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@MastersThesis{Oliveira:2017:AvUsSe,
               author = "Oliveira, Luana Thayza de",
                title = "Avalia{\c{c}}{\~a}o do uso de sensor termal a bordo de VANT 
                         atrav{\'e}s de an{\'a}lises radiom{\'e}tricas, espectrais, 
                         espaciais e posicionais",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2017",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2017-05-15",
             keywords = "termal, VANT, caracteriza{\c{c}}{\~a}o de sensores, 
                         exatid{\~a}o posicional, thermal infrared, UAV, characterization 
                         of sensors, positional accuracy.",
             abstract = "Dados obtidos na regi{\~a}o do infravermelho termal (Thermal 
                         Infrared - TIR) podem revelar informa{\c{c}}{\~o}es n{\~a}o 
                         vis{\'{\i}}veis importantes sobre os alvos observados. Tais 
                         dados t{\^e}m aplica{\c{c}}{\~o}es nas mais diversas {\'a}reas 
                         de monitoramento, seja ambiental, urbano ou agr{\'{\i}}cola. 
                         Contudo, sua larga utiliza{\c{c}}{\~a}o esbarra em alguns 
                         desafios: h{\'a} poucos sensores orbitais operacionais 
                         dispon{\'{\i}}veis que atuam no TIR. E, dentre os sistemas TIR 
                         existentes, precisa ser ainda considerada a sua 
                         limita{\c{c}}{\~a}o quanto {\`a} frequ{\^e}ncia de imageamento 
                         e resolu{\c{c}}{\~a}o espacial. Assim, o uso de sistemas de 
                         sensores infravermelhos termais a bordo de aeronaves e, mais 
                         recentemente, em ve{\'{\i}}culos a{\'e}reos n{\~a}o tripulados 
                         (VANTs) tem sido crescente. Em contrapartida, poucos estudos 
                         t{\^e}m explorado as caracter{\'{\i}}sticas dos sensores 
                         aplicados nestas miss{\~o}es e tampouco a acur{\'a}cia dos dados 
                         obtidos. Neste contexto, o objetivo deste trabalho foi avaliar as 
                         capacidades radiom{\'e}tricas, espectrais e espaciais de dois 
                         sensores termais comerciais, um deles desenvolvido para a 
                         integra{\c{c}}{\~a}o em plataformas n{\~a}o tripuladas, bem 
                         como avaliar exatid{\~a}o posicional dos produtos resultantes do 
                         seu uso em um VANT, ortomosaico termal e modelo de 
                         superf{\'{\i}}cie (MDS), segundo o Padr{\~a}o de Exatid{\~a}o 
                         Cartogr{\'a}fica dos Produtos Cartogr{\'a}ficos Digitais 
                         (PEC-PCD). Para tanto, foram realizados procedimentos 
                         laboratoriais de caracteriza{\c{c}}{\~a}o dos dois sensores. Em 
                         campo, foi realizado levantamento de dados termais utilizando um 
                         VANT multirrotor quadric{\'o}ptero em uma {\'a}rea de 
                         aproximadamente 10 mil mē, al{\'e}m de medi{\c{c}}{\~o}es 
                         experimentais de quatro superf{\'{\i}}cies com diferentes tipos 
                         de cobertura pelos dois sensores previamente caracterizados. Dos 
                         experimentos laboratoriais de caracteriza{\c{c}}{\~a}o 
                         espectral, resultaram as curvas da fun{\c{c}}{\~a}o de reposta 
                         espectral (FRE) dos sensores, em que em ambos os casos, foi 
                         poss{\'{\i}}vel verificar diferen{\c{c}}as na faixa de 
                         atua{\c{c}}{\~a}o em rela{\c{c}}{\~a}o ao declarado pelos 
                         fabricantes. Na an{\'a}lise radiom{\'e}trica um dos sensores 
                         demonstrou ter incertezas superiores {\`a}s declaradas pelos 
                         fabricantes, e na caracteriza{\c{c}}{\~a}o espacial, os valores 
                         de EIFOV de cada um dos sensores foram obtidos. A an{\'a}lise dos 
                         dados obtidos em campo, al{\'e}m de validar as incertezas de 
                         medi{\c{c}}{\~a}o determinadas em laborat{\'o}rio, permitiu 
                         verificar que, mesmo em baixas altitudes, a atmosfera pode exercer 
                         influ{\^e}ncia sobre os dados termais e levar a conclus{\~o}es 
                         err{\^o}neas sobre os alvos, sobretudo em an{\'a}lises 
                         quantitativas. Da avalia{\c{c}}{\~a}o quanto {\`a} 
                         exatid{\~a}o posicional, concluiu-se que o ortomosaico gerado sem 
                         pontos de controle apresenta exatid{\~a}o planim{\'e}trica a 
                         partir da escala 1:5.000 e altim{\'e}trica a partir de 1:50.000, 
                         e o ortomosaico processado com 4 pontos de controle apresentou 
                         exatid{\~a}o planim{\'e}trica a partir de 1:1.000 e 
                         altim{\'e}trica a partir de 1:25.000. Desde que consideradas as 
                         incertezas envolvidas no processo de obten{\c{c}}{\~a}o das 
                         imagens termais por VANT, esta demonstrou ser uma alternativa 
                         eficaz para imageamento de {\'a}reas com caracter{\'{\i}}sticas 
                         n{\~a}o aparentes na faixa do vis{\'{\i}}vel. ABSTRACT: Data 
                         obtained in the Thermal Infrared (TIR) part of the electromagnetic 
                         spectrum may present invisible, but important, information from 
                         the targets of interest. Such data are important in the most 
                         different applications of environmental, urban and agriculture 
                         monitoring. Nevertheless there are some challenges to its wide 
                         use: presently there are few operational orbital TIR sensors 
                         available, and among those there are limitations regarding its 
                         imaging frequency and spatial resolution. Therefore the use of TIR 
                         systems aboard aircrafts, and more recently on drones is growing. 
                         On the other hand, few studies evaluated the characteristics of 
                         the TIR sensors used in such missions and neither the accuracy of 
                         the data obtained. In this frame, the objective of this study was 
                         the evaluation of the radiometric, spectral and spatial capacities 
                         of two commercial thermal sensors. One of them was developed for 
                         the integration on unmanned platforms, as well as to evaluate the 
                         positional accuracy of the resulting products for its use on a 
                         drone, a thermal ortho-mosaic and a Digital Surface Model (DSM), 
                         in accordance with the Brazilian Cartographic Accuracy Standard of 
                         Digital Cartographic Products (PEC-PCD). In order to perform these 
                         tasks, laboratory procedures were executed to characterize both 
                         sensor systems. Afterwards a field survey of thermal data was 
                         done, using a multi-rotor quadri-copter drone, at an area of 
                         approximately 10,000 m2, besides experimental measurements on four 
                         test-sites with different types of soil cover, using both 
                         previously characterized sensors. From the laboratory works on 
                         spectral characterization, frequency curves of both sensors were 
                         obtained. It was verified that there were differences in the 
                         respective performance bands, regarding what was declared by the 
                         manufacturers. The radiometric analysis from one of the sensors 
                         showed higher uncertainties than those declared, as well as at the 
                         spatial characterization of EIFOV values, from each sensor. The 
                         analysis of data obtained during the field survey, besides 
                         validating the uncertainties from the measurements in the 
                         laboratory, also showed that, even at low altitudes, the 
                         atmosphere influences thermal data and can lead to erroneous 
                         conclusions about targets, especially at a quantitative analysis. 
                         Regarding the positional accuracy, it was concluded that the 
                         ortho-mosaic obtained without ground control points, presents a 
                         planimetric accuracy at 1:5,000 scale, and an altimetry accuracy 
                         at 1:50,000. The ortho-mosaic processed with four control points 
                         presented a planimetric accuracy starting at 1:1,000 and an 
                         altimetry accuracy starting at 1:25,000. Taking into account the 
                         uncertainties involved in the process to obtain thermal images 
                         with a drone, this is an efficient alternative to image areas with 
                         non-apparent characteristics in the visible spectrum.",
            committee = "Almeida, Cl{\'a}udia Maria de (presidente) and Kux, Hermman 
                         Johann Heinrich (orientador) and Korting, Thales Sehn and Castro, 
                         Ruy Morgado de",
         englishtitle = "Evaluation of the use of a thermal sensor on a uav through 
                         radiometric, spectral, spatial and positional analysis",
             language = "pt",
                pages = "157",
                  ibi = "8JMKD3MGP3W34P/3NS677H",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34P/3NS677H",
           targetfile = "publicacao.pdf",
        urlaccessdate = "23 nov. 2020"
}


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