Análise de produtos cartográficos obtidos com câmera digital não métrica acoplada a um veículo aéreo não tripulado em áreas urbanas e rurais no estado de Goiás

• Ano de defesa: 2015
• Autor(a) principal: Alves Júnior, Leomar Rufino
• Orientador(a): Ferreira, Manuel Eduardo
• Banca de defesa: Ferreira , Manuel Eduardo, Oliveira, Ivanilton José de, Jorge, Lúcio André de Castro
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• dARK ID: ark:/38995/0013000002dkq
• Idioma: por
• Instituição de defesa: Universidade Federal de Goiás
• Programa de Pós-Graduação: Programa de Pós-graduação em Geografia (IESA)
• Departamento: Instituto de Estudos Socioambientais - IESA (RG)
• País: Brasil
• Palavras-chave em Português: Ortomosaico; Automação fotogramétrica; Atualização cartográfica; Ponto de controle; Calibração de câmera; Pix4Dmapper
• Palavras-chave em Inglês: Orthomosaic; Photogrammetric automation; Cartography update; Control point; Camera calibration; Pix4Dmapper
• Área do conhecimento CNPq: CIENCIAS HUMANAS::GEOGRAFIA
• Link de acesso: http://repositorio.bc.ufg.br/tede/handle/tede/4952

This research aimed to verify the precision and accuracy of orthomosaics and Digital Surface Model (DSM) generated automatically by aerial photography taken with an Unmanned Aerial Vehicle (UAV) in urban and rural areas at the cities of Goiânia, Goiás and Edéia, all located in the state of Goiás. The survey also verified for the influence of the scale, depending on the flight height, the influence of the sunlight, and the phenological analysis obtained in agricultural areas with sugarcane and corn (vegetative cycle) crops. Flight plans were drawn up in E-mo-tion software provided by Sensefly - Swiss company manufacturer of UAV Swinglet CAM used in this work. The camera on board UAV was the Canon IXUS 220 HS, with a spatial resolution of 12.1 megapixel, CMOS sensor equipped with type 1 / 2.3" (4000 x 3000 pixel), pixel pitch of 1.54 m, and focal distance equivalent of 35 mm. To check the precision and accuracy of orthomosaics in urban areas, the flights were uniformly distributed in the study area with three-dimensional coordinates pre-marked targets read in the orthomosaic itself, and compared with the coordinates obtained by RTK and static fast positioning methods geodetic survey, using a pair of GNSS signal receiver. Evaluation of Cartographic Accuracy Standards (PEC, defined by the Brazilian decree, no. 89817 of June 20, 1984) was performed by discrepancies between these coordinates. The bias was analyzed by student's t test and the accuracy with the chi-square probability. We have found that in those orthomosaics performed over the urban area in Goiânia city, some buildings were not properly processed in terms of the conical to orthogonal projection; this product was classified as PEC Class A to the 1/250 scale. In Goiás city, the generated orthomosaics without support points were classified as PEC Class A to the 1/2,500 scale, while the orthomosaic generated with eight supporting points was classified as PEC Class A to the 1/1,125 scale. The orthomosaic and MDS generated without ground supporting points presented planialtimetric trends. The mean difference calculated in the orthomosaic with ground supporting was 54 times lower on the E axis, and 111 times lower in N axis, and 10 times lower in the Z axis relative to the average of the discrepancies in orthomosaic without ground control points. The MDS generated with and without supporting showed vertical displacement trend. Thus it was evident the need for supporting points for making orthomosaics and MDS obtained with UAV. In flights performed in crop areas, it was observed that for a better estimate of MPRI vegetation index, the photographs needs to with larger scales (GSD of 5 cm), even with a higher software difficulty in finding homologous points. It did not occur when we used pictures with smaller scales (GSD 20 cm, or larger) for the generation of orthomosaics and MDS.