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Revista Raega: O Espaço Geográfico em Análise
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VERIFICAÇÃO DA QUALIDADE DE ORTOMOSAICOS PRODUZIDOS A PARTIR DE IMAGENS OBTIDAS COM AERONAVE REMOTAMENTE PILOTADA SEM O USO DE PONTOS DE APOIO

Authors: Sopchaki, Carlos Henrique; Paz, Otacílio Lopes de Souza da; Graça, Niarkios Luiz Santos de Salles; Sampaio, Tony Vinicius Moreira;

VERIFICAÇÃO DA QUALIDADE DE ORTOMOSAICOS PRODUZIDOS A PARTIR DE IMAGENS OBTIDAS COM AERONAVE REMOTAMENTE PILOTADA SEM O USO DE PONTOS DE APOIO

Abstract

UAVs (Unmanned aerial vehicle) have been widely used in the generation of orthomosaics and digital elevation models (DEM) that give support geospatial analyzes. Sometimes these analyzes require rapid surveys and/or are make in remote areas, which makes it unfeasible to use UAVs associated with the points of support for the correction of position, adjustment and evaluation of the quality of orthomosaic and MDEs. Currently it is possible to automate the generation of these products using pre-established routines available in specialized programs to manipulation UAV´s images. This work evaluates the planimetric quality of the orthomosaics produced from images collected with UAVs associated with the use of automated routines of specialist software, without the use of support points. As a result, it was observed that 100% of the orthomosaics obtained was classified into Class A of the scale 1: 50,000 or higher (PEC-PCD - Cartographic Accuracy Standard of Digital Cartographic Products) and, the best planimetric accuracy was 1:5000. The orthomosaics showed regular pattern of error distribution, not presenting preferred areas of deformation (edge / center). The errors in the measured distances in orthomosaics are less than 1.6% of the measured distance. As RPAs (Aeronaves Remotamente Pilotadas) têm sido amplamente utilizadas na geração de ortomosaicos e modelos digitais de elevação (MDE), que subsidiam as análises geoespaciais. Por vezes, estas análises demandam levantamentos rápidos e/ou são feitos em áreas remotas, o que inviabiliza o uso de RPAs associadas a pontos de apoio para a correção da posição, ajuste e avaliação da qualidade dos ortomosaicos e MDEs. Atualmente é possível a geração automatizada destes produtos através do uso de rotinas preestabelecidas disponíveis em programas especializados na manipulação das imagens obtidas pelas RPAs. Este trabalho avaliou a qualidade planimétrica dos ortomosaicos produzidos a partir de imagens coletadas com RPAs criados a partir do uso de rotinas automatizadas de software especialista, sem o emprego de pontos de apoio de campo. Como resultado observou-se que 100% dos ortomosaicos produzidos enquadram-se na Classe A da escala 1:50.000 ou superior (PEC-PCD - Padrão de Exatidão Cartográfica dos Produtos Cartográficos Digitais), sendo a melhor acurácia planimétrica obtida compatível com a escala 1:5.000. Os ortomosaicos apresentaram padrão regular de distribuição do erro, não apresentando áreas preferenciais de deformação. Os erros nas distâncias obtidas nos ortomosaicos são inferiores a 1,6% ao valor da distância medida.

Related Organizations
Subjects by Vocabulary

Microsoft Academic Graph classification: Geospatial analysis business.industry Computer science computer.software_genre Software Regular pattern Scale (map) business Digital elevation model Cartography computer

Keywords

Geography, Planning and Development, Accuracy; Fitness to use; Geospatial analysis; RPA; UAV., Acurácia; Adequação ao uso; Análise geoespacial; Drone; RPA.

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    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
gold