Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland

Autores
Lara, Bruno Daniel; Gandini, Marcelo Luciano
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
NDVI (Normalized Difference Vegetation Index) time-series have beenused for permitting a land surface phenology retrieval but these timeseries are affected by clouds and aerosols,which add noise to the signalsensor. In this sense, several smoothing functions are used to removenoise introduced by undetected clouds and poor atmospheric conditions,but a comparison between methods is still necessary due todisagreements about its performance in the literature. The applicationof a smoothing function is a necessarily previous step to describe landsurface phenology in different ecosystems. The aims of this researchwere to evaluate the consistency of different smoothing functions fromTIMESAT software and their impacts on phenological attributes oftemperate grassland ? a complex mosaic of land uses with naturalvegetated and agricultural regions using NDVI-MODIS time series. Anadaptive Savitzky?Golay (SG) filter, Asymmetric Gaussian (AG) andDouble Logistic (DL) functions to fitting NDVI data were used andtheir performances were assessed using the measures root meansquare error (RMSE), Akaike Information Criterion (AIC), BayesianInformation Criterion (BIC) and bias. Besides, differences on the estimationof the start of the growing season (SOS) and the length of thegrowing season (LOS) were obtained. High and low RMSE over croplandsand grassland were observed for the three smoothing functions;in the rest of the region, the SG filter showed more reliable results.Patterns of difference on the estimation of SOS and LOS between SGfilter and the other two models were randomly distributed, wheredifferences of 20?50 days were found. This study demonstrated thatmethods from TIMESAT software are robust and spatially consistentbut must be carefully used.
Fil: Lara, Bruno Daniel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Agronomia. Departamento Ciencias Básicas Agronómicas y Biológicas. Laboratorio de Investigación y Servicios En Teledetección de Azul; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Gandini, Marcelo Luciano. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Agronomia. Departamento Ciencias Básicas Agronómicas y Biológicas. Laboratorio de Investigación y Servicios En Teledetección de Azul; Argentina
Materia
Ndvi Time Series
Land Surface Phenology
Savitzky-Golay Filter
Timesat
Temperate Grassland
Phenological Attributes
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/58727
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/58727
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Assessing the performance of smoothing functions to estimate land surface phenology on temperate grasslandLara, Bruno DanielGandini, Marcelo LucianoNdvi Time SeriesLand Surface PhenologySavitzky-Golay FilterTimesatTemperate GrasslandPhenological Attributeshttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1NDVI (Normalized Difference Vegetation Index) time-series have beenused for permitting a land surface phenology retrieval but these timeseries are affected by clouds and aerosols,which add noise to the signalsensor. In this sense, several smoothing functions are used to removenoise introduced by undetected clouds and poor atmospheric conditions,but a comparison between methods is still necessary due todisagreements about its performance in the literature. The applicationof a smoothing function is a necessarily previous step to describe landsurface phenology in different ecosystems. The aims of this researchwere to evaluate the consistency of different smoothing functions fromTIMESAT software and their impacts on phenological attributes oftemperate grassland ? a complex mosaic of land uses with naturalvegetated and agricultural regions using NDVI-MODIS time series. Anadaptive Savitzky?Golay (SG) filter, Asymmetric Gaussian (AG) andDouble Logistic (DL) functions to fitting NDVI data were used andtheir performances were assessed using the measures root meansquare error (RMSE), Akaike Information Criterion (AIC), BayesianInformation Criterion (BIC) and bias. Besides, differences on the estimationof the start of the growing season (SOS) and the length of thegrowing season (LOS) were obtained. High and low RMSE over croplandsand grassland were observed for the three smoothing functions;in the rest of the region, the SG filter showed more reliable results.Patterns of difference on the estimation of SOS and LOS between SGfilter and the other two models were randomly distributed, wheredifferences of 20?50 days were found. This study demonstrated thatmethods from TIMESAT software are robust and spatially consistentbut must be carefully used.Fil: Lara, Bruno Daniel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Agronomia. Departamento Ciencias Básicas Agronómicas y Biológicas. Laboratorio de Investigación y Servicios En Teledetección de Azul; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gandini, Marcelo Luciano. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Agronomia. Departamento Ciencias Básicas Agronómicas y Biológicas. Laboratorio de Investigación y Servicios En Teledetección de Azul; ArgentinaTaylor & Francis2016-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/58727Lara, Bruno Daniel; Gandini, Marcelo Luciano; Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland; Taylor & Francis; International Journal of Remote Sensing; 37; 8; 4-2016; 1801-18130143-11611366-5901CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1080/2150704X.2016.1168945info:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/abs/10.1080/2150704X.2016.1168945info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:35:09Zoai:ri.conicet.gov.ar:11336/58727instacron: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 09:35:10.176CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland
title Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland
spellingShingle Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland
Lara, Bruno Daniel
Ndvi Time Series
Land Surface Phenology
Savitzky-Golay Filter
Timesat
Temperate Grassland
Phenological Attributes
title_short Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland
title_full Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland
title_fullStr Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland
title_full_unstemmed Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland
title_sort Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland
dc.creator.none.fl_str_mv Lara, Bruno Daniel
Gandini, Marcelo Luciano
author Lara, Bruno Daniel
author_facet Lara, Bruno Daniel
Gandini, Marcelo Luciano
author_role author
author2 Gandini, Marcelo Luciano
author2_role author
dc.subject.none.fl_str_mv Ndvi Time Series
Land Surface Phenology
Savitzky-Golay Filter
Timesat
Temperate Grassland
Phenological Attributes
topic Ndvi Time Series
Land Surface Phenology
Savitzky-Golay Filter
Timesat
Temperate Grassland
Phenological Attributes
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv NDVI (Normalized Difference Vegetation Index) time-series have beenused for permitting a land surface phenology retrieval but these timeseries are affected by clouds and aerosols,which add noise to the signalsensor. In this sense, several smoothing functions are used to removenoise introduced by undetected clouds and poor atmospheric conditions,but a comparison between methods is still necessary due todisagreements about its performance in the literature. The applicationof a smoothing function is a necessarily previous step to describe landsurface phenology in different ecosystems. The aims of this researchwere to evaluate the consistency of different smoothing functions fromTIMESAT software and their impacts on phenological attributes oftemperate grassland ? a complex mosaic of land uses with naturalvegetated and agricultural regions using NDVI-MODIS time series. Anadaptive Savitzky?Golay (SG) filter, Asymmetric Gaussian (AG) andDouble Logistic (DL) functions to fitting NDVI data were used andtheir performances were assessed using the measures root meansquare error (RMSE), Akaike Information Criterion (AIC), BayesianInformation Criterion (BIC) and bias. Besides, differences on the estimationof the start of the growing season (SOS) and the length of thegrowing season (LOS) were obtained. High and low RMSE over croplandsand grassland were observed for the three smoothing functions;in the rest of the region, the SG filter showed more reliable results.Patterns of difference on the estimation of SOS and LOS between SGfilter and the other two models were randomly distributed, wheredifferences of 20?50 days were found. This study demonstrated thatmethods from TIMESAT software are robust and spatially consistentbut must be carefully used.
Fil: Lara, Bruno Daniel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Agronomia. Departamento Ciencias Básicas Agronómicas y Biológicas. Laboratorio de Investigación y Servicios En Teledetección de Azul; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Gandini, Marcelo Luciano. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Agronomia. Departamento Ciencias Básicas Agronómicas y Biológicas. Laboratorio de Investigación y Servicios En Teledetección de Azul; Argentina
description NDVI (Normalized Difference Vegetation Index) time-series have beenused for permitting a land surface phenology retrieval but these timeseries are affected by clouds and aerosols,which add noise to the signalsensor. In this sense, several smoothing functions are used to removenoise introduced by undetected clouds and poor atmospheric conditions,but a comparison between methods is still necessary due todisagreements about its performance in the literature. The applicationof a smoothing function is a necessarily previous step to describe landsurface phenology in different ecosystems. The aims of this researchwere to evaluate the consistency of different smoothing functions fromTIMESAT software and their impacts on phenological attributes oftemperate grassland ? a complex mosaic of land uses with naturalvegetated and agricultural regions using NDVI-MODIS time series. Anadaptive Savitzky?Golay (SG) filter, Asymmetric Gaussian (AG) andDouble Logistic (DL) functions to fitting NDVI data were used andtheir performances were assessed using the measures root meansquare error (RMSE), Akaike Information Criterion (AIC), BayesianInformation Criterion (BIC) and bias. Besides, differences on the estimationof the start of the growing season (SOS) and the length of thegrowing season (LOS) were obtained. High and low RMSE over croplandsand grassland were observed for the three smoothing functions;in the rest of the region, the SG filter showed more reliable results.Patterns of difference on the estimation of SOS and LOS between SGfilter and the other two models were randomly distributed, wheredifferences of 20?50 days were found. This study demonstrated thatmethods from TIMESAT software are robust and spatially consistentbut must be carefully used.
publishDate 2016
dc.date.none.fl_str_mv 2016-04
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/11336/58727
Lara, Bruno Daniel; Gandini, Marcelo Luciano; Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland; Taylor & Francis; International Journal of Remote Sensing; 37; 8; 4-2016; 1801-1813
0143-1161
1366-5901
CONICET Digital
CONICET
url http://hdl.handle.net/11336/58727
identifier_str_mv Lara, Bruno Daniel; Gandini, Marcelo Luciano; Assessing the performance of smoothing functions to estimate land surface phenology on temperate grassland; Taylor & Francis; International Journal of Remote Sensing; 37; 8; 4-2016; 1801-1813
0143-1161
1366-5901
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1080/2150704X.2016.1168945
info:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/abs/10.1080/2150704X.2016.1168945
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
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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score 13.070432

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