHA at a large scale, which may hinder theoretical study and practical application of GHA. In this study, along with previous concept and practices (i.e., CVOR, the integrated indexes of condition, vigor, organization and resilience), we proposed an assessment system based on the indicators monitored by unmanned aerial vehicles (UAVs)-UAV (CVOR) , and tested the feasibility of UAV (CVOR) at typical household pastures on the Qinghai-Tibetan Plateau, China. Our findings show that: (1) the key indicators of GHA could be measured directly or represented by the relative counterpart indicators that monitored by UAVs, (2) there was a significantly linear relationship between CVOR estimated by field- and UAV-based data, and (3) the CVOR decreased along with the increasing grazing intensity nonlinearly, and there are similar tendencies of CVOR that estimated by the two methods. These findings suggest that UAVs is suitable for GHA efficiently and correctly, which will be useful for the protection and sustainable management of grasslands. |
format | Online Article Text |
id | pubmed-10548208 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105482082023-10-05 Grassland health assessment based on indicators monitored by UAVs: a case study at a household scale Luo, Yifei Ji, Wenxiang Wu, Wenjun Liao, Yafang Wei, Xinyi Yang, Yudie Dong, Guoqiang Ma, Qingshan Yi, Shuhua Sun, Yi Front Plant Sci Plant Science Grassland health assessment (GHA) is a bridge of study and management of grassland ecosystem. However, there is no standardized quantitative indicators and long-term monitor methods for GHA at a large scale, which may hinder theoretical study and practical application of GHA. In this study, along with previous concept and practices (i.e., CVOR, the integrated indexes of condition, vigor, organization and resilience), we proposed an assessment system based on the indicators monitored by unmanned aerial vehicles (UAVs)-UAV (CVOR) , and tested the feasibility of UAV (CVOR) at typical household pastures on the Qinghai-Tibetan Plateau, China. Our findings show that: (1) the key indicators of GHA could be measured directly or represented by the relative counterpart indicators that monitored by UAVs, (2) there was a significantly linear relationship between CVOR estimated by field- and UAV-based data, and (3) the CVOR decreased along with the increasing grazing intensity nonlinearly, and there are similar tendencies of CVOR that estimated by the two methods. These findings suggest that UAVs is suitable for GHA efficiently and correctly, which will be useful for the protection and sustainable management of grasslands. Frontiers Media S.A. 2023-09-20 /pmc/articles/PMC10548208/ /pubmed/37799559 http://dx.doi.org/10.3389/fpls.2023.1150859 Text en Copyright © 2023 Luo, Ji, Wu, Liao, Wei, Yang, Dong, Ma, Yi and Sun https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Luo, Yifei Ji, Wenxiang Wu, Wenjun Liao, Yafang Wei, Xinyi Yang, Yudie Dong, Guoqiang Ma, Qingshan Yi, Shuhua Sun, Yi Grassland health assessment based on indicators monitored by UAVs: a case study at a household scale |
title | Grassland health assessment based on indicators monitored by UAVs: a case study at a household scale |
title_full | Grassland health assessment based on indicators monitored by UAVs: a case study at a household scale |
title_fullStr | Grassland health assessment based on indicators monitored by UAVs: a case study at a household scale |
title_full_unstemmed | Grassland health assessment based on indicators monitored by UAVs: a case study at a household scale |
title_short | Grassland health assessment based on indicators monitored by UAVs: a case study at a household scale |
title_sort | grassland health assessment based on indicators monitored by uavs: a case study at a household scale |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10548208/ https://www.ncbi.nlm.nih.gov/pubmed/37799559 http://dx.doi.org/10.3389/fpls.2023.1150859 |
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