Characterization of multispectral aerial images of sugarcane

Autores
Solano, Agustín; Schneider, Gerardo; Kemerer, Alejandra Cecilia; Hadad, Alejandro Javier
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Trabajo presentado al 19th Argentinean Bioengineering Society Congress (SABI 2013), 4–6 September 2013, Tucumán, Argentina
In this paper we present a implementation and characterization the status of sugarcane plantations based on the analysis of multispectral aerial images. Currently there are no precise techniques to estimate objectively the cane area fall or overturned, and this causes significant losses in crop productivity and industrialization. For the realization of this work was made a dataset benchmark images, and implemented a software from which were obtained indicators related to agronomic phenomenon, and analyzes of the data generated. In addition was used Principal Component Analysis to visualize and integrate statistical texture features. The results indicate the statistical features used characterize partially the sugar cane phenomena and suggest include another texture focus to complement this feature set, previous to built an cane identification process.
EEA Paraná
Fil: Solano, A. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina
Fil: Schneider, Gerardo. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina
Fil: Kemerer, Alejandra Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná. Grupo Recursos Naturales y Factores Abióticos; Argentina
Fil: Kemerer, Alejandra Cecilia. IUniversidad Nacional de Entre Ríos. Facultad de Ciencias Agrarias; Argentina
Fil: Hadad, Alejandro Javier. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina
Fuente
Journal of Physics: Conference Series 477 : 012016 (2013)
Materia
Caña de Azúcar
Imágenes Multiespectrales
Productividad
Sugar Cane
Multispectral Imagery
Productivity
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:20.500.12123/14769
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spelling Characterization of multispectral aerial images of sugarcaneSolano, AgustínSchneider, GerardoKemerer, Alejandra CeciliaHadad, Alejandro JavierCaña de AzúcarImágenes MultiespectralesProductividadSugar CaneMultispectral ImageryProductivityTrabajo presentado al 19th Argentinean Bioengineering Society Congress (SABI 2013), 4–6 September 2013, Tucumán, ArgentinaIn this paper we present a implementation and characterization the status of sugarcane plantations based on the analysis of multispectral aerial images. Currently there are no precise techniques to estimate objectively the cane area fall or overturned, and this causes significant losses in crop productivity and industrialization. For the realization of this work was made a dataset benchmark images, and implemented a software from which were obtained indicators related to agronomic phenomenon, and analyzes of the data generated. In addition was used Principal Component Analysis to visualize and integrate statistical texture features. The results indicate the statistical features used characterize partially the sugar cane phenomena and suggest include another texture focus to complement this feature set, previous to built an cane identification process.EEA ParanáFil: Solano, A. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; ArgentinaFil: Schneider, Gerardo. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; ArgentinaFil: Kemerer, Alejandra Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná. Grupo Recursos Naturales y Factores Abióticos; ArgentinaFil: Kemerer, Alejandra Cecilia. IUniversidad Nacional de Entre Ríos. Facultad de Ciencias Agrarias; ArgentinaFil: Hadad, Alejandro Javier. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; ArgentinaIOP Science2023-07-18T17:25:49Z2023-07-18T17:25:49Z2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/14769https://iopscience.iop.org/article/10.1088/1742-6596/477/1/0120161742-6596https://doi.org/10.1088/1742-6596/477/1/012016Journal of Physics: Conference Series 477 : 012016 (2013)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)2025-10-16T09:31:12Zoai:localhost:20.500.12123/14769instacron: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 09:31:12.563INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Characterization of multispectral aerial images of sugarcane
title Characterization of multispectral aerial images of sugarcane
spellingShingle Characterization of multispectral aerial images of sugarcane
Solano, Agustín
Caña de Azúcar
Imágenes Multiespectrales
Productividad
Sugar Cane
Multispectral Imagery
Productivity
title_short Characterization of multispectral aerial images of sugarcane
title_full Characterization of multispectral aerial images of sugarcane
title_fullStr Characterization of multispectral aerial images of sugarcane
title_full_unstemmed Characterization of multispectral aerial images of sugarcane
title_sort Characterization of multispectral aerial images of sugarcane
dc.creator.none.fl_str_mv Solano, Agustín
Schneider, Gerardo
Kemerer, Alejandra Cecilia
Hadad, Alejandro Javier
author Solano, Agustín
author_facet Solano, Agustín
Schneider, Gerardo
Kemerer, Alejandra Cecilia
Hadad, Alejandro Javier
author_role author
author2 Schneider, Gerardo
Kemerer, Alejandra Cecilia
Hadad, Alejandro Javier
author2_role author
author
author
dc.subject.none.fl_str_mv Caña de Azúcar
Imágenes Multiespectrales
Productividad
Sugar Cane
Multispectral Imagery
Productivity
topic Caña de Azúcar
Imágenes Multiespectrales
Productividad
Sugar Cane
Multispectral Imagery
Productivity
dc.description.none.fl_txt_mv Trabajo presentado al 19th Argentinean Bioengineering Society Congress (SABI 2013), 4–6 September 2013, Tucumán, Argentina
In this paper we present a implementation and characterization the status of sugarcane plantations based on the analysis of multispectral aerial images. Currently there are no precise techniques to estimate objectively the cane area fall or overturned, and this causes significant losses in crop productivity and industrialization. For the realization of this work was made a dataset benchmark images, and implemented a software from which were obtained indicators related to agronomic phenomenon, and analyzes of the data generated. In addition was used Principal Component Analysis to visualize and integrate statistical texture features. The results indicate the statistical features used characterize partially the sugar cane phenomena and suggest include another texture focus to complement this feature set, previous to built an cane identification process.
EEA Paraná
Fil: Solano, A. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina
Fil: Schneider, Gerardo. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina
Fil: Kemerer, Alejandra Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná. Grupo Recursos Naturales y Factores Abióticos; Argentina
Fil: Kemerer, Alejandra Cecilia. IUniversidad Nacional de Entre Ríos. Facultad de Ciencias Agrarias; Argentina
Fil: Hadad, Alejandro Javier. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina
description Trabajo presentado al 19th Argentinean Bioengineering Society Congress (SABI 2013), 4–6 September 2013, Tucumán, Argentina
publishDate 2013
dc.date.none.fl_str_mv 2013
2023-07-18T17:25:49Z
2023-07-18T17:25:49Z
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/20.500.12123/14769
https://iopscience.iop.org/article/10.1088/1742-6596/477/1/012016
1742-6596
https://doi.org/10.1088/1742-6596/477/1/012016
url http://hdl.handle.net/20.500.12123/14769
https://iopscience.iop.org/article/10.1088/1742-6596/477/1/012016
https://doi.org/10.1088/1742-6596/477/1/012016
identifier_str_mv 1742-6596
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 IOP Science
publisher.none.fl_str_mv IOP Science
dc.source.none.fl_str_mv Journal of Physics: Conference Series 477 : 012016 (2013)
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
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score 12.712165

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