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<suppInfo>A definição deste tipo de produto encontra-se na Especificação Técnica para Produtos de Conjuntos de Dados Geoespaciais (ET-PCDG). A PCDG pode ser obtida no Geoportal do Exército Brasileiro (http://www.geoportal.eb.mil.br).</suppInfo>
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<stepSrc>
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<prcStep>
<stepDesc>Modelo Digital de Terreno com resolução espacial de 40 metros por pixel, gerado através de correlação esteroscópica de fotografias aéreas com objetivo exclusivo de geração de Ortofotos.</stepDesc>
<stepDateTm>2018-03-20</stepDateTm>
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<prcStep>
<stepDesc>Coleta de Pontos de Apoio de campo realizada com o objetivo de orientar as imagens aéreas na etapa de aerotriangulação. Para realização desta etapa foram rastreados pontos de apoio suplementar, com tempo de ocupação mínima de 30 minutos e foram utilizadas como base as estações da RBMC.</stepDesc>
<stepDateTm>2018-03-22</stepDateTm>
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<srcDesc>Ponto de Apoio</srcDesc>
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<resTitle>HV-04</resTitle>
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<stepSrc>
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<stepSrc>
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<prcStep>
<stepDesc>Aerotriangulação gerada para o lote 01 utilizando as imagens aerofogrametricas e pontos de apoio citados anteriormente.</stepDesc>
<stepDateTm>2018-03-26</stepDateTm>
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<prcStep>
<stepDesc>Aquisição vetorial a partir da ortoimagem</stepDesc>
<stepDateTm>2018-07-16</stepDateTm>
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<prcStep>
<stepDesc>Reambulação</stepDesc>
<stepDateTm>2018-08-17</stepDateTm>
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<prcStep>
<stepDesc>ORTOIMAGEM com resolução espacial de 35cm, nas bandas R,G,B e IR, 8 bits.</stepDesc>
<stepDateTm>2019-03-21</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Modelo Digital de Superfície com resolução espacial de 2,5 metros por pixel, gerado através de correlação esteroscópica de fotografias aéreas.</stepDesc>
<stepDateTm>2020-02-03</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Restituição da Hidrografia realizada a partir de processos de restituição estereofotogrametrica na escala 1:25000, obtida seguindo as especificações técnicas da ET-ADGV e estruturada seguindo as especificações técnicas da ET-EDGV.</stepDesc>
<stepDateTm>2020-02-03</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Modelo Digital de Terreno com resolução espacial de 2,5 metros por pixel, gerado através de correlação esteroscópica de fotografias aéreas e processos de filtragem. Para melhor modelagem do MDT foram utilizadas as breaklines da hidrografia como injunção nos modelos.</stepDesc>
<stepDateTm>2020-02-03</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Curvas de Nível geradas com equidistância de 10 metros a partir do MDT.</stepDesc>
<stepDateTm>2020-02-03</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Pontos Cotados obtido a partir do Modelo Digital do Terreno.</stepDesc>
<stepDateTm>2020-02-03</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Validação</stepDesc>
<stepDateTm>2020-06-26</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Criacão da área contínua</stepDesc>
<stepDateTm>2020-07-24</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Edição</stepDesc>
<stepDateTm>2020-07-31</stepDateTm>
</prcStep>
<statement>Aquisição vetorial na escala 1:25.000, a partir da ortoimagem com resolução espacial de 35 cm, nas bandas R,G, B e IR, 8 bits seguindo as especificações de aquisição e estruturação contidas nas normas ET-ADGV e ET-EDGV.</statement>
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<cornerPts>
<pos Sync="TRUE">-51.073774 -29.509286</pos>
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<dimSize Sync="TRUE">13906</dimSize>
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<identVrsn>7.4</identVrsn>
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<idVersion Sync="TRUE">9.7(9.2.0)</idVersion>
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<ERROR>gmd:MD_FeatureCatalogueDescription</ERROR>
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<Band>
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<ERROR>gmd:MD_ImageDescription</ERROR>
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<covDim>
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</Data>
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