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Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model

BACKGROUND: Associated with the significant decrease in water resources, natural vegetation degradation has also led to many widespread environmental problems in the Aral Sea Basin. However, few studies have examined long-term vegetation dynamics in the Aral Sea Basin or distinguished between natura...

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Autores principales: Su, Yiting, Wang, Dongchuan, Zhao, Shuang, Shi, Jiancong, Shi, Yanqing, Wei, Dongying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7934649/
https://www.ncbi.nlm.nih.gov/pubmed/33717666
http://dx.doi.org/10.7717/peerj.10747
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author Su, Yiting
Wang, Dongchuan
Zhao, Shuang
Shi, Jiancong
Shi, Yanqing
Wei, Dongying
author_facet Su, Yiting
Wang, Dongchuan
Zhao, Shuang
Shi, Jiancong
Shi, Yanqing
Wei, Dongying
author_sort Su, Yiting
collection PubMed
description BACKGROUND: Associated with the significant decrease in water resources, natural vegetation degradation has also led to many widespread environmental problems in the Aral Sea Basin. However, few studies have examined long-term vegetation dynamics in the Aral Sea Basin or distinguished between natural vegetation and cultivated land when calculating the fractional vegetation cover. METHODS: Based on the multi-temporal Moderate Resolution Imaging Spectroradiometer, this study examined the natural vegetation coverage by introducing the Linear Spectral Mixture Model to the Google Earth Engine platform, which greatly reduces the experimental time. Further, trend line analysis, Sen trend analysis, and Mann–Kendall trend test methods were employed to explore the characteristics of natural vegetation cover change in the Aral Sea Basin from 2000 to 2018. RESULTS: Analyses of the results suggest three major conclusions. First, the development of irrigated agriculture in the desert area is the main reason for the decrease in downstream water. Second, with the reduction of water, the natural vegetation coverage in the Aral Sea Basin showed an upward trend of 17.77% from 2000 to 2018. Finally, the main driving factor of vegetation cover changes in the Aral Sea Basin is the migration of cultivated land to the desert.
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spelling pubmed-79346492021-03-11 Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model Su, Yiting Wang, Dongchuan Zhao, Shuang Shi, Jiancong Shi, Yanqing Wei, Dongying PeerJ Ecosystem Science BACKGROUND: Associated with the significant decrease in water resources, natural vegetation degradation has also led to many widespread environmental problems in the Aral Sea Basin. However, few studies have examined long-term vegetation dynamics in the Aral Sea Basin or distinguished between natural vegetation and cultivated land when calculating the fractional vegetation cover. METHODS: Based on the multi-temporal Moderate Resolution Imaging Spectroradiometer, this study examined the natural vegetation coverage by introducing the Linear Spectral Mixture Model to the Google Earth Engine platform, which greatly reduces the experimental time. Further, trend line analysis, Sen trend analysis, and Mann–Kendall trend test methods were employed to explore the characteristics of natural vegetation cover change in the Aral Sea Basin from 2000 to 2018. RESULTS: Analyses of the results suggest three major conclusions. First, the development of irrigated agriculture in the desert area is the main reason for the decrease in downstream water. Second, with the reduction of water, the natural vegetation coverage in the Aral Sea Basin showed an upward trend of 17.77% from 2000 to 2018. Finally, the main driving factor of vegetation cover changes in the Aral Sea Basin is the migration of cultivated land to the desert. PeerJ Inc. 2021-03-02 /pmc/articles/PMC7934649/ /pubmed/33717666 http://dx.doi.org/10.7717/peerj.10747 Text en © 2021 Su et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Ecosystem Science
Su, Yiting
Wang, Dongchuan
Zhao, Shuang
Shi, Jiancong
Shi, Yanqing
Wei, Dongying
Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model
title Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model
title_full Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model
title_fullStr Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model
title_full_unstemmed Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model
title_short Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model
title_sort examining long-term natural vegetation dynamics in the aral sea basin applying the linear spectral mixture model
topic Ecosystem Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7934649/
https://www.ncbi.nlm.nih.gov/pubmed/33717666
http://dx.doi.org/10.7717/peerj.10747
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