Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series

Autores
de Abelleyra, Diego; Verón, Santiago Ramón
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Realizing the full benefits of MODIS' temporal resolution requires, among others, the correction of the directional effect (i.e. the combined impact of the variation of the measurement geometry and of the observed land surface upon the registered radiant flux). While different BRDF methods have been proposed to address this effect, its performance has been evaluated at coarse spatial resolutions making it difficult to assess its applicability to, for example, crop monitoring. Here we test 2 approaches based on two different assumptions: the Classic approach that relies on the hypothesis of stable target and a recent Alternative that is based on the idea that despite reflectance magnitude may change rapidly, the BRDF shape varies slowly in time. Additionally, we segmented the growing season into different numbers of periods for the BRDF correction (a single period along the growing season, 3 periods based in phenology and 9–12 periods of fixed 16-days). The resulting 6 methods were compared over annual crops (wheat, maize and soybean) at 250 m spatial resolution from a site located in the Argentine Pampas. We used MOD and MYD 09 GQ and GA as inputs and compared the corrected daily red and infrared reflectances and the NDVI time series against the filtered benchmark (input time series with quality filters applied) by means of the high frequency variability (i.e. noise). We also tested whether corrected time series were better correlated with soybean PAR interception and biomass. Our results showed that methods' performance was more explained by the number of periods than by the approach (Classic or Alternative). Single period methods decreased noise by 52%, 55% and 4% for red, infrared and NDVI time series. The use of 3 periods improved the correction performance to 63, 64 and 24% for red, infrared and NVDI time series respectively, while the highest reductions (65, 68 and 32% for red, infrared and NVDI) were found with 16-day intervals (9–12 periods) considering a magnitude inversion process. Wheat displayed the lowest noise reduction compared to the other crops. BRDF parameters obtained from different methods were associated to crop structure, suggesting that they have biophysical meaning. The decrease in noise obtained with correction methods was translated into a better assessment of the fraction of intercepted PAR and biomass. These promising results suggest the possibility of extensive field crop monitoring at an unprecedented temporal resolution.
Fil: de Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Fil: Verón, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Surface Reflectance
Directional Effects
Hyper-Temporal
Crop Monitoring Modis 250 Brdf
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/16222

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network_name_str CONICET Digital (CONICET)
spelling Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time seriesde Abelleyra, DiegoVerón, Santiago RamónSurface ReflectanceDirectional EffectsHyper-TemporalCrop Monitoring Modis 250 Brdfhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Realizing the full benefits of MODIS' temporal resolution requires, among others, the correction of the directional effect (i.e. the combined impact of the variation of the measurement geometry and of the observed land surface upon the registered radiant flux). While different BRDF methods have been proposed to address this effect, its performance has been evaluated at coarse spatial resolutions making it difficult to assess its applicability to, for example, crop monitoring. Here we test 2 approaches based on two different assumptions: the Classic approach that relies on the hypothesis of stable target and a recent Alternative that is based on the idea that despite reflectance magnitude may change rapidly, the BRDF shape varies slowly in time. Additionally, we segmented the growing season into different numbers of periods for the BRDF correction (a single period along the growing season, 3 periods based in phenology and 9–12 periods of fixed 16-days). The resulting 6 methods were compared over annual crops (wheat, maize and soybean) at 250 m spatial resolution from a site located in the Argentine Pampas. We used MOD and MYD 09 GQ and GA as inputs and compared the corrected daily red and infrared reflectances and the NDVI time series against the filtered benchmark (input time series with quality filters applied) by means of the high frequency variability (i.e. noise). We also tested whether corrected time series were better correlated with soybean PAR interception and biomass. Our results showed that methods' performance was more explained by the number of periods than by the approach (Classic or Alternative). Single period methods decreased noise by 52%, 55% and 4% for red, infrared and NDVI time series. The use of 3 periods improved the correction performance to 63, 64 and 24% for red, infrared and NVDI time series respectively, while the highest reductions (65, 68 and 32% for red, infrared and NVDI) were found with 16-day intervals (9–12 periods) considering a magnitude inversion process. Wheat displayed the lowest noise reduction compared to the other crops. BRDF parameters obtained from different methods were associated to crop structure, suggesting that they have biophysical meaning. The decrease in noise obtained with correction methods was translated into a better assessment of the fraction of intercepted PAR and biomass. These promising results suggest the possibility of extensive field crop monitoring at an unprecedented temporal resolution.Fil: de Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; ArgentinaFil: Verón, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaElsevier Science Inc2014-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/16222de Abelleyra, Diego; Verón, Santiago Ramón; Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series; Elsevier Science Inc; Remote Sensing Of Environment; 140; 1-2014; 46-590034-4257enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2013.08.019info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0034425713002770info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:22:36Zoai:ri.conicet.gov.ar:11336/16222instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:22:36.975CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series
title Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series
spellingShingle Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series
de Abelleyra, Diego
Surface Reflectance
Directional Effects
Hyper-Temporal
Crop Monitoring Modis 250 Brdf
title_short Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series
title_full Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series
title_fullStr Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series
title_full_unstemmed Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series
title_sort Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series
dc.creator.none.fl_str_mv de Abelleyra, Diego
Verón, Santiago Ramón
author de Abelleyra, Diego
author_facet de Abelleyra, Diego
Verón, Santiago Ramón
author_role author
author2 Verón, Santiago Ramón
author2_role author
dc.subject.none.fl_str_mv Surface Reflectance
Directional Effects
Hyper-Temporal
Crop Monitoring Modis 250 Brdf
topic Surface Reflectance
Directional Effects
Hyper-Temporal
Crop Monitoring Modis 250 Brdf
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Realizing the full benefits of MODIS' temporal resolution requires, among others, the correction of the directional effect (i.e. the combined impact of the variation of the measurement geometry and of the observed land surface upon the registered radiant flux). While different BRDF methods have been proposed to address this effect, its performance has been evaluated at coarse spatial resolutions making it difficult to assess its applicability to, for example, crop monitoring. Here we test 2 approaches based on two different assumptions: the Classic approach that relies on the hypothesis of stable target and a recent Alternative that is based on the idea that despite reflectance magnitude may change rapidly, the BRDF shape varies slowly in time. Additionally, we segmented the growing season into different numbers of periods for the BRDF correction (a single period along the growing season, 3 periods based in phenology and 9–12 periods of fixed 16-days). The resulting 6 methods were compared over annual crops (wheat, maize and soybean) at 250 m spatial resolution from a site located in the Argentine Pampas. We used MOD and MYD 09 GQ and GA as inputs and compared the corrected daily red and infrared reflectances and the NDVI time series against the filtered benchmark (input time series with quality filters applied) by means of the high frequency variability (i.e. noise). We also tested whether corrected time series were better correlated with soybean PAR interception and biomass. Our results showed that methods' performance was more explained by the number of periods than by the approach (Classic or Alternative). Single period methods decreased noise by 52%, 55% and 4% for red, infrared and NDVI time series. The use of 3 periods improved the correction performance to 63, 64 and 24% for red, infrared and NVDI time series respectively, while the highest reductions (65, 68 and 32% for red, infrared and NVDI) were found with 16-day intervals (9–12 periods) considering a magnitude inversion process. Wheat displayed the lowest noise reduction compared to the other crops. BRDF parameters obtained from different methods were associated to crop structure, suggesting that they have biophysical meaning. The decrease in noise obtained with correction methods was translated into a better assessment of the fraction of intercepted PAR and biomass. These promising results suggest the possibility of extensive field crop monitoring at an unprecedented temporal resolution.
Fil: de Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Fil: Verón, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Realizing the full benefits of MODIS' temporal resolution requires, among others, the correction of the directional effect (i.e. the combined impact of the variation of the measurement geometry and of the observed land surface upon the registered radiant flux). While different BRDF methods have been proposed to address this effect, its performance has been evaluated at coarse spatial resolutions making it difficult to assess its applicability to, for example, crop monitoring. Here we test 2 approaches based on two different assumptions: the Classic approach that relies on the hypothesis of stable target and a recent Alternative that is based on the idea that despite reflectance magnitude may change rapidly, the BRDF shape varies slowly in time. Additionally, we segmented the growing season into different numbers of periods for the BRDF correction (a single period along the growing season, 3 periods based in phenology and 9–12 periods of fixed 16-days). The resulting 6 methods were compared over annual crops (wheat, maize and soybean) at 250 m spatial resolution from a site located in the Argentine Pampas. We used MOD and MYD 09 GQ and GA as inputs and compared the corrected daily red and infrared reflectances and the NDVI time series against the filtered benchmark (input time series with quality filters applied) by means of the high frequency variability (i.e. noise). We also tested whether corrected time series were better correlated with soybean PAR interception and biomass. Our results showed that methods' performance was more explained by the number of periods than by the approach (Classic or Alternative). Single period methods decreased noise by 52%, 55% and 4% for red, infrared and NDVI time series. The use of 3 periods improved the correction performance to 63, 64 and 24% for red, infrared and NVDI time series respectively, while the highest reductions (65, 68 and 32% for red, infrared and NVDI) were found with 16-day intervals (9–12 periods) considering a magnitude inversion process. Wheat displayed the lowest noise reduction compared to the other crops. BRDF parameters obtained from different methods were associated to crop structure, suggesting that they have biophysical meaning. The decrease in noise obtained with correction methods was translated into a better assessment of the fraction of intercepted PAR and biomass. These promising results suggest the possibility of extensive field crop monitoring at an unprecedented temporal resolution.
publishDate 2014
dc.date.none.fl_str_mv 2014-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/16222
de Abelleyra, Diego; Verón, Santiago Ramón; Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series; Elsevier Science Inc; Remote Sensing Of Environment; 140; 1-2014; 46-59
0034-4257
url http://hdl.handle.net/11336/16222
identifier_str_mv de Abelleyra, Diego; Verón, Santiago Ramón; Comparison of different BRDF correction methods to generate daily normalized MODIS 250 m time series; Elsevier Science Inc; Remote Sensing Of Environment; 140; 1-2014; 46-59
0034-4257
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2013.08.019
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0034425713002770
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science Inc
publisher.none.fl_str_mv Elsevier Science Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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