Terrain Data (DEM / Textures)

to use osgVisual, you need a terrain model to visualize. This model can be generated on thy fly (e.g. via osgEarth) or preprocessed with ​VirtualPlanetBuilder.
This page gives an overview how to obtain digital elevation model (DEM) data and texture data to build such a database.

The following source data could be used:

• Digital Elevation Data
  • Free global elevation data with 3 arcs resolution: SRTM data (NASA)
  • Free local high resolution elevation models: DEM data (www.viewfinderpanoramas.org)
• Textures/Orthophotos?
  • Free global low resolution texture data : Bluemarble Next Generation (NASA)
  • Free local low/medium resolution texture data: Landsat (NASA)
  • Commercial global medium/high resolution texture data: Landsat (atlogis.com, ...)
  • Commercial high resolution national texture data: e.g. Germany (Geocontent), USA (USGS), ...

SRTM-Data

SRTM data with 3 arcs are available for free at

• ​http://www.csi.cgiar.org/index.asp (american server, very slow)
• ​ftp://xftp.jrc.it/pub/srtmV4/ (european mirror, very fast)

Local high resolution DEM data (mainly based on SRTM)

• ​http://www.viewfinderpanoramas.org/dem3.html

Tip: Because SRTM data is delivery in many small .zip or tar.gz files, download and unpack it automatically:

wget -r ftp://xftp.jrc.it/pub/srtmV4/tiff/
for zipfile in *.zip;do unzip -o "$zipfile" -d unpacked; done

US texture data

Local High and global resolution Texture and DEM data

• ​http://edcsns17.cr.usgs.gov/EarthExplorer/
• ​http://glovis.usgs.com

To use LANDSAT arial images, read ​https://zulu.ssc.nasa.gov/mesid/tutorial/LandsatTutorial-V1.html for introduction. LANDSAT datasets are deliverey with up to seven images, each representing a different sensor with different wavelength. Three of this files (sensors for RGB) must be combined for the raw "natural" image.

The image merging is possible with gdal_merge.py (available in FWTools):

gdal_merge.py -o outfile.tif R_sensor.tif  G_sensor.tif B_sensor.tif

National high resolution data

National high resolution data is available from many companies. Germany: GeoContent

compress Data

To shift system load from HDD to CPU, compress all textures lossless with LZW. This will decrease rendering time a lot, because usually the HDD ist the bottleneck.

gdal_translate -co "COMPRESS=LZW" unsw ToDo

Moon Data

To animate earth rising above moon horizon, it could be usefull to model the moon.

​http://lunar.arc.nasa.gov/dataviz/datamaps/index.html