[[TracNav(TracNav/TOC)]] = 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