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 Geological Relief Map of South at a sca​le of 1:5M

​​Geological Relief Map of South America   at a sca​le of 1:5M​

CCGM         SGC         Servicio Geológico de Brasil         ASGMI


​             Authors:
   
            Jorge GÓMEZ TAPIAS, Colombian Geological Survey
            Nohora Emma MONTES RAMÍREZ, Colombian Geological Survey
            Carlos SCHOBBENHAUS, Geological Survey of Brazil

             Download: 
                           



Citation of the map:


English: 

Gómez, J., Schobbenhaus, C. & Montes, N.E., compilers. 2019. Geological Map of South America 2019. Scale 1:5 000 000. Commission for the Geological Map of the World (CGMW), Colombian Geological Survey, and Geological Survey of Brazil. Paris. https://doi.org/10.32685/10.143.2019.929​​


Español: 

Gómez, J., Schobbenhaus, C. & Montes, N.E., compiladores. 2019. Geological Map of South America 2019. Escala 1:5 000 000. Commission for the Geological Map of the World (CGMW), Servicio Geológico Colombiano, y Servicio Geológico de Brasil. París. https://doi.org/10.32685/10.143.2019.929​


3D map elaboration process​


The process of elaboration of 3D models is carried out with the software Blender 3D. This is a modeling tool that allows schematic representation through a set of objects and elements, shadows and textures added to an initial 3D surface generated with a DEM (GEBCO). The resulted work, once rendered, would become a 3D image, which will have a 90 STRM resolution.

 

STRM: Shuttle Radar Topography Mission​

General Bathymetric Chart of the Oceans​

DEM: Digital Elevation Model


Hengki PURWONEGORO graduated as a Forest engineer from the Institut Pertanian Bogor in 2005 and as a GIS and Remote Sensing Specialist from the PT. Sylva Prima Kaltim in 2012. He has extensive experience in map production, geospatial modeling, 3D maps, geospatial record-keeping, photogrammetry with drones, and database in ArcGIS. Currently, he works in the industrial forestry sector at Araya Bumi Indonesia Group. His main research interest is in individual tree detection using drone photogrammetry in plantation forests.​