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= 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 [http://www.openscenegraph.org/projects/VirtualPlanetBuilder VirtualPlanetBuilder].[[br]]
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 arcsec resolution: SRTM data (NASA)
  * Free global elevation data with 1 arcsec resolution but a lot of high frequency noise: ASTER Data (NASA)[[br]]
    Comparison SRTM vs. ASTER: https://arrowsmith.blog.asu.edu/2009/07/27/looking-at-the-new-aster-30-m-dems-not-so-impressive-relative-to-srtm-90-m/?triedWebauth=1
  * 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:
{{{
#!sh
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):
{{{
#!sh
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.
{{{
#!sh
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