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Documentation
- Getting Started
BuildEnvironment...
- Terrain Data
- Architecture
Modules...
osgVisual Configuration via XML...
- SerializationNotes
- ExecuterNotes
- CameraControl
- Theories of Terrain Deformation
- Theories of Image Distortion
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- Screenshots
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Projection Designer...
- Wiki Edit
- Website Credits/Impressum
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 arcsec resolution: SRTM data (NASA)
- Free global elevation data with 1 arcsec resolution but a lot of high frequency noise: ASTER Data (NASA)
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/Imagery/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)
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
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.