Corn crops identification using multispectral images from unmanned aircraft systems

dc.contributor.advisorRacoceanu, Daniel
dc.contributor.authorTrujillano Asato, Fedra Catherinees_ES
dc.date.accessioned2019-04-08T23:04:17Zes_ES
dc.date.available2019-04-08T23:04:17Zes_ES
dc.date.created2018es_ES
dc.date.issued2019-04-08es_ES
dc.description.abstractClimate change and migration of population from rural to urban areas are affecting the agricultural production around the world. This study was based in the particular department of Ancash - Peru where corn is one of the most important crops of the region. Authorities in this region are concerned in finding a method, different from census; that can constantly monitor corn crops areas. This data is important to evaluate how these two causes will impact on food security in Ancash. The first part of the present thesis reviews the current techniques in the recognition of crop areas using remote sensing and multispectral images. The second part explains the methodology developed for this study, considering the data acquisition using Unmanned Aircraft Systems, the preparation of the acquired data and two deep learning model approaches. The first approach is based on binary classification of corn patches using Le Net model with near infrared images. The second one describes the segmentation of corn areas in different stages using the U-net model, in this case five band images were considered. The third part shows the results of both approaches. From these results it is concluded that training a model with data from different stages and scenarios of two campaigns (2016 and 2017) can achieve a 95% of accuracy in corn segmentation.es_ES
dc.description.uriTesises_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12404/13923
dc.language.isoenges_ES
dc.publisherPontificia Universidad Católica del Perúes_ES
dc.publisher.countryPEes_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.subjectMaíz--Cultivos--Monitoreo--Perú--Ancashes_ES
dc.subjectMaíz--Cultivos--Sensores remotos--Perú--Ancashes_ES
dc.subjectProcesamiento de imágenes digitaleses_ES
dc.subjectImágenes--Vehículos aéreos no tripuladoses_ES
dc.subjectAnálisis espectral--Instrumentoses_ES
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.02.05es_ES
dc.titleCorn crops identification using multispectral images from unmanned aircraft systemses_ES
dc.typeinfo:eu-repo/semantics/masterThesises_ES
renati.discipline613077es_ES
renati.levelhttps://purl.org/pe-repo/renati/level#maestroes_ES
renati.typehttps://purl.org/pe-repo/renati/type#tesises_ES
thesis.degree.disciplineProcesamiento de Señales e Imágenes Digitaleses_ES
thesis.degree.grantorPontificia Universidad Católica del Perú. Escuela de Posgradoes_ES
thesis.degree.levelMaestríaes_ES
thesis.degree.nameMaestro en Procesamiento de Señales e Imágenes Digitales.es_ES

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