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A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000–2018
Water colour is the result of its constituents and their interactions with solar irradiance; this forms the basis for water quality monitoring using optical remote sensing data. The Forel-Ule Index (FUI) is a useful comprehensive indicator to show the water colour variability and water quality chang...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7835379/ https://www.ncbi.nlm.nih.gov/pubmed/33495477 http://dx.doi.org/10.1038/s41597-021-00807-z |
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author | Wang, Shenglei Li, Junsheng Zhang, Wenzhi Cao, Chang Zhang, Fangfang Shen, Qian Zhang, Xianfeng Zhang, Bing |
author_facet | Wang, Shenglei Li, Junsheng Zhang, Wenzhi Cao, Chang Zhang, Fangfang Shen, Qian Zhang, Xianfeng Zhang, Bing |
author_sort | Wang, Shenglei |
collection | PubMed |
description | Water colour is the result of its constituents and their interactions with solar irradiance; this forms the basis for water quality monitoring using optical remote sensing data. The Forel-Ule Index (FUI) is a useful comprehensive indicator to show the water colour variability and water quality change in both inland waters and oceans. In recent decades, lakes around the world have experienced dramatic changes in water quality under pressure from both climate change and anthropogenic activities. However, acquiring consistent water colour products for global lakes has been a challenge. In this paper we present the first time series FUI dataset for large global lakes from 2000–2018 based on MODIS observations. This dataset provides significant information on spatial and temporal changes of water colour for global large lakes during the past 19 years. It will be valuable to studies in search of the drivers of global and regional lake colour change, and the interaction mechanisms between water colour, hydrological factors, climate change, and anthropogenic activities. |
format | Online Article Text |
id | pubmed-7835379 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78353792021-01-29 A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000–2018 Wang, Shenglei Li, Junsheng Zhang, Wenzhi Cao, Chang Zhang, Fangfang Shen, Qian Zhang, Xianfeng Zhang, Bing Sci Data Data Descriptor Water colour is the result of its constituents and their interactions with solar irradiance; this forms the basis for water quality monitoring using optical remote sensing data. The Forel-Ule Index (FUI) is a useful comprehensive indicator to show the water colour variability and water quality change in both inland waters and oceans. In recent decades, lakes around the world have experienced dramatic changes in water quality under pressure from both climate change and anthropogenic activities. However, acquiring consistent water colour products for global lakes has been a challenge. In this paper we present the first time series FUI dataset for large global lakes from 2000–2018 based on MODIS observations. This dataset provides significant information on spatial and temporal changes of water colour for global large lakes during the past 19 years. It will be valuable to studies in search of the drivers of global and regional lake colour change, and the interaction mechanisms between water colour, hydrological factors, climate change, and anthropogenic activities. Nature Publishing Group UK 2021-01-25 /pmc/articles/PMC7835379/ /pubmed/33495477 http://dx.doi.org/10.1038/s41597-021-00807-z Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Wang, Shenglei Li, Junsheng Zhang, Wenzhi Cao, Chang Zhang, Fangfang Shen, Qian Zhang, Xianfeng Zhang, Bing A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000–2018 |
title | A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000–2018 |
title_full | A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000–2018 |
title_fullStr | A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000–2018 |
title_full_unstemmed | A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000–2018 |
title_short | A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000–2018 |
title_sort | dataset of remote-sensed forel-ule index for global inland waters during 2000–2018 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7835379/ https://www.ncbi.nlm.nih.gov/pubmed/33495477 http://dx.doi.org/10.1038/s41597-021-00807-z |
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