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An improved global vegetation health index dataset in detecting vegetation drought

Due to global warming, drought events have become more frequent, which resulted in aggravated crop failures, food shortage, larger and more energetic wildfires, and have seriously affected socio-economic development and agricultural production. In this study, a global long-term (1981–2021), high-res...

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Autores principales: Zeng, Jingyu, Zhou, Tao, Qu, Yanping, Bento, Virgílio A., Qi, Junyu, Xu, Yixin, Li, Ying, Wang, Qianfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232453/
https://www.ncbi.nlm.nih.gov/pubmed/37258520
http://dx.doi.org/10.1038/s41597-023-02255-3
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author Zeng, Jingyu
Zhou, Tao
Qu, Yanping
Bento, Virgílio A.
Qi, Junyu
Xu, Yixin
Li, Ying
Wang, Qianfeng
author_facet Zeng, Jingyu
Zhou, Tao
Qu, Yanping
Bento, Virgílio A.
Qi, Junyu
Xu, Yixin
Li, Ying
Wang, Qianfeng
author_sort Zeng, Jingyu
collection PubMed
description Due to global warming, drought events have become more frequent, which resulted in aggravated crop failures, food shortage, larger and more energetic wildfires, and have seriously affected socio-economic development and agricultural production. In this study, a global long-term (1981–2021), high-resolution (4 km) improved vegetation health index (VHI) dataset integrating climate, vegetation and soil moisture was developed. Based on drought records from the Emergency Event Database, we compared the detection efficiency of the VHI before and after its improvement in the occurrence and scope of observed drought events. The global drought detection efficiency of the improved high-resolution VHI dataset reached values as high as 85%, which is 14% higher than the original VHI dataset. The improved VHI dataset was also more sensitive to mild droughts and more accurate regarding the extent of droughts. This improved dataset can play an important role in long-term drought monitoring but also has the potential to assess the impact of drought on the agricultural, forestry, ecological and environmental sectors.
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spelling pubmed-102324532023-06-02 An improved global vegetation health index dataset in detecting vegetation drought Zeng, Jingyu Zhou, Tao Qu, Yanping Bento, Virgílio A. Qi, Junyu Xu, Yixin Li, Ying Wang, Qianfeng Sci Data Data Descriptor Due to global warming, drought events have become more frequent, which resulted in aggravated crop failures, food shortage, larger and more energetic wildfires, and have seriously affected socio-economic development and agricultural production. In this study, a global long-term (1981–2021), high-resolution (4 km) improved vegetation health index (VHI) dataset integrating climate, vegetation and soil moisture was developed. Based on drought records from the Emergency Event Database, we compared the detection efficiency of the VHI before and after its improvement in the occurrence and scope of observed drought events. The global drought detection efficiency of the improved high-resolution VHI dataset reached values as high as 85%, which is 14% higher than the original VHI dataset. The improved VHI dataset was also more sensitive to mild droughts and more accurate regarding the extent of droughts. This improved dataset can play an important role in long-term drought monitoring but also has the potential to assess the impact of drought on the agricultural, forestry, ecological and environmental sectors. Nature Publishing Group UK 2023-05-31 /pmc/articles/PMC10232453/ /pubmed/37258520 http://dx.doi.org/10.1038/s41597-023-02255-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Zeng, Jingyu
Zhou, Tao
Qu, Yanping
Bento, Virgílio A.
Qi, Junyu
Xu, Yixin
Li, Ying
Wang, Qianfeng
An improved global vegetation health index dataset in detecting vegetation drought
title An improved global vegetation health index dataset in detecting vegetation drought
title_full An improved global vegetation health index dataset in detecting vegetation drought
title_fullStr An improved global vegetation health index dataset in detecting vegetation drought
title_full_unstemmed An improved global vegetation health index dataset in detecting vegetation drought
title_short An improved global vegetation health index dataset in detecting vegetation drought
title_sort improved global vegetation health index dataset in detecting vegetation drought
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232453/
https://www.ncbi.nlm.nih.gov/pubmed/37258520
http://dx.doi.org/10.1038/s41597-023-02255-3
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