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...

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Main Authors: Jingyu Song, Michael S Delgado, Paul V Preckel, Nelson B Villoria
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC6181340?pdf=render
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spelling doaj-2a3247f26e0045d18e4f25468107b9382020-11-25T02:33:33ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-011310e020515210.1371/journal.pone.0205152Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions.Jingyu SongMichael S DelgadoPaul V PreckelNelson B VilloriaDespite 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.http://europepmc.org/articles/PMC6181340?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Jingyu Song
Michael S Delgado
Paul V Preckel
Nelson B Villoria
spellingShingle Jingyu Song
Michael S Delgado
Paul V Preckel
Nelson B Villoria
Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions.
PLoS ONE
author_facet Jingyu Song
Michael S Delgado
Paul V Preckel
Nelson B Villoria
author_sort Jingyu Song
title 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_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_sort downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2018-01-01
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.
url http://europepmc.org/articles/PMC6181340?pdf=render
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AT paulvpreckel downscalingofnationalcropareastatisticsusingdriversofcroplandproductivitymeasuredatfineresolutions
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