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Maps of cropping patterns in China during 2015–2021
Multiple cropping is a widespread approach for intensifying crop production through rotations of diverse crops. Maps of cropping intensity with crop descriptions are important for supporting sustainable agricultural management. As the most populated country, China ranked first in global cereal produ...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9356131/ https://www.ncbi.nlm.nih.gov/pubmed/35931696 http://dx.doi.org/10.1038/s41597-022-01589-8 |
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author | Qiu, Bingwen Hu, Xiang Chen, Chongcheng Tang, Zhenghong Yang, Peng Zhu, Xiaolin Yan, Chao Jian, Zeyu |
author_facet | Qiu, Bingwen Hu, Xiang Chen, Chongcheng Tang, Zhenghong Yang, Peng Zhu, Xiaolin Yan, Chao Jian, Zeyu |
author_sort | Qiu, Bingwen |
collection | PubMed |
description | Multiple cropping is a widespread approach for intensifying crop production through rotations of diverse crops. Maps of cropping intensity with crop descriptions are important for supporting sustainable agricultural management. As the most populated country, China ranked first in global cereal production and the percentages of multiple-cropped land are twice of the global average. However, there are no reliable updated national-scale maps of cropping patterns in China. Here we present the first recent annual 500-m MODIS-based national maps of multiple cropping systems in China using phenology-based mapping algorithms with pixel purity-based thresholds, which provide information on cropping intensity with descriptions of three staple crops (maize, paddy rice, and wheat). The produced cropping patterns maps achieved an overall accuracy of 89% based on ground truth data, and a good agreement with the statistical data (R(2) ≥ 0.89). The China Cropping Pattern maps (ChinaCP) are available for public download online. Cropping patterns maps in China and other countries with finer resolutions can be produced based on Sentinel-2 Multispectral Instrument (MSI) images using the shared code. |
format | Online Article Text |
id | pubmed-9356131 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93561312022-08-07 Maps of cropping patterns in China during 2015–2021 Qiu, Bingwen Hu, Xiang Chen, Chongcheng Tang, Zhenghong Yang, Peng Zhu, Xiaolin Yan, Chao Jian, Zeyu Sci Data Data Descriptor Multiple cropping is a widespread approach for intensifying crop production through rotations of diverse crops. Maps of cropping intensity with crop descriptions are important for supporting sustainable agricultural management. As the most populated country, China ranked first in global cereal production and the percentages of multiple-cropped land are twice of the global average. However, there are no reliable updated national-scale maps of cropping patterns in China. Here we present the first recent annual 500-m MODIS-based national maps of multiple cropping systems in China using phenology-based mapping algorithms with pixel purity-based thresholds, which provide information on cropping intensity with descriptions of three staple crops (maize, paddy rice, and wheat). The produced cropping patterns maps achieved an overall accuracy of 89% based on ground truth data, and a good agreement with the statistical data (R(2) ≥ 0.89). The China Cropping Pattern maps (ChinaCP) are available for public download online. Cropping patterns maps in China and other countries with finer resolutions can be produced based on Sentinel-2 Multispectral Instrument (MSI) images using the shared code. Nature Publishing Group UK 2022-08-05 /pmc/articles/PMC9356131/ /pubmed/35931696 http://dx.doi.org/10.1038/s41597-022-01589-8 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 Qiu, Bingwen Hu, Xiang Chen, Chongcheng Tang, Zhenghong Yang, Peng Zhu, Xiaolin Yan, Chao Jian, Zeyu Maps of cropping patterns in China during 2015–2021 |
title | Maps of cropping patterns in China during 2015–2021 |
title_full | Maps of cropping patterns in China during 2015–2021 |
title_fullStr | Maps of cropping patterns in China during 2015–2021 |
title_full_unstemmed | Maps of cropping patterns in China during 2015–2021 |
title_short | Maps of cropping patterns in China during 2015–2021 |
title_sort | maps of cropping patterns in china during 2015–2021 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9356131/ https://www.ncbi.nlm.nih.gov/pubmed/35931696 http://dx.doi.org/10.1038/s41597-022-01589-8 |
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