First Large Extent and High Resolution Cropland and Crop Type Map of Argentina

Autores
De Abelleyra, Diego; Veron, Santiago Ramón; Banchero, Santiago; Mosciaro, Maria Jesus; Propato, Tamara Sofia; Ferraina, Antonella; Gómez Taffarel, Maria Cielo; Dacunto, Luciana; Franzoni, Agustin; Volante, Jose Norberto
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Trabajo presentado al 2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS 2020), 22–26 March 2020, Santiago, Chile.
The availability of spatially explicit information about agricultural crops for large regions in Argentina is scarce. In particular, due to temporal dynamics of agricultural production (i.e. changes in planted crops from year to year) and spectral similarities among herbaceous crops it is difficult to generate crop type maps from remote sensing. Large regions with marked climatic variations, like the main agricultural areas of Argentina, represent an additional challenge. Here we generated a map based on supervised classifications using field samples along 14 agricultural zones. Best classification accuracies were obtained by combining seasonal indices (year, summer and winter), with indices that describe the temporal dynamics of vegetation. Accuracy was increased at regions with high and balanced number of samples and with longer growing seasons. The map allows to identify areas with clusters of one, two or three crops and to characterize areas with different spatial distribution between cropland and no cropland areas.
EEA Salta.
Fil: De Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Veron, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos; Argentina.
Fil: Banchero, Santiago. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Mosciaro, Maria Jesus. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina
Fil: Propato, Tamara. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Ferraina, Antonela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Gomez Taffarel, Maria Cielo. Actividad privada; Argentina.
Fil: Dacunto, Luciana. Actividad privada; Argentina.
Fil: Franzoni, Agustin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina
Fil: Volante, Jose Norberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina
Fuente
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W12-2020 (2020)
Materia
Cultivos
Tierras Agrícolas
Argentina
Crops
Farmland
Remote Sensing
Teledetección
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/14533
Acceder
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oai_identifier_str oai:localhost:20.500.12123/14533
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling First Large Extent and High Resolution Cropland and Crop Type Map of ArgentinaDe Abelleyra, DiegoVeron, Santiago RamónBanchero, SantiagoMosciaro, Maria JesusPropato, Tamara SofiaFerraina, AntonellaGómez Taffarel, Maria CieloDacunto, LucianaFranzoni, AgustinVolante, Jose NorbertoCultivosTierras AgrícolasArgentinaCropsFarmlandRemote SensingTeledetecciónTrabajo presentado al 2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS 2020), 22–26 March 2020, Santiago, Chile.The availability of spatially explicit information about agricultural crops for large regions in Argentina is scarce. In particular, due to temporal dynamics of agricultural production (i.e. changes in planted crops from year to year) and spectral similarities among herbaceous crops it is difficult to generate crop type maps from remote sensing. Large regions with marked climatic variations, like the main agricultural areas of Argentina, represent an additional challenge. Here we generated a map based on supervised classifications using field samples along 14 agricultural zones. Best classification accuracies were obtained by combining seasonal indices (year, summer and winter), with indices that describe the temporal dynamics of vegetation. Accuracy was increased at regions with high and balanced number of samples and with longer growing seasons. The map allows to identify areas with clusters of one, two or three crops and to characterize areas with different spatial distribution between cropland and no cropland areas.EEA Salta.Fil: De Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Veron, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos; Argentina.Fil: Banchero, Santiago. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Mosciaro, Maria Jesus. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaFil: Propato, Tamara. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Ferraina, Antonela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Gomez Taffarel, Maria Cielo. Actividad privada; Argentina.Fil: Dacunto, Luciana. Actividad privada; Argentina.Fil: Franzoni, Agustin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaFil: Volante, Jose Norberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaInternational Society of Photogrammetry and Remote Sensing2023-04-20T12:19:08Z2023-04-20T12:19:08Z2020-03-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/14533https://isprs-archives.copernicus.org/articles/XLII-3-W12-2020/165/2020/https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-165-2020The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W12-2020 (2020)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-10-16T09:31:10Zoai:localhost:20.500.12123/14533instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-16 09:31:10.61INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv First Large Extent and High Resolution Cropland and Crop Type Map of Argentina
title First Large Extent and High Resolution Cropland and Crop Type Map of Argentina
spellingShingle First Large Extent and High Resolution Cropland and Crop Type Map of Argentina
De Abelleyra, Diego
Cultivos
Tierras Agrícolas
Argentina
Crops
Farmland
Remote Sensing
Teledetección
title_short First Large Extent and High Resolution Cropland and Crop Type Map of Argentina
title_full First Large Extent and High Resolution Cropland and Crop Type Map of Argentina
title_fullStr First Large Extent and High Resolution Cropland and Crop Type Map of Argentina
title_full_unstemmed First Large Extent and High Resolution Cropland and Crop Type Map of Argentina
title_sort First Large Extent and High Resolution Cropland and Crop Type Map of Argentina
dc.creator.none.fl_str_mv De Abelleyra, Diego
Veron, Santiago Ramón
Banchero, Santiago
Mosciaro, Maria Jesus
Propato, Tamara Sofia
Ferraina, Antonella
Gómez Taffarel, Maria Cielo
Dacunto, Luciana
Franzoni, Agustin
Volante, Jose Norberto
author De Abelleyra, Diego
author_facet De Abelleyra, Diego
Veron, Santiago Ramón
Banchero, Santiago
Mosciaro, Maria Jesus
Propato, Tamara Sofia
Ferraina, Antonella
Gómez Taffarel, Maria Cielo
Dacunto, Luciana
Franzoni, Agustin
Volante, Jose Norberto
author_role author
author2 Veron, Santiago Ramón
Banchero, Santiago
Mosciaro, Maria Jesus
Propato, Tamara Sofia
Ferraina, Antonella
Gómez Taffarel, Maria Cielo
Dacunto, Luciana
Franzoni, Agustin
Volante, Jose Norberto
author2_role author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Cultivos
Tierras Agrícolas
Argentina
Crops
Farmland
Remote Sensing
Teledetección
topic Cultivos
Tierras Agrícolas
Argentina
Crops
Farmland
Remote Sensing
Teledetección
dc.description.none.fl_txt_mv Trabajo presentado al 2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS 2020), 22–26 March 2020, Santiago, Chile.
The availability of spatially explicit information about agricultural crops for large regions in Argentina is scarce. In particular, due to temporal dynamics of agricultural production (i.e. changes in planted crops from year to year) and spectral similarities among herbaceous crops it is difficult to generate crop type maps from remote sensing. Large regions with marked climatic variations, like the main agricultural areas of Argentina, represent an additional challenge. Here we generated a map based on supervised classifications using field samples along 14 agricultural zones. Best classification accuracies were obtained by combining seasonal indices (year, summer and winter), with indices that describe the temporal dynamics of vegetation. Accuracy was increased at regions with high and balanced number of samples and with longer growing seasons. The map allows to identify areas with clusters of one, two or three crops and to characterize areas with different spatial distribution between cropland and no cropland areas.
EEA Salta.
Fil: De Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Veron, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos; Argentina.
Fil: Banchero, Santiago. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Mosciaro, Maria Jesus. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina
Fil: Propato, Tamara. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Ferraina, Antonela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Gomez Taffarel, Maria Cielo. Actividad privada; Argentina.
Fil: Dacunto, Luciana. Actividad privada; Argentina.
Fil: Franzoni, Agustin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina
Fil: Volante, Jose Norberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina
description Trabajo presentado al 2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS 2020), 22–26 March 2020, Santiago, Chile.
publishDate 2020
dc.date.none.fl_str_mv 2020-03-22
2023-04-20T12:19:08Z
2023-04-20T12:19:08Z
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/20.500.12123/14533
https://isprs-archives.copernicus.org/articles/XLII-3-W12-2020/165/2020/
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-165-2020
url http://hdl.handle.net/20.500.12123/14533
https://isprs-archives.copernicus.org/articles/XLII-3-W12-2020/165/2020/
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-165-2020
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv International Society of Photogrammetry and Remote Sensing
publisher.none.fl_str_mv International Society of Photogrammetry and Remote Sensing
dc.source.none.fl_str_mv The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W12-2020 (2020)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
_version_ 1846143559114162176
score 12.712165

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