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Estimating crop parameters using Sentinel-1 and 2 datasets and geospatial field data

Crop monitoring is essential for ensuring food security in a global context of population growth and climate change. Satellite images are commonly used to estimate crop parameters over large areas, and the freely available Synthetic Aperture Radar (SAR) Sentinel-1 (S-1) and optical Sentinel-2 (S-2)...

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Autores principales: Mercier, Audrey, Betbeder, Julie, Denize, Julien, Roger, Jean-Luc, Spicher, Fabien, Lacoux, Jérôme, Roger, David, Baudry, Jacques, Hubert-Moy, Laurence
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477130/
https://www.ncbi.nlm.nih.gov/pubmed/34611541
http://dx.doi.org/10.1016/j.dib.2021.107408
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author Mercier, Audrey
Betbeder, Julie
Denize, Julien
Roger, Jean-Luc
Spicher, Fabien
Lacoux, Jérôme
Roger, David
Baudry, Jacques
Hubert-Moy, Laurence
author_facet Mercier, Audrey
Betbeder, Julie
Denize, Julien
Roger, Jean-Luc
Spicher, Fabien
Lacoux, Jérôme
Roger, David
Baudry, Jacques
Hubert-Moy, Laurence
author_sort Mercier, Audrey
collection PubMed
description Crop monitoring is essential for ensuring food security in a global context of population growth and climate change. Satellite images are commonly used to estimate crop parameters over large areas, and the freely available Synthetic Aperture Radar (SAR) Sentinel-1 (S-1) and optical Sentinel-2 (S-2) images are relevant for that purpose combining high temporal resolution and high spatial resolution. For this data article, field surveys were conducted from January to July 2017 in France to sample wheat and rapeseed crop parameters during the entire crops cycle. Phenological stages were identified in 83 wheat fields and 32 rapeseed fields in Brittany and Picardy regions. Moreover, Leaf Area Index (LAI), wet biomass, dry biomass and water content were sampled in three wheat fields and three rapeseed fields in Brittany. We assigned to each field sample 10 spectral bands and 12 vegetation indices from S-2 images and two backscattering coefficients, one backscattering ratio and four polarimetric indicators from S-1 images. This dataset can be used for crop monitoring in other regions, as well as for modelling development.
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spelling pubmed-84771302021-10-04 Estimating crop parameters using Sentinel-1 and 2 datasets and geospatial field data Mercier, Audrey Betbeder, Julie Denize, Julien Roger, Jean-Luc Spicher, Fabien Lacoux, Jérôme Roger, David Baudry, Jacques Hubert-Moy, Laurence Data Brief Data Article Crop monitoring is essential for ensuring food security in a global context of population growth and climate change. Satellite images are commonly used to estimate crop parameters over large areas, and the freely available Synthetic Aperture Radar (SAR) Sentinel-1 (S-1) and optical Sentinel-2 (S-2) images are relevant for that purpose combining high temporal resolution and high spatial resolution. For this data article, field surveys were conducted from January to July 2017 in France to sample wheat and rapeseed crop parameters during the entire crops cycle. Phenological stages were identified in 83 wheat fields and 32 rapeseed fields in Brittany and Picardy regions. Moreover, Leaf Area Index (LAI), wet biomass, dry biomass and water content were sampled in three wheat fields and three rapeseed fields in Brittany. We assigned to each field sample 10 spectral bands and 12 vegetation indices from S-2 images and two backscattering coefficients, one backscattering ratio and four polarimetric indicators from S-1 images. This dataset can be used for crop monitoring in other regions, as well as for modelling development. Elsevier 2021-09-21 /pmc/articles/PMC8477130/ /pubmed/34611541 http://dx.doi.org/10.1016/j.dib.2021.107408 Text en © 2021 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Mercier, Audrey
Betbeder, Julie
Denize, Julien
Roger, Jean-Luc
Spicher, Fabien
Lacoux, Jérôme
Roger, David
Baudry, Jacques
Hubert-Moy, Laurence
Estimating crop parameters using Sentinel-1 and 2 datasets and geospatial field data
title Estimating crop parameters using Sentinel-1 and 2 datasets and geospatial field data
title_full Estimating crop parameters using Sentinel-1 and 2 datasets and geospatial field data
title_fullStr Estimating crop parameters using Sentinel-1 and 2 datasets and geospatial field data
title_full_unstemmed Estimating crop parameters using Sentinel-1 and 2 datasets and geospatial field data
title_short Estimating crop parameters using Sentinel-1 and 2 datasets and geospatial field data
title_sort estimating crop parameters using sentinel-1 and 2 datasets and geospatial field data
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477130/
https://www.ncbi.nlm.nih.gov/pubmed/34611541
http://dx.doi.org/10.1016/j.dib.2021.107408
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