20260416 10301400 1.0 TRUE CreateMosaicDataset D:\OrtoRural2025\OrtoRural2025.gdb OrtoRural2025 GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]] 4 "8-bit unsigned" None # AddRastersToMosaicDataset D:\OrtoRural2025\OrtoRural2025.gdb\OrtoRural2025 "Raster Dataset" D:\OrtoRural2025\Ortobogotarural2025.tif UPDATE_CELL_SIZES NO_BOUNDARY NO_OVERVIEWS # 0 1500 "PROJCS["MAGNA-SIRGAS_2018_Origen-Nacional",GEOGCS["MAGNA-SIRGAS_2018",DATUM["Marco_Geocentrico_Nacional_de_Referencia_2018",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",5000000.0],PARAMETER["False_Northing",2000000.0],PARAMETER["Central_Meridian",-73.0],PARAMETER["Scale_Factor",0.9992],PARAMETER["Latitude_Of_Origin",4.0],UNIT["Meter",1.0]];-618700 -8436100 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision" *.tif SUBFOLDERS "Exclude duplicates" BUILD_PYRAMIDS CALCULATE_STATISTICS NO_THUMBNAILS "Carga OrtoRural2025" FORCE_SPATIAL_REFERENCE NO_STATISTICS # 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0 1500 "PROJCS["MAGNA-SIRGAS_2018_Origen-Nacional",GEOGCS["MAGNA-SIRGAS_2018",DATUM["Marco_Geocentrico_Nacional_de_Referencia_2018",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",5000000.0],PARAMETER["False_Northing",2000000.0],PARAMETER["Central_Meridian",-73.0],PARAMETER["Scale_Factor",0.9992],PARAMETER["Latitude_Of_Origin",4.0],UNIT["Meter",1.0]];-618700 -8436100 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision" *.tif SUBFOLDERS "Exclude duplicates" BUILD_PYRAMIDS CALCULATE_STATISTICS NO_THUMBNAILS "Carga OrtoRural2025" FORCE_SPATIAL_REFERENCE NO_STATISTICS # USE_PIXEL_CACHE D:\OrtoRural2025\pixel_cache AddRastersToMosaicDataset D:\OrtoRural2025\OrtoRural2025.gdb\OrtoRural2025 "Raster Dataset" D:\OrtoRural2025\Ortobogotarural2025.tif UPDATE_CELL_SIZES NO_BOUNDARY NO_OVERVIEWS # 0 1500 "PROJCS["MAGNA-SIRGAS_2018_Origen-Nacional",GEOGCS["MAGNA-SIRGAS_2018",DATUM["Marco_Geocentrico_Nacional_de_Referencia_2018",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",5000000.0],PARAMETER["False_Northing",2000000.0],PARAMETER["Central_Meridian",-73.0],PARAMETER["Scale_Factor",0.9992],PARAMETER["Latitude_Of_Origin",4.0],UNIT["Meter",1.0]];-618700 -8436100 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision" *.tif SUBFOLDERS "Exclude duplicates" BUILD_PYRAMIDS CALCULATE_STATISTICS NO_THUMBNAILS "Carga OrtoRural2025" FORCE_SPATIAL_REFERENCE NO_STATISTICS # 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# # "1 0;2 0;3 0;4 0" # # 004 150000000 5000 ItemDescription Mosaico de 32 ortoimágenes satelitales (EarthScanner y Pléiades) con bandas RGB e Infrarrojo Cercano (NIR), que cubre la zona rural al sur de Bogotá D.C. Generado con un GSD de 0.50 metros bajo especificaciones para escala 1:10.000. Generado por SIGLA S.A.S. en 2025. <div style='text-align:Left;'><div><div><p><span>La Ortoimagen Satelital de la Zona Rural de Bogotá D.C. es un producto cartográfico básico en formato ráster, procesado geométricamente para corregir las distorsiones inherentes a la captura y topografía, formando una representación cartográfica precisa.</span></p><p><span>Características técnicas del producto:</span></p><p><span>- Extensión: ~107.304 Ha (Zona rural al sur de Bogotá D.C.).</span></p><p><span>- Escala de aplicación: 1:10.000.</span></p><p><span>- Resolución espacial (GSD/Pixel): 0.50 m.</span></p><p><span>- Bandas espectrales: 4 bandas (Rojo, Verde, Azul e Infrarrojo Cercano - RGB+NIR).</span></p><p><span>- Sensores satelitales: EarthScanner y Pléiades 1A/1B.</span></p><p><span>- Total de imágenes que conforman el mosaico: 32 imágenes satelitales obtenidas en 2024 y/o 2025.</span></p><p><span>- Control Terrestre: Se utilizaron un total de 1.235 Tie Points automáticos y 144 puntos de control y/o chequeo.</span></p><p><span>- Precisión de la Aerotriangulación (RMS): X=0.107 m, Y=0.130 m, Z=0.015 m.</span></p><p><span>- Método de ajuste radiométrico: Lineal (con edición exhaustiva de líneas de costura debido a nubosidad).</span></p><p><span>Generado por: SIGLA S.A.S. — Sistemas de Información Geográfica de Latinoamérica</span></p><p><span>Contrato/Autoridad: Unidad Administrativa Especial de Catastro Distrital (UAECD).</span></p><p><span>Normas aplicadas: Resoluciones IGAC 471/2020, 529/2020, 1421/2021, 197/2022 y 1040/2023.</span></p><p><span /></p></div></div></div> orthorural2025funcion 2025-12-17T00:00:00 Ortoimagen Mosaico Satelital RGB NIR Infrarrojo Cercano EarthScanner Pléiades Bogotá D.C. Zona Rural Cartografía básica Ráster MAGNA-SIRGAS UAECD 2025 0.5m 74.07 74.46 3.72 4.54 Unidad Administrativa Especial de Catastro Distrital - UAECD <div style='text-align:Left;'><div><p><span>CC BY 4.0</span></p></div></div> 20260420 Unidad Administrativa Especial de Catastro Distrital — UAECD / IDECA 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