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<idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;P STYLE="text-align:Justify;margin:0 0 0 0;"&gt;&lt;SPAN&gt;Base cartográfica digital da Região Funcional 1 com geoinformações atualizadas, compatível à escala de 1:25.000, com Padrão de Exatidão Cartográfica (PEC) Classe A, a partir de ortoimagens digitais com resolução espacial de 35cm, datadas de 2019, contemplando classes das seguintes categorias de informação: Agricultura, Biota, Limites, Ciências Atmosféricas, Economia, Elevação, Ambiente, Geocientífico, Saúde, Imagens e Mapas Base, Exército &amp;amp; Inteligência, Águas Interiores, Local, Planejamento e Cadastro, Sociedade, Estrutura, Transporte, Utilitários e Comunicação. Foram geradas 174 cartas topográficas, 174 conjunto de dados geoespaciais vetoriais (CDGV) e uma base contínua vetorial, atendendo às seguintes normas técnicas da Infraestrutura Nacional de Dados Espaciais (INDE): Especificação Técnica para Estruturação de Dados Geoespaciais Vetoriais (ET-EDGV), Especificação Técnica para Aquisição de Dados Geoespaciais Vetoriais (ET-ADGV), Especificação Técnica para Produtos de Conjuntos de Dados Geoespaciais (ET-PCDG) e Especificação Técnica para Controle de Qualidade de Dados Geoespaciais (ET-CQDG).&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;</idAbs>
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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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<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>2018-04-18</stepDateTm>
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<srcDesc>Ponto de Apoio</srcDesc>
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<stepSrc>
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<stepSrc>
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<prcStep>
<stepDesc>Aerotriangulação gerada para o lote 02 utilizando as imagens aerofogrametricas e pontos de apoio citados anteriormente.</stepDesc>
<stepDateTm>2018-08-21</stepDateTm>
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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>2018-11-06</stepDateTm>
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<prcStep>
<stepDesc>Aquisição vetorial a partir da ortoimagem</stepDesc>
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<prcStep>
<stepDesc>Reambulação</stepDesc>
<stepDateTm>2019-05-24</stepDateTm>
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<prcStep>
<stepDesc>ORTOIMAGEM com resolução espacial de 35cm, nas bandas R,G,B e IR, 8 bits.</stepDesc>
<stepDateTm>2019-08-02</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>2020-10-22</stepDateTm>
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<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>2020-10-22</stepDateTm>
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<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>2020-10-22</stepDateTm>
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<prcStep>
<stepDesc>Curvas de Nível geradas com equidistância de 10 metros a partir do MDT.</stepDesc>
<stepDateTm>2020-10-22</stepDateTm>
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<prcStep>
<stepDesc>Pontos Cotados obtido a partir do Modelo Digital do Terreno.</stepDesc>
<stepDateTm>2020-10-22</stepDateTm>
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<prcStep>
<stepDesc>Validação</stepDesc>
<stepDateTm>2021-06-25</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Criacão da área contínua</stepDesc>
<stepDateTm>2021-07-05</stepDateTm>
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<prcStep>
<stepDesc>Edição</stepDesc>
<stepDateTm>2021-07-12</stepDateTm>
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</Data>
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