Herramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. Hass

ilustraciones, diagramas, fotografías, mapas, tablas

Autores:: Sánchez Vivas, Diego Fernando

Tipo de recurso:

Fecha de publicación:: 2024

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

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oai_identifier_str	oai:repositorio.unal.edu.co:unal/86890
network_acronym_str	UNACIONAL2
network_name_str	Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv	Herramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. Hass
dc.title.translated.eng.fl_str_mv	Space-time analysis tools for climatic and spectral data as a basis for the characterization and climatic modeling and indirect estimation of productive parameters in Hass avocado
title	Herramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. Hass
spellingShingle	Herramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. Hass 630 - Agricultura y tecnologías relacionadas::631 - Técnicas específicas, aparatos, equipos, materiales 630 - Agricultura y tecnologías relacionadas::634 - Huertos, frutas, silvicultura AGUACATE-CONSERVACION CLIMATOLOGIA AGRICOLA METEOROLOGIA AGRICOLA RECOPILACION DE DATOS CAMBIOS CLIMATICOS VARIABILIDAD DE PRECIPITACION ZONAS CLIMATICAS Avocado - preservation Crops and climate Meteorology, agricultural Data collecting Climatic changes Precipitation variability Climatic zones Variabilidad y cambio climático Series de tiempo Redes neuronales profundas Índices de vegetación Teledetección Climate variability and change Time series Deep neural networks Vegetation indices Remote sensing
title_short	Herramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. Hass
title_full	Herramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. Hass
title_fullStr	Herramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. Hass
title_full_unstemmed	Herramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. Hass
title_sort	Herramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. Hass
dc.creator.fl_str_mv	Sánchez Vivas, Diego Fernando
dc.contributor.advisor.spa.fl_str_mv	Ramírez Gil, Joaquín Guillermo Terán Chaves, Cesar Augusto
dc.contributor.author.spa.fl_str_mv	Sánchez Vivas, Diego Fernando
dc.contributor.researchgroup.spa.fl_str_mv	Biogénesis
dc.contributor.orcid.spa.fl_str_mv	Sánchez Vivas, Diego Fernando [0000000163130871]
dc.contributor.cvlac.spa.fl_str_mv	Sánchez Vivas, Diego Fernando [0000092231]
dc.contributor.scopus.spa.fl_str_mv	Sánchez Vivas, Diego Fernando [58159513500]
dc.contributor.researchgate.spa.fl_str_mv	Sánchez Vivas, Diego Fernando [https://www.researchgate.net/profile/Diego-Sanchez-Vivas]
dc.contributor.googlescholar.spa.fl_str_mv	Sánchez Vivas, Diego Fernando [https://scholar.google.se/citations?user=7KTTn5UAAAAJ]
dc.subject.ddc.spa.fl_str_mv	630 - Agricultura y tecnologías relacionadas::631 - Técnicas específicas, aparatos, equipos, materiales 630 - Agricultura y tecnologías relacionadas::634 - Huertos, frutas, silvicultura
topic	630 - Agricultura y tecnologías relacionadas::631 - Técnicas específicas, aparatos, equipos, materiales 630 - Agricultura y tecnologías relacionadas::634 - Huertos, frutas, silvicultura AGUACATE-CONSERVACION CLIMATOLOGIA AGRICOLA METEOROLOGIA AGRICOLA RECOPILACION DE DATOS CAMBIOS CLIMATICOS VARIABILIDAD DE PRECIPITACION ZONAS CLIMATICAS Avocado - preservation Crops and climate Meteorology, agricultural Data collecting Climatic changes Precipitation variability Climatic zones Variabilidad y cambio climático Series de tiempo Redes neuronales profundas Índices de vegetación Teledetección Climate variability and change Time series Deep neural networks Vegetation indices Remote sensing
dc.subject.lemb.spa.fl_str_mv	AGUACATE-CONSERVACION CLIMATOLOGIA AGRICOLA METEOROLOGIA AGRICOLA RECOPILACION DE DATOS CAMBIOS CLIMATICOS VARIABILIDAD DE PRECIPITACION ZONAS CLIMATICAS
dc.subject.lemb.eng.fl_str_mv	Avocado - preservation Crops and climate Meteorology, agricultural Data collecting Climatic changes Precipitation variability Climatic zones
dc.subject.proposal.spa.fl_str_mv	Variabilidad y cambio climático Series de tiempo Redes neuronales profundas Índices de vegetación Teledetección
dc.subject.proposal.eng.fl_str_mv	Climate variability and change Time series Deep neural networks Vegetation indices Remote sensing
description	ilustraciones, diagramas, fotografías, mapas, tablas
publishDate	2024
dc.date.accessioned.none.fl_str_mv	2024-10-03T17:41:03Z
dc.date.available.none.fl_str_mv	2024-10-03T17:41:03Z
dc.date.issued.none.fl_str_mv	2024
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/86890
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/86890 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	spa
language	spa
dc.relation.indexed.spa.fl_str_mv	Agrosavia Agrovoc
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dc.coverage.country.spa.fl_str_mv	Colombia
dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
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dc.publisher.faculty.spa.fl_str_mv	Facultad de Ciencias Agrarias
dc.publisher.place.spa.fl_str_mv	Bogotá, Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Bogotá
institution	Universidad Nacional de Colombia
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spelling	Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Ramírez Gil, Joaquín Guillermo057a48c561d6f5700e30039433833652Terán Chaves, Cesar Augusto35ae929efd039578284d7f55f12eef9dSánchez Vivas, Diego Fernandof60620d7f6dd4551832b0069498febfeBiogénesisSánchez Vivas, Diego Fernando [0000000163130871]Sánchez Vivas, Diego Fernando [0000092231]Sánchez Vivas, Diego Fernando [58159513500]Sánchez Vivas, Diego Fernando [https://www.researchgate.net/profile/Diego-Sanchez-Vivas]Sánchez Vivas, Diego Fernando [https://scholar.google.se/citations?user=7KTTn5UAAAAJ]2024-10-03T17:41:03Z2024-10-03T17:41:03Z2024https://repositorio.unal.edu.co/handle/unal/86890Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramas, fotografías, mapas, tablasEl aguacate cv. Hass ha experimentado un crecimiento en la demanda a nivel mundial, lo que ha generado un aumento en los últimos años de las áreas cultivadas. Este frutal proveniente de Colombia cuenta con admisibilidad en 18 países del mundo, por lo que el área cosechada se ha incrementado en los últimos años. Sin embargo, fenómenos como la escasez de agua, la variabilidad y el cambio climático y la presencia y dispersión de plagas han planteado desafíos para el establecimiento de una agroindustria del aguacate sostenible en nuestro país. En este contexto, el objetivo principal de este trabajo de investigación fue implementar herramientas de análisis de datos espaciotemporales para la caracterización climática y espectral de las áreas productoras de aguacate cv. Hass. El estudio se dividió en dos etapas: en la primera, se realizó la caracterización y modelación climática bajo escenarios de variabilidad y cambio climático a nivel espacial en las regiones con aptitud para el cultivo de aguacate en Colombia. Por su parte, en la segunda etapa, utilizando imágenes multiespectrales obtenidas de sensores remotos y proximales, y bases de datos de clima de libre acceso se validaron índices de vegetación y variables de clima para determinar su capacidad para discriminar entre plantas visualmente afectadas por distintas fuentes de estrés (bióticos y abióticos) y plantas sanas, así como su potencial uso para predecir componentes de rendimiento del cultivo. De acuerdo con nuestros resultados, las zonas productoras de aguacate cv. Hass en Colombia se agrupan en cinco zonas climáticas homogéneas. Las herramientas de predicción climática, a partir de redes neuronales (ConvLSTM y Bi-LSTM), así como el modelo Sarima representaron adecuadamente los patrones de temperatura y precipitación para cada uno de los cinco clústeres establecidos. Además, el modelo Maxent implementado, permitió estimar el riesgo asociado al cambio climático, en términos de modificación de áreas idóneas para la producción en dos escenarios de cambio climático y tres períodos de tiempo. Así mismo, se presentan resultados sobre la validación de herramientas de teledetección para la identificación de afectaciones y la estimación de productividad en parcelas comerciales de aguacate cv. Hass, en uno de los principales municipios productores de Colombia (Texto tomado de la fuente).The Hass avocado cv. has experienced a worldwide growth in demand, which has generated an increase in cultivated areas in recent years. This fruit tree from Colombia has admissibility in 18 countries of the world, so the harvested area has increased in recent years. However, phenomena such as water scarcity, variability and climate change, and the presence and dispersion of pests have posed challenges to the establishment of a sustainable avocado agroindustry in our country. In this context, the main objective of this research work was to implement spatio-temporal data analysis tools for the climatic and spectral characterization of Hass avocado producing areas. The study was divided into two stages: in the first, the climatic characterization and modeling under scenarios of variability and climate change at the spatial level in the regions with aptitude for avocado cultivation in Colombia was carried out. For its part, in the second stage, using multispectral images obtained from remote and proximal sensors, and open access climate databases, vegetation indices and climate variables were validated to determine their capacity to discriminate between plants visually affected by different sources of stress (biotic and abiotic) and healthy plants, as well as their potential use to predict crop yield components. According to our results, the Hass avocado producing areas in Colombia are grouped into five homogeneous climatic zones. Climate prediction tools, based on neural networks (ConvLSTM and Bi-LSTM), as well as the Sarima model, adequately represented the temperature and precipitation patterns for each of the five established clusters. In addition, the implemented Maxent model allowed estimating the risk associated with climate change, in terms of modification of suitable areas for production in two climate change scenarios and three time periods. Likewise, results are presented on the validation of remote sensing tools for the identification of affectations and the estimation of productivity in commercial Hass avocado plots, in one of the main producing municipalities in Colombia.MaestríaMagister en GeomáticaLínea Agricultura 4.0 y Gestión Tecnológica248 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ciencias Agrarias - Maestría en GeomáticaFacultad de Ciencias AgrariasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá630 - Agricultura y tecnologías relacionadas::631 - Técnicas específicas, aparatos, equipos, materiales630 - Agricultura y tecnologías relacionadas::634 - Huertos, frutas, silviculturaAGUACATE-CONSERVACIONCLIMATOLOGIA AGRICOLAMETEOROLOGIA AGRICOLARECOPILACION DE DATOSCAMBIOS CLIMATICOSVARIABILIDAD DE PRECIPITACIONZONAS CLIMATICASAvocado - preservationCrops and climateMeteorology, agriculturalData collectingClimatic changesPrecipitation variabilityClimatic zonesVariabilidad y cambio climáticoSeries de tiempoRedes neuronales profundasÍndices de vegetaciónTeledetecciónClimate variability and changeTime seriesDeep neural networksVegetation indicesRemote sensingHerramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. 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

Herramientas de análisis espacio-temporal de datos climáticos y espectrales como base para la caracterización y modelación climática y estimación indirecta de parámetros productivos en aguacate cv. Hass

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