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A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to wheat yield monitoring

The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing dataset that ranges from the 1980’s to the present. Over the years, several efforts have been made on the calibration of the different instruments to establish a consistent land surface reflectance ti...

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Autores principales: Franch, Belen, Vermote, Eric F., Roger, Jean-Claude, Murphy, Emilie, Becker-Reshef, Inbal, Justice, Chris, Claverie, Martin, Nagol, Jyoteshwar, Csiszar, Ivan, Meyer, Dave, Baret, Frederic, Masuoka, Edward, Wolfe, Robert, Devadiga, Sadashiva
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6999664/
https://www.ncbi.nlm.nih.gov/pubmed/32021703
http://dx.doi.org/10.3390/rs9030296
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author Franch, Belen
Vermote, Eric F.
Roger, Jean-Claude
Murphy, Emilie
Becker-Reshef, Inbal
Justice, Chris
Claverie, Martin
Nagol, Jyoteshwar
Csiszar, Ivan
Meyer, Dave
Baret, Frederic
Masuoka, Edward
Wolfe, Robert
Devadiga, Sadashiva
author_facet Franch, Belen
Vermote, Eric F.
Roger, Jean-Claude
Murphy, Emilie
Becker-Reshef, Inbal
Justice, Chris
Claverie, Martin
Nagol, Jyoteshwar
Csiszar, Ivan
Meyer, Dave
Baret, Frederic
Masuoka, Edward
Wolfe, Robert
Devadiga, Sadashiva
author_sort Franch, Belen
collection PubMed
description The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing dataset that ranges from the 1980’s to the present. Over the years, several efforts have been made on the calibration of the different instruments to establish a consistent land surface reflectance time-series and to augment the AVHRR data record with data from other sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS). In this paper, we present a summary of all the corrections applied to the AVHRR Surface Reflectance and NDVI Version 4 Product, developed in the framework of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) program. These corrections result from assessment of the geo-location, improvement of the cloud masking and calibration monitoring. Additionally, we evaluate the performance of the surface reflectance over the AERONET sites by a cross-comparison with MODIS, which is an already validated product, and evaluation of a downstream Leaf Area Index (LAI) product. We demonstrate the utility of this long time-series by estimating the winter wheat yield over the USA. The methods developed by [1] and [2] are applied to both the MODIS and AVHRR data. Comparison of the results from both sensors during the MODIS-era shows the consistency of the dataset with similar errors of 10%. When applying the methods to AVHRR historical data from the 1980’s, the results have errors equivalent to those derived from MODIS.
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spelling pubmed-69996642020-02-04 A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to wheat yield monitoring Franch, Belen Vermote, Eric F. Roger, Jean-Claude Murphy, Emilie Becker-Reshef, Inbal Justice, Chris Claverie, Martin Nagol, Jyoteshwar Csiszar, Ivan Meyer, Dave Baret, Frederic Masuoka, Edward Wolfe, Robert Devadiga, Sadashiva Remote Sens (Basel) Article The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing dataset that ranges from the 1980’s to the present. Over the years, several efforts have been made on the calibration of the different instruments to establish a consistent land surface reflectance time-series and to augment the AVHRR data record with data from other sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS). In this paper, we present a summary of all the corrections applied to the AVHRR Surface Reflectance and NDVI Version 4 Product, developed in the framework of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) program. These corrections result from assessment of the geo-location, improvement of the cloud masking and calibration monitoring. Additionally, we evaluate the performance of the surface reflectance over the AERONET sites by a cross-comparison with MODIS, which is an already validated product, and evaluation of a downstream Leaf Area Index (LAI) product. We demonstrate the utility of this long time-series by estimating the winter wheat yield over the USA. The methods developed by [1] and [2] are applied to both the MODIS and AVHRR data. Comparison of the results from both sensors during the MODIS-era shows the consistency of the dataset with similar errors of 10%. When applying the methods to AVHRR historical data from the 1980’s, the results have errors equivalent to those derived from MODIS. 2017-03-21 /pmc/articles/PMC6999664/ /pubmed/32021703 http://dx.doi.org/10.3390/rs9030296 Text en Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Franch, Belen
Vermote, Eric F.
Roger, Jean-Claude
Murphy, Emilie
Becker-Reshef, Inbal
Justice, Chris
Claverie, Martin
Nagol, Jyoteshwar
Csiszar, Ivan
Meyer, Dave
Baret, Frederic
Masuoka, Edward
Wolfe, Robert
Devadiga, Sadashiva
A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to wheat yield monitoring
title A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to wheat yield monitoring
title_full A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to wheat yield monitoring
title_fullStr A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to wheat yield monitoring
title_full_unstemmed A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to wheat yield monitoring
title_short A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to wheat yield monitoring
title_sort 30+ year avhrr land surface reflectance climate data record and its application to wheat yield monitoring
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6999664/
https://www.ncbi.nlm.nih.gov/pubmed/32021703
http://dx.doi.org/10.3390/rs9030296
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