O uso de técnicas de sensoriamento remoto e das aeronaves remotamente pilotadas na agricultura: contribuições estatísticas e geotecnológicas

• Ano de defesa: 2022
• Autor(a) principal: Facco, Fernanda Lampert Batista
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• dARK ID: ark:/26339/00130000123n8
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Geografia; UFSM; Programa de Pós-Graduação em Geografia; Centro de Ciências Naturais e Exatas
• Palavras-chave em Português: Geotecnologias; Interdisciplinaridade; Soja; Geotechnologies; Interdisciplinarity; Soy; CNPQ::CIENCIAS HUMANAS::GEOGRAFIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/26641

Remotely Pilot Aircrafts (RPA) come revolutionizing the way that society watches terrestrial topographic surface, being the maps cartographic products that demonstrate a complex language. By lining this geotechnology to multitasking techniques of processin g and studies targeted to agriculture, there is a support to the processes of decisionmaking. Yet, still has a long path of learning concerning the connections between the truth in the field and the remote observations. In quite of this context, the main purpose of this study is to obtain cartographic products related to soya productiveness’ estimate and crop monitoring using RPA with the support of greenery indexes in the range of visible. Is catalogued, as specific goals: to analyse the contribution of c artographic obtained by imaging with RPA in the development of soya’s culture (Glycine max); to verify if there are differences of efficiency with the tested products; to verify if there is statistical summary between the Green Leaf Indexes (GLI) and Visib le Atmosphere Region Index (VARI) with the productivity data obtained in the field. The present work uses on its methodology a compiled of data arise from: experiment, climatology and photogrammetric. The climatic and testing data were tabulated through Ex cel while the products from RPA were processed on MetaShape and QGis, on which was made the implementation of GLI and VARI indexes. Subsequently, was used ARCGIS software to obtain statistic data derivated from imaging and flora rates. Lastly, were applied PAST, SISVAR and GENES’ softwares to statistical evaluations, hasn’t being possible to observe difference of efficiency with the tested treatments. Furthermore, there was no direct correlation of the greenery indexes with productivity. The tool was useful for the monitoring of cultural development, allowing to connect aerial photogrammetry with the short distance. Is worth highlighting that the RPA have extremely interesting characteristics and its relation with the farming themes should be technically imp roved.