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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dc.contributor.advisorRamírez Gil, Joaquín Guillermospa
dc.contributor.advisorTerán Chaves, Cesar Augustospa
dc.contributor.authorSánchez Vivas, Diego Fernandospa
dc.contributor.cvlacSánchez Vivas, Diego Fernando [0000092231]spa
dc.contributor.googlescholarSánchez Vivas, Diego Fernando [https://scholar.google.se/citations?user=7KTTn5UAAAAJ]spa
dc.contributor.orcidSánchez Vivas, Diego Fernando [0000000163130871]spa
dc.contributor.researchgateSánchez Vivas, Diego Fernando [https://www.researchgate.net/profile/Diego-Sanchez-Vivas]spa
dc.contributor.researchgroupBiogénesisspa
dc.contributor.scopusSánchez Vivas, Diego Fernando [58159513500]spa
dc.coverage.countryColombiaspa
dc.date.accessioned2024-10-03T17:41:03Z
dc.date.available2024-10-03T17:41:03Z
dc.date.issued2024
dc.descriptionilustraciones, diagramas, fotografías, mapas, tablasspa
dc.description.abstractEl 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).spa
dc.description.abstractThe 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.eng
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagister en Geomáticaspa
dc.description.researchareaLínea Agricultura 4.0 y Gestión Tecnológicaspa
dc.format.extent248 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/86890
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.facultyFacultad de Ciencias Agrariasspa
dc.publisher.placeBogotá, Colombiaspa
dc.publisher.programBogotá - Ciencias Agrarias - Maestría en Geomáticaspa
dc.relation.indexedAgrosaviaspa
dc.relation.indexedAgrovocspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subject.ddc630 - Agricultura y tecnologías relacionadas::631 - Técnicas específicas, aparatos, equipos, materialesspa
dc.subject.ddc630 - Agricultura y tecnologías relacionadas::634 - Huertos, frutas, silviculturaspa
dc.subject.lembAGUACATE-CONSERVACIONspa
dc.subject.lembAvocado - preservationeng
dc.subject.lembCLIMATOLOGIA AGRICOLAspa
dc.subject.lembCrops and climateeng
dc.subject.lembMETEOROLOGIA AGRICOLAspa
dc.subject.lembMeteorology, agriculturaleng
dc.subject.lembRECOPILACION DE DATOSspa
dc.subject.lembData collectingeng
dc.subject.lembCAMBIOS CLIMATICOSspa
dc.subject.lembClimatic changeseng
dc.subject.lembVARIABILIDAD DE PRECIPITACIONspa
dc.subject.lembPrecipitation variabilityeng
dc.subject.lembZONAS CLIMATICASspa
dc.subject.lembClimatic zoneseng
dc.subject.proposalVariabilidad y cambio climáticospa
dc.subject.proposalSeries de tiempospa
dc.subject.proposalRedes neuronales profundasspa
dc.subject.proposalÍndices de vegetaciónspa
dc.subject.proposalTeledetecciónspa
dc.subject.proposalClimate variability and changeeng
dc.subject.proposalTime serieseng
dc.subject.proposalDeep neural networkseng
dc.subject.proposalVegetation indiceseng
dc.subject.proposalRemote sensingeng
dc.titleHerramientas 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. Hassspa
dc.title.translatedSpace-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 avocadoeng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentEstudiantesspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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