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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/16222
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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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1844614218012164096 |
score |
13.070432 |