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Crop Type Maps for Operational Global Agricultural Monitoring
Crop type maps identify the spatial distribution of crop types and underpin a large range of agricultural monitoring applications ranging from early warning of crop shortfalls, crop condition assessments, production forecasts, and damage assessment from extreme weather, to agricultural statistics, a...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050185/ https://www.ncbi.nlm.nih.gov/pubmed/36977689 http://dx.doi.org/10.1038/s41597-023-02047-9 |
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author | Becker-Reshef, Inbal Barker, Brian Whitcraft, Alyssa Oliva, Patricia Mobley, Kara Justice, Christina Sahajpal, Ritvik |
author_facet | Becker-Reshef, Inbal Barker, Brian Whitcraft, Alyssa Oliva, Patricia Mobley, Kara Justice, Christina Sahajpal, Ritvik |
author_sort | Becker-Reshef, Inbal |
collection | PubMed |
description | Crop type maps identify the spatial distribution of crop types and underpin a large range of agricultural monitoring applications ranging from early warning of crop shortfalls, crop condition assessments, production forecasts, and damage assessment from extreme weather, to agricultural statistics, agricultural insurance, and climate mitigation and adaptation decisions. Despite their importance, harmonized, up-to-date global crop type maps of the main food commodities do not exist to date. To address this critical data gap of global-scale consistent, up-to-date crop type maps, we harmonized 24 national and regional datasets from 21 sources covering 66 countries to develop a set of Best Available Crop Specific masks (BACS) over the major production and export countries for wheat, maize, rice, and soybeans, in the context of the G20 Global Agriculture Monitoring Program, GEOGLAM. |
format | Online Article Text |
id | pubmed-10050185 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100501852023-03-30 Crop Type Maps for Operational Global Agricultural Monitoring Becker-Reshef, Inbal Barker, Brian Whitcraft, Alyssa Oliva, Patricia Mobley, Kara Justice, Christina Sahajpal, Ritvik Sci Data Data Descriptor Crop type maps identify the spatial distribution of crop types and underpin a large range of agricultural monitoring applications ranging from early warning of crop shortfalls, crop condition assessments, production forecasts, and damage assessment from extreme weather, to agricultural statistics, agricultural insurance, and climate mitigation and adaptation decisions. Despite their importance, harmonized, up-to-date global crop type maps of the main food commodities do not exist to date. To address this critical data gap of global-scale consistent, up-to-date crop type maps, we harmonized 24 national and regional datasets from 21 sources covering 66 countries to develop a set of Best Available Crop Specific masks (BACS) over the major production and export countries for wheat, maize, rice, and soybeans, in the context of the G20 Global Agriculture Monitoring Program, GEOGLAM. Nature Publishing Group UK 2023-03-28 /pmc/articles/PMC10050185/ /pubmed/36977689 http://dx.doi.org/10.1038/s41597-023-02047-9 Text en © The Author(s) 2023 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 Becker-Reshef, Inbal Barker, Brian Whitcraft, Alyssa Oliva, Patricia Mobley, Kara Justice, Christina Sahajpal, Ritvik Crop Type Maps for Operational Global Agricultural Monitoring |
title | Crop Type Maps for Operational Global Agricultural Monitoring |
title_full | Crop Type Maps for Operational Global Agricultural Monitoring |
title_fullStr | Crop Type Maps for Operational Global Agricultural Monitoring |
title_full_unstemmed | Crop Type Maps for Operational Global Agricultural Monitoring |
title_short | Crop Type Maps for Operational Global Agricultural Monitoring |
title_sort | crop type maps for operational global agricultural monitoring |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050185/ https://www.ncbi.nlm.nih.gov/pubmed/36977689 http://dx.doi.org/10.1038/s41597-023-02047-9 |
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