Cargando…

Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive

Field-level monitoring of crop types in the United States via the Cropland Data Layer (CDL) has played an important role in improving production forecasts and enabling large-scale study of agricultural inputs and outcomes. Although CDL offers crop type maps across the conterminous US from 2008 onwar...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Sherrie, Di Tommaso, Stefania, Deines, Jillian M., Lobell, David B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493954/
https://www.ncbi.nlm.nih.gov/pubmed/32934216
http://dx.doi.org/10.1038/s41597-020-00646-4
_version_ 1783582662098681856
author Wang, Sherrie
Di Tommaso, Stefania
Deines, Jillian M.
Lobell, David B.
author_facet Wang, Sherrie
Di Tommaso, Stefania
Deines, Jillian M.
Lobell, David B.
author_sort Wang, Sherrie
collection PubMed
description Field-level monitoring of crop types in the United States via the Cropland Data Layer (CDL) has played an important role in improving production forecasts and enabling large-scale study of agricultural inputs and outcomes. Although CDL offers crop type maps across the conterminous US from 2008 onward, such maps are missing in many Midwestern states or are uneven in quality before 2008. To fill these data gaps, we used the now-public Landsat archive and cloud computing services to map corn and soybean at 30 m resolution across the US Midwest from 1999–2018. Our training data were CDL from 2008–2018, and we validated the predictions on CDL 1999–2007 where available, county-level crop acreage statistics, and state-level crop rotation statistics. The corn-soybean maps, which we call the Corn-Soy Data Layer (CSDL), are publicly hosted on Google Earth Engine and also available for download online.
format Online
Article
Text
id pubmed-7493954
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-74939542020-10-01 Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive Wang, Sherrie Di Tommaso, Stefania Deines, Jillian M. Lobell, David B. Sci Data Data Descriptor Field-level monitoring of crop types in the United States via the Cropland Data Layer (CDL) has played an important role in improving production forecasts and enabling large-scale study of agricultural inputs and outcomes. Although CDL offers crop type maps across the conterminous US from 2008 onward, such maps are missing in many Midwestern states or are uneven in quality before 2008. To fill these data gaps, we used the now-public Landsat archive and cloud computing services to map corn and soybean at 30 m resolution across the US Midwest from 1999–2018. Our training data were CDL from 2008–2018, and we validated the predictions on CDL 1999–2007 where available, county-level crop acreage statistics, and state-level crop rotation statistics. The corn-soybean maps, which we call the Corn-Soy Data Layer (CSDL), are publicly hosted on Google Earth Engine and also available for download online. Nature Publishing Group UK 2020-09-15 /pmc/articles/PMC7493954/ /pubmed/32934216 http://dx.doi.org/10.1038/s41597-020-00646-4 Text en © The Author(s) 2020 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, Sherrie
Di Tommaso, Stefania
Deines, Jillian M.
Lobell, David B.
Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive
title Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive
title_full Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive
title_fullStr Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive
title_full_unstemmed Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive
title_short Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive
title_sort mapping twenty years of corn and soybean across the us midwest using the landsat archive
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493954/
https://www.ncbi.nlm.nih.gov/pubmed/32934216
http://dx.doi.org/10.1038/s41597-020-00646-4
work_keys_str_mv AT wangsherrie mappingtwentyyearsofcornandsoybeanacrosstheusmidwestusingthelandsatarchive
AT ditommasostefania mappingtwentyyearsofcornandsoybeanacrosstheusmidwestusingthelandsatarchive
AT deinesjillianm mappingtwentyyearsofcornandsoybeanacrosstheusmidwestusingthelandsatarchive
AT lobelldavidb mappingtwentyyearsofcornandsoybeanacrosstheusmidwestusingthelandsatarchive