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
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/14769
Ver los metadatos del registro completo
id |
INTADig_722d6709fb35a860671c274a7a8db41e |
---|---|
oai_identifier_str |
oai:localhost:20.500.12123/14769 |
network_acronym_str |
INTADig |
repository_id_str |
l |
network_name_str |
INTA Digital (INTA) |
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 |
_version_ |
1846143560441659392 |
score |
12.712165 |