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Wind farms dry surface soil in temporal and spatial variation

Wind farms have been proved to have potential impact on the ecology. As an important ecological factor, soil moisture has a great impact on the ecosystem. Therefore, it is of great significance to explore the effect of wind farms on soil moisture. At present, the remote sensing data can be used to c...

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Detalles Bibliográficos
Autores principales: Wang, Gang, Li, Guoqing, Liu, Zhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9842675/
https://www.ncbi.nlm.nih.gov/pubmed/36660340
http://dx.doi.org/10.1016/j.mex.2023.102000
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author Wang, Gang
Li, Guoqing
Liu, Zhe
author_facet Wang, Gang
Li, Guoqing
Liu, Zhe
author_sort Wang, Gang
collection PubMed
description Wind farms have been proved to have potential impact on the ecology. As an important ecological factor, soil moisture has a great impact on the ecosystem. Therefore, it is of great significance to explore the effect of wind farms on soil moisture. At present, the remote sensing data can be used to calculate the soil moisture of wind farm conveniently, but its spatial resolution is poor. Moreover, the measured soil moisture can't express the spatial difference. Therefore, through the effective combination of remote sensing data and measured data, this method can accurately judge the impact of wind farm on soil moisture. This method investigated wind farms located in the grasslands of China. Remote sensing images and field data were used to explore the area and extent of influence of wind farms on grassland soil moisture. We use Landsat images and field measurements to derive a linear relationship between the soil moisture and the TVDI, which was calculated based on the land surface temperature and NDVI, was developed in this work. The correlation was used to reverse spatial distribution map of soil moisture before and after the construction of wind farms. The diurnal and seasonal variation of the influence of the wind farm on the grassland soil moisture was also judged. • This method of combining measurement and remote sensing provides a reference for analysing the influence of wind farms on soil moisture. • This method can be used for reference to compare the meteorological factors of different wind directions before and after the construction of wind farms.
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spelling pubmed-98426752023-01-18 Wind farms dry surface soil in temporal and spatial variation Wang, Gang Li, Guoqing Liu, Zhe MethodsX Method Article Wind farms have been proved to have potential impact on the ecology. As an important ecological factor, soil moisture has a great impact on the ecosystem. Therefore, it is of great significance to explore the effect of wind farms on soil moisture. At present, the remote sensing data can be used to calculate the soil moisture of wind farm conveniently, but its spatial resolution is poor. Moreover, the measured soil moisture can't express the spatial difference. Therefore, through the effective combination of remote sensing data and measured data, this method can accurately judge the impact of wind farm on soil moisture. This method investigated wind farms located in the grasslands of China. Remote sensing images and field data were used to explore the area and extent of influence of wind farms on grassland soil moisture. We use Landsat images and field measurements to derive a linear relationship between the soil moisture and the TVDI, which was calculated based on the land surface temperature and NDVI, was developed in this work. The correlation was used to reverse spatial distribution map of soil moisture before and after the construction of wind farms. The diurnal and seasonal variation of the influence of the wind farm on the grassland soil moisture was also judged. • This method of combining measurement and remote sensing provides a reference for analysing the influence of wind farms on soil moisture. • This method can be used for reference to compare the meteorological factors of different wind directions before and after the construction of wind farms. Elsevier 2023-01-02 /pmc/articles/PMC9842675/ /pubmed/36660340 http://dx.doi.org/10.1016/j.mex.2023.102000 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method Article
Wang, Gang
Li, Guoqing
Liu, Zhe
Wind farms dry surface soil in temporal and spatial variation
title Wind farms dry surface soil in temporal and spatial variation
title_full Wind farms dry surface soil in temporal and spatial variation
title_fullStr Wind farms dry surface soil in temporal and spatial variation
title_full_unstemmed Wind farms dry surface soil in temporal and spatial variation
title_short Wind farms dry surface soil in temporal and spatial variation
title_sort wind farms dry surface soil in temporal and spatial variation
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9842675/
https://www.ncbi.nlm.nih.gov/pubmed/36660340
http://dx.doi.org/10.1016/j.mex.2023.102000
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