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A data set of distributed global population and water withdrawal from 1960 to 2020
Population and water withdrawal data sets are currently faced with difficulties in collecting, processing and verifying multi-source time series, and the spatial distribution characteristics of long series are also relatively lacking. Time series is the basic guarantee for the accuracy of data sets,...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9587213/ https://www.ncbi.nlm.nih.gov/pubmed/36271026 http://dx.doi.org/10.1038/s41597-022-01760-1 |
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| author | Yan, Denghua Zhang, Xin Qin, Tianling Li, Chenhao Zhang, Jianyun Wang, Hao Weng, Baisha Wang, Kun Liu, Shanshan Li, Xiangnan Yang, Yuheng Li, Weizhi Lv, Zhenyu Wang, Jianwei Li, Meng He, Shan Liu, Fang Bi, Wuxia Xu, Ting Shi, Xiaoqing Man, Zihao Sun, Congwu Liu, Meiyu Wang, Mengke Huang, Yinghou Long, Haoyu Niu, Yongzhen Dorjsuren, Batsuren Gedefaw, Mohammed Li, Yizhe Tian, Zihao Mu, Shizhou Wang, Wenyu Zhou, Xiaoxiang |
| author_facet | Yan, Denghua Zhang, Xin Qin, Tianling Li, Chenhao Zhang, Jianyun Wang, Hao Weng, Baisha Wang, Kun Liu, Shanshan Li, Xiangnan Yang, Yuheng Li, Weizhi Lv, Zhenyu Wang, Jianwei Li, Meng He, Shan Liu, Fang Bi, Wuxia Xu, Ting Shi, Xiaoqing Man, Zihao Sun, Congwu Liu, Meiyu Wang, Mengke Huang, Yinghou Long, Haoyu Niu, Yongzhen Dorjsuren, Batsuren Gedefaw, Mohammed Li, Yizhe Tian, Zihao Mu, Shizhou Wang, Wenyu Zhou, Xiaoxiang |
| author_sort | Yan, Denghua |
| collection | PubMed |
| description | Population and water withdrawal data sets are currently faced with difficulties in collecting, processing and verifying multi-source time series, and the spatial distribution characteristics of long series are also relatively lacking. Time series is the basic guarantee for the accuracy of data sets, and the production of long series spatial distribution is a realistic requirement to expand the application scope of data sets. Through the time-consuming and laborious basic processing work, this research focuses on the population and water intake time series, and interpolates and extends them to specific land uses to ensure the accuracy of the time series and the demand of spatially distributed data sets. This research provides a set of population density and water intensity products from 1960 to 2020 distributed to the administrative units or the corresponding regions. The data set fills the gaps in the multi-year data set for the accuracy of population density and the intensity of water withdrawal. |
| format | Online Article Text |
| id | pubmed-9587213 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2022 |
| publisher | Nature Publishing Group UK |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-95872132022-10-23 A data set of distributed global population and water withdrawal from 1960 to 2020 Yan, Denghua Zhang, Xin Qin, Tianling Li, Chenhao Zhang, Jianyun Wang, Hao Weng, Baisha Wang, Kun Liu, Shanshan Li, Xiangnan Yang, Yuheng Li, Weizhi Lv, Zhenyu Wang, Jianwei Li, Meng He, Shan Liu, Fang Bi, Wuxia Xu, Ting Shi, Xiaoqing Man, Zihao Sun, Congwu Liu, Meiyu Wang, Mengke Huang, Yinghou Long, Haoyu Niu, Yongzhen Dorjsuren, Batsuren Gedefaw, Mohammed Li, Yizhe Tian, Zihao Mu, Shizhou Wang, Wenyu Zhou, Xiaoxiang Sci Data Data Descriptor Population and water withdrawal data sets are currently faced with difficulties in collecting, processing and verifying multi-source time series, and the spatial distribution characteristics of long series are also relatively lacking. Time series is the basic guarantee for the accuracy of data sets, and the production of long series spatial distribution is a realistic requirement to expand the application scope of data sets. Through the time-consuming and laborious basic processing work, this research focuses on the population and water intake time series, and interpolates and extends them to specific land uses to ensure the accuracy of the time series and the demand of spatially distributed data sets. This research provides a set of population density and water intensity products from 1960 to 2020 distributed to the administrative units or the corresponding regions. The data set fills the gaps in the multi-year data set for the accuracy of population density and the intensity of water withdrawal. Nature Publishing Group UK 2022-10-21 /pmc/articles/PMC9587213/ /pubmed/36271026 http://dx.doi.org/10.1038/s41597-022-01760-1 Text en © The Author(s) 2022 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 Yan, Denghua Zhang, Xin Qin, Tianling Li, Chenhao Zhang, Jianyun Wang, Hao Weng, Baisha Wang, Kun Liu, Shanshan Li, Xiangnan Yang, Yuheng Li, Weizhi Lv, Zhenyu Wang, Jianwei Li, Meng He, Shan Liu, Fang Bi, Wuxia Xu, Ting Shi, Xiaoqing Man, Zihao Sun, Congwu Liu, Meiyu Wang, Mengke Huang, Yinghou Long, Haoyu Niu, Yongzhen Dorjsuren, Batsuren Gedefaw, Mohammed Li, Yizhe Tian, Zihao Mu, Shizhou Wang, Wenyu Zhou, Xiaoxiang A data set of distributed global population and water withdrawal from 1960 to 2020 |
| title | A data set of distributed global population and water withdrawal from 1960 to 2020 |
| title_full | A data set of distributed global population and water withdrawal from 1960 to 2020 |
| title_fullStr | A data set of distributed global population and water withdrawal from 1960 to 2020 |
| title_full_unstemmed | A data set of distributed global population and water withdrawal from 1960 to 2020 |
| title_short | A data set of distributed global population and water withdrawal from 1960 to 2020 |
| title_sort | data set of distributed global population and water withdrawal from 1960 to 2020 |
| topic | Data Descriptor |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9587213/ https://www.ncbi.nlm.nih.gov/pubmed/36271026 http://dx.doi.org/10.1038/s41597-022-01760-1 |
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