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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...

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Detalles Bibliográficos
Autores principales: Becker-Reshef, Inbal, Barker, Brian, Whitcraft, Alyssa, Oliva, Patricia, Mobley, Kara, Justice, Christina, Sahajpal, Ritvik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
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.
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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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