<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20210422</CreaDate>
<CreaTime>13233700</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
<MapLyrSync>TRUE</MapLyrSync>
<scaleRange>
<minScale>150000000</minScale>
<maxScale>5000</maxScale>
</scaleRange>
<ArcGISProfile>ItemDescription</ArcGISProfile>
</Esri>
<dataIdInfo>
<idCitation>
<resTitle>carto10000morales19473</resTitle>
</idCitation>
<idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;DIV STYLE="font-size:12pt"&gt;&lt;P&gt;&lt;SPAN&gt;La cartografía básica escala 1:10.000 del municipio Morales (Cauca), elaborada en el año 2020 por el Instituto Geográfico Agustín Codazzi (IGAC), es un producto generado a partir de restitución fotogramétrica a partir de fotografías áreas de 2019 y 2020. Este producto cumple con los estándares de planimetría y altimetría de la escala 1:10.000 y cubre totalmente el área del municipio.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</idAbs>
<searchKeys>
<keyword>Cartografia</keyword>
<keyword>Morales</keyword>
<keyword>Cauca</keyword>
<keyword>Planimetría</keyword>
<keyword>Altimetría</keyword>
<keyword>Hidrografía</keyword>
<keyword>Relieve</keyword>
</searchKeys>
<idPurp>La cartografía básica escala 1:10.000 del municipio Morales (Cauca), elaborada en el año 2020 por el Instituto Geográfico Agustín Codazzi (IGAC), es un producto generado a partir de restitución fotogramétrica a partir de fotografías áreas de 2019 y 2020. Este producto cumple con los estándares de planimetría y altimetría de la escala 1:10.000 y cubre totalmente el área del municipio.</idPurp>
<idCredit>Instituto Geográfico Agustín Codazzi - IGAC</idCredit>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<mdHrLv>
<ScopeCd value="005"/>
</mdHrLv>
<mdDateSt Sync="TRUE">20210721</mdDateSt>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAAAAAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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</Data>
</Thumbnail>
</Binary>
</metadata>
