Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series

Autores
Amherdt, Sebastián; Di Leo, Néstor Cristian; Pereira, Ayelen; Cornero, Cecilia; Pacino, Maria Cristina
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This work aims to evaluate the added value of interferometric coherence to backscatter information of Synthetic Aperture Radar (SAR) systems for soybean and corn mapping. First, SAR response to crop growth, and then accuracies for the classification using a combination of SAR variables were evaluated for scenarios that employ in-season or the entire season time series. Results showed that: i) using a single feature, the backscatter at vertical-horizontal (VH) polarization would be the most suitable variable; ii) the complementarity of coherence to single backscatter at vertical-vertical (VV) polarization was demonstrated, adding a significant contribution to late sown corns differentiation and iii) the combination of VV and VH backscatter would be the preferable variables for the proposed classification. In this case, the adding of coherence did not show a significant accuracy improvement, while a high computational cost is required. Finally, high general accuracies (until 90%) for early-season maps were achieved.
Fil: Amherdt, Sebastián. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina
Fil: Di Leo, Néstor Cristian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario; Argentina
Fil: Pereira, Ayelen. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina
Fil: Cornero, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina
Fil: Pacino, Maria Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina
Materia
CROP MAPPING
INSAR COHERENCE
SAR TIME SERIES
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:11336/216964
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time seriesAmherdt, SebastiánDi Leo, Néstor CristianPereira, AyelenCornero, CeciliaPacino, Maria CristinaCROP MAPPINGINSAR COHERENCESAR TIME SERIEShttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1This work aims to evaluate the added value of interferometric coherence to backscatter information of Synthetic Aperture Radar (SAR) systems for soybean and corn mapping. First, SAR response to crop growth, and then accuracies for the classification using a combination of SAR variables were evaluated for scenarios that employ in-season or the entire season time series. Results showed that: i) using a single feature, the backscatter at vertical-horizontal (VH) polarization would be the most suitable variable; ii) the complementarity of coherence to single backscatter at vertical-vertical (VV) polarization was demonstrated, adding a significant contribution to late sown corns differentiation and iii) the combination of VV and VH backscatter would be the preferable variables for the proposed classification. In this case, the adding of coherence did not show a significant accuracy improvement, while a high computational cost is required. Finally, high general accuracies (until 90%) for early-season maps were achieved.Fil: Amherdt, Sebastián. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; ArgentinaFil: Di Leo, Néstor Cristian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario; ArgentinaFil: Pereira, Ayelen. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; ArgentinaFil: Cornero, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; ArgentinaFil: Pacino, Maria Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; ArgentinaTaylor & Francis2022-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/216964Amherdt, Sebastián; Di Leo, Néstor Cristian; Pereira, Ayelen; Cornero, Cecilia; Pacino, Maria Cristina; Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series; Taylor & Francis; Geocarto International; 11-2022; 1-231010-6049CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1080/10106049.2022.2144472info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:49:55Zoai:ri.conicet.gov.ar:11336/216964instacron: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 09:49:55.737CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series
title Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series
spellingShingle Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series
Amherdt, Sebastián
CROP MAPPING
INSAR COHERENCE
SAR TIME SERIES
title_short Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series
title_full Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series
title_fullStr Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series
title_full_unstemmed Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series
title_sort Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series
dc.creator.none.fl_str_mv Amherdt, Sebastián
Di Leo, Néstor Cristian
Pereira, Ayelen
Cornero, Cecilia
Pacino, Maria Cristina
author Amherdt, Sebastián
author_facet Amherdt, Sebastián
Di Leo, Néstor Cristian
Pereira, Ayelen
Cornero, Cecilia
Pacino, Maria Cristina
author_role author
author2 Di Leo, Néstor Cristian
Pereira, Ayelen
Cornero, Cecilia
Pacino, Maria Cristina
author2_role author
author
author
author
dc.subject.none.fl_str_mv CROP MAPPING
INSAR COHERENCE
SAR TIME SERIES
topic CROP MAPPING
INSAR COHERENCE
SAR TIME SERIES
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv This work aims to evaluate the added value of interferometric coherence to backscatter information of Synthetic Aperture Radar (SAR) systems for soybean and corn mapping. First, SAR response to crop growth, and then accuracies for the classification using a combination of SAR variables were evaluated for scenarios that employ in-season or the entire season time series. Results showed that: i) using a single feature, the backscatter at vertical-horizontal (VH) polarization would be the most suitable variable; ii) the complementarity of coherence to single backscatter at vertical-vertical (VV) polarization was demonstrated, adding a significant contribution to late sown corns differentiation and iii) the combination of VV and VH backscatter would be the preferable variables for the proposed classification. In this case, the adding of coherence did not show a significant accuracy improvement, while a high computational cost is required. Finally, high general accuracies (until 90%) for early-season maps were achieved.
Fil: Amherdt, Sebastián. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina
Fil: Di Leo, Néstor Cristian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario; Argentina
Fil: Pereira, Ayelen. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina
Fil: Cornero, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina
Fil: Pacino, Maria Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina
description This work aims to evaluate the added value of interferometric coherence to backscatter information of Synthetic Aperture Radar (SAR) systems for soybean and corn mapping. First, SAR response to crop growth, and then accuracies for the classification using a combination of SAR variables were evaluated for scenarios that employ in-season or the entire season time series. Results showed that: i) using a single feature, the backscatter at vertical-horizontal (VH) polarization would be the most suitable variable; ii) the complementarity of coherence to single backscatter at vertical-vertical (VV) polarization was demonstrated, adding a significant contribution to late sown corns differentiation and iii) the combination of VV and VH backscatter would be the preferable variables for the proposed classification. In this case, the adding of coherence did not show a significant accuracy improvement, while a high computational cost is required. Finally, high general accuracies (until 90%) for early-season maps were achieved.
publishDate 2022
dc.date.none.fl_str_mv 2022-11
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/11336/216964
Amherdt, Sebastián; Di Leo, Néstor Cristian; Pereira, Ayelen; Cornero, Cecilia; Pacino, Maria Cristina; Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series; Taylor & Francis; Geocarto International; 11-2022; 1-23
1010-6049
CONICET Digital
CONICET
url http://hdl.handle.net/11336/216964
identifier_str_mv Amherdt, Sebastián; Di Leo, Néstor Cristian; Pereira, Ayelen; Cornero, Cecilia; Pacino, Maria Cristina; Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series; Taylor & Francis; Geocarto International; 11-2022; 1-23
1010-6049
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1080/10106049.2022.2144472
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
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
_version_ 1844613542034014208
score 13.070432

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