Identificación del estado fenológico del cultivo del arroz a partir de imágenes de radar Sentinel-1

ilustraciones, fotografías a color, mapas

Autores:
Martínez Alayón, Fredy Alberto
Tipo de recurso:
Fecha de publicación:
2023
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
OAI Identifier:
oai:repositorio.unal.edu.co:unal/84138
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/84138
https://repositorio.unal.edu.co/
Palabra clave:
Recursos naturales
Fenología
Natural resources
Phenology
Radar de apertura sintética (SAR)
Imágenes Sentinel-1
Fenología del arroz
Datos polarimétricos
Exactitud de clasificación
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
id UNACIONAL2_f972226771892d1e18d5a48eeb411f53
oai_identifier_str oai:repositorio.unal.edu.co:unal/84138
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv Identificación del estado fenológico del cultivo del arroz a partir de imágenes de radar Sentinel-1
dc.title.translated.eng.fl_str_mv Identification of the phenological state of rice cultivation from Sentinel-1 radar images
title Identificación del estado fenológico del cultivo del arroz a partir de imágenes de radar Sentinel-1
spellingShingle Identificación del estado fenológico del cultivo del arroz a partir de imágenes de radar Sentinel-1
Recursos naturales
Fenología
Natural resources
Phenology
Radar de apertura sintética (SAR)
Imágenes Sentinel-1
Fenología del arroz
Datos polarimétricos
Exactitud de clasificación
title_short Identificación del estado fenológico del cultivo del arroz a partir de imágenes de radar Sentinel-1
title_full Identificación del estado fenológico del cultivo del arroz a partir de imágenes de radar Sentinel-1
title_fullStr Identificación del estado fenológico del cultivo del arroz a partir de imágenes de radar Sentinel-1
title_full_unstemmed Identificación del estado fenológico del cultivo del arroz a partir de imágenes de radar Sentinel-1
title_sort Identificación del estado fenológico del cultivo del arroz a partir de imágenes de radar Sentinel-1
dc.creator.fl_str_mv Martínez Alayón, Fredy Alberto
dc.contributor.advisor.none.fl_str_mv Lizarazo Salcedo, Iván Alberto
dc.contributor.author.none.fl_str_mv Martínez Alayón, Fredy Alberto
dc.subject.lemb.spa.fl_str_mv Recursos naturales
Fenología
topic Recursos naturales
Fenología
Natural resources
Phenology
Radar de apertura sintética (SAR)
Imágenes Sentinel-1
Fenología del arroz
Datos polarimétricos
Exactitud de clasificación
dc.subject.lemb.eng.fl_str_mv Natural resources
Phenology
dc.subject.proposal.spa.fl_str_mv Radar de apertura sintética (SAR)
Imágenes Sentinel-1
Fenología del arroz
Datos polarimétricos
Exactitud de clasificación
description ilustraciones, fotografías a color, mapas
publishDate 2023
dc.date.accessioned.none.fl_str_mv 2023-07-04T21:37:33Z
dc.date.available.none.fl_str_mv 2023-07-04T21:37:33Z
dc.date.issued.none.fl_str_mv 2023-01-30
dc.type.spa.fl_str_mv Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/TM
status_str acceptedVersion
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/84138
dc.identifier.instname.spa.fl_str_mv Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv https://repositorio.unal.edu.co/
url https://repositorio.unal.edu.co/handle/unal/84138
https://repositorio.unal.edu.co/
identifier_str_mv Universidad Nacional de Colombia
Repositorio Institucional Universidad Nacional de Colombia
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spelling Atribución-NoComercial 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Lizarazo Salcedo, Iván Albertob7a911d83f30c19f50a8d2f7b4e94e02Martínez Alayón, Fredy Albertoc022367f9aad079e92efe5e3fc93a06b2023-07-04T21:37:33Z2023-07-04T21:37:33Z2023-01-30https://repositorio.unal.edu.co/handle/unal/84138Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, fotografías a color, mapasLa disponibilidad de información oportuna y exacta sobre la fenología del arroz es esencial para diversas actividades de manejo de un cultivo que es esencial para la seguridad agroalimentaria. Aunque la recopilación directa de datos en el campo proporciona información confiable, esa tarea requiere mucho tiempo y trabajo. Como alternativa tecnológica, la teledetección óptica satelital recopila datos de reflectancia cada 5 días. Sin embargo, en ambientes tropicales, la cobertura de nubes obstruye la vista desde arriba. Debido a su capacidad de ver a través de las nubes, las imágenes obtenidas mediante sensores de radar de apertura sintética (SAR) tienen potencial para el monitoreo de las etapas fenológicas del arroz. Este estudio implementa un flujo de trabajo técnico para procesar y analizar datos SAR polarimétricos para el mapeo de la fenología del arroz. Un conjunto multitemporal de imágenes Sentinel-1 de banda C adquiridas en dos zonas de arroz en Colombia se utilizaron para validar el flujo de trabajo. En este estudio, se realizó la clasificación fenológica utilizando índices polarimétricos e interferométricos como variables explicativas. Se obtuvo una buena exactitud de clasificación general para las etapas de fenología del cultivo utilizando polarizaciones VH y VV, junto con el índice DpRVI y una exactitud deficiente para los resultados con la variable coherencia. Esta diferencia en la calidad de los resultados podría deberse a que tanto las polarizaciones como el índice logran describir el crecimiento del cultivo de manera satisfactoria mientras que la coherencia está enfocada en la detección de cambios que no se pudieron caracterizar en coberturas vegetales. Se demuestra la utilidad de las imágenes Sentinel-1 para el monitoreo de la fenología del arroz, así como los desafíos técnicos que deben resolverse para tener éxito con estas imágenes. (Texto tomado de la fuente)Accurate and timely information on rice phenology is crucial for ensuring agrifood security and effective crop management. While direct data collection in the field is reliable, it can be labor-intensive and time-consuming. In tropical environments, cloud cover often obstructs satellite optical remote sensing, which collects reflectance data every 5 days. However, synthetic aperture radar (SAR) sensors have the potential to monitor rice phenology, as they can see through clouds. This study implements a technical workflow to process and analyze polarimetric SAR data for mapping rice phenology. A multi-temporal set of C-band Sentinel-1 images acquired in two rice areas in Colombia were used to validate the workflow. Phenological classification was performed using polarimetric and interferometric indices as explanatory variables. The results show that VH and VV polarizations, together with the DpRVI index, produced good overall classification accuracy for crop phenology stages, while coherence variable had poor accuracy. This difference in the quality of the results could be due to the fact that both polarizations and the index satisfactorily describe crop growth, while coherence is focused on detecting changes that cannot be characterized in vegetation coverages.The usefulness of Sentinel-1 imagery for monitoring rice phenology is demonstrated, along with the technical challenges that need to be resolved for successful use of these images.MaestríaGeoinformación para el uso sostenible de los recursos naturalesxix, 157 páginasapplication/pdfIdentificación del estado fenológico del cultivo del arroz a partir de imágenes de radar Sentinel-1Identification of the phenological state of rice cultivation from Sentinel-1 radar imagesTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMBogotá - Ciencias Agrarias - Maestría en GeomáticaFacultad de Ciencias AgrariasBogotá,ColombiaUniversidad Nacional de Colombia - Sede BogotáAnderson, F., Ixmuca, A., Herndon, K. 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IEEE Geoscience and Remote Sensing Magazine, 5(4):8–36.Recursos naturalesFenologíaNatural resourcesPhenologyRadar de apertura sintética (SAR)Imágenes Sentinel-1Fenología del arrozDatos polarimétricosExactitud de clasificaciónLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/84138/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL11232581.2023.pdf11232581.2023.pdfTesis de Maestría en Geomáticaapplication/pdf26028868https://repositorio.unal.edu.co/bitstream/unal/84138/2/11232581.2023.pdf4e4e46251cb53e25c6de0f15258be35dMD52THUMBNAIL11232581.2023.pdf.jpg11232581.2023.pdf.jpgGenerated Thumbnailimage/jpeg4933https://repositorio.unal.edu.co/bitstream/unal/84138/3/11232581.2023.pdf.jpge0cc5aa1f81d6788f48c1ec36619c636MD53unal/84138oai:repositorio.unal.edu.co:unal/841382023-08-09 23:04:40.429Repositorio Institucional Universidad Nacional de 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