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Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions
Despite substantial research and policy interest in pixel level cropland allocation data, few sources are available that span a large geographic area. The data used for much of this research are derived from complex modeling techniques that may include model simulation and other data processing. We...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6181340/ https://www.ncbi.nlm.nih.gov/pubmed/30307995 http://dx.doi.org/10.1371/journal.pone.0205152 |
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author | Song, Jingyu Delgado, Michael S. Preckel, Paul V. Villoria, Nelson B. |
author_facet | Song, Jingyu Delgado, Michael S. Preckel, Paul V. Villoria, Nelson B. |
author_sort | Song, Jingyu |
collection | PubMed |
description | Despite substantial research and policy interest in pixel level cropland allocation data, few sources are available that span a large geographic area. The data used for much of this research are derived from complex modeling techniques that may include model simulation and other data processing. We develop a transparent econometric framework that uses pixel level biophysical measurements and aggregate cropland statistics to develop pixel level cropland allocation predictions. Such pixel level land use data can be used to investigate the impact of human activities on the environment. Validation exercises show that our approach is effective at downscaling cropland allocation to multiple levels of resolution. |
format | Online Article Text |
id | pubmed-6181340 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-61813402018-10-26 Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions Song, Jingyu Delgado, Michael S. Preckel, Paul V. Villoria, Nelson B. PLoS One Research Article Despite substantial research and policy interest in pixel level cropland allocation data, few sources are available that span a large geographic area. The data used for much of this research are derived from complex modeling techniques that may include model simulation and other data processing. We develop a transparent econometric framework that uses pixel level biophysical measurements and aggregate cropland statistics to develop pixel level cropland allocation predictions. Such pixel level land use data can be used to investigate the impact of human activities on the environment. Validation exercises show that our approach is effective at downscaling cropland allocation to multiple levels of resolution. Public Library of Science 2018-10-11 /pmc/articles/PMC6181340/ /pubmed/30307995 http://dx.doi.org/10.1371/journal.pone.0205152 Text en © 2018 Song et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Song, Jingyu Delgado, Michael S. Preckel, Paul V. Villoria, Nelson B. Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions |
title | Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions |
title_full | Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions |
title_fullStr | Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions |
title_full_unstemmed | Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions |
title_short | Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions |
title_sort | downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6181340/ https://www.ncbi.nlm.nih.gov/pubmed/30307995 http://dx.doi.org/10.1371/journal.pone.0205152 |
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