Estimativa de parâmetros biofísicos de lavoura cafeeira a partir de imagens obtidas por aeronave remotamente pilotada

• Ano de defesa: 2018
• Autor(a) principal: Gonçalves, Luana Mendes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Lavras; Programa de Pós-graduação em Engenharia Agrícola; UFLA; brasil; Departamento de Engenharia
• Palavras-chave em Português: Agricultura de precisão; Veículo aéreo não tripulado (VANT); Drone; Cafeeiros; Ortomosaico; Precision agriculture; Unmanned aerial vehicle (UAV); Coffee; Orthomosaic; Mecanização Agrícola
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/30549

Precision Agriculture (PA) is based on a set of techniques and technologies that optimizes the resources used by the producer, identifying spatial variability in the crop. Within this set it is possible to cite the remote sensing that assists in obtaining data remotely and in the localized support of agricultural managements. The objective of this work was to obtain indirect measures of height and diameter of coffee trees using high spatial resolution images detected by a Remotely Piloted Aircraft (RPA); propose a model that may be used to estimate such parameters; to perform analysis of the coverage percentage and leaf area index over the follow-up months and to calculate and to map coefficient of culture (Kc) using data of height and canopy diameter detected by RPA. The experiment was carried out in a coffee plantation belongs at the Federal University of Lavras, Lavras, MG. A rotating wing RPA was used in autonomous flight mode, carring a conventional camera, height of 30 m, with image overlap of 80% and velocity of 3 m/s. The images were collected once a month, from June 2017 to March 2018, at the same day that the images were collected, data of height and canopy diameter of the coffee plants where collected in the field as well, in order to compare them. The images were processed in the PhotoScan software and the analyzes were done in Qgis. It was obtained a correlation of 85% between field height values and height values obtained through RPA, and 95% correlation between values of canopy diameter obtained in the field and the values obtained through RPA.It made possible to propose an estimation equation of biophysical parameters, such as height and crown diameter of coffee trees, by using values derived from image obtained by RPA. It was possible to analyze the Percentage of land cover and Foliar Area Index by data obteined remotely, besides proposing a map of Kc for the variety of coffee under study.