Earth Proland
A C++/OpenGL library for the real-time realistic rendering of very large and detailed 3D natural scenes on GPU
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Proland is a research prototype, not an industrial quality software library. Its main purpose is to foster research on real-time and realistic rendering algorithms. It provides a framework and several predefined algorithms allowing researchers to develop new ideas, without having to redevelop a full rendering engine to show their results. It also provides a "reference" implementation for the research papers listed in publications.

However Proland can also be used for other goals than research, including Open Source or commercial projects (contact proland-licensing@inria.fr for all questions about commercial licenses), but WITHOUT ANY WARRANTY. In particular, Proland requires a graphics card compatible with OpenGL 3.x. Proland has only been tested on Windows and Linux, with specific NVidia graphics cards and OpenGL driver versions (e.g. NVidia GeForce 470 GTX, NVidia GeForce 260M GTX). IT MAY NOT WORK WITH ANY OTHER SYSTEM CONFIGURATION (in particular with ATI cards).

All contributions are welcome, and if you actively use or extend Proland, don't hesitate to let us know.

Source code

Proland source code:
  • Access to the git on Gitlab.

    Binaries and Demo

    A binary release is also available here. It contains precompiled DLLs for Windows, the libray header files, the developper documentation, as well as a precompiled demo application and several precompiled examples. These executables can be run directly after you have downloaded them, except for the Earth scenes, which also require you to download the associated Earth terrain data.

    Registration

    - Registration form.

    Documentation

    The Proland documentation can be browsed online here. Proland is based on Ork , whose documentation is available here.

    Terrain data

    The Earth scenes in the Proland demo require precomputed terrain data for the Earth, which is avaible at http://proland.inrialpes.fr/data/. In order to display these scenes, you must first download this huge data (more than 20 GB), with the same directory structure. The easiest way to do this is to use wget, with the following command (for optimal rendering performance, store this data on a SSD drive, if possible):

        wget -r -A .dat,.graph http://proland.inrialpes.fr/data/

    Then edit the init.bat file in the Proland demo to reference the folder where you downloaded this data.

    This data comes Blue Marble Next Generation, CIAT-CSI SRTM v4, Global Land Cover Facility AVHRR and ArcGIS, and is redistributed here in the Proland internal format with the permission of CIAT-CSI and GLCF (no authorization is required to redistribute the Blue Marble Data, and the world borders map from ArcGIS has a creative commons license).

    We reproduce here the disclaimer from the CIAT-CSI:
       
    PROCESSED SRTM DATA
    The data  distributed here  are in  ARC GRID,  ARC ASCII  and Geotiff format, in decimal degrees and datum WGS84.  They are derived from the USGS/NASA SRTM data.
    CIAT  have  processed  this  data  to  provide  seamless  continuous  topography surfaces.  Areas with  regions of no  data in the  original SRTM data  have been
    filled using interpolation methods described by Reuter et al. (2007).
     
    DISTRIBUTION
    Users are  prohibited from  any commercial,  non-free resale,  or redistribution without explicit written permission from CIAT. Users should acknowledge CIAT  as the source used  in the creation  of any reports,  publications, new data  sets, derived products, or services resulting from the use of this data set. CIAT also request  reprints of  any publications  and notification  of any  redistributing efforts. For commercial  access to  the data,  send requests  to Andy Jarvis.
     
    NO WARRANTY OR LIABILITY
    CIAT provides  these data  without any  warranty of  any kind whatsoever, either express or implied,  including warranties of  merchantability and fitness  for a particular purpose. CIAT shall not  be liable for incidental, consequential, or special damages arising out of the use of any data.
     
    ACKNOWLEDGMENT AND CITATION
     
     

    We kindly ask  any users to  cite this data  in any published  material produced using this data,  and if possible  link web pages  to the CIAT-CSI  SRTM website (http://srtm.csi.cgiar.org).

    Citations should be made as follows: Jarvis A., H.I. Reuter, A.  Nelson, E. Guevara, 2008, Hole-filled  seamless SRTM data V4, International  Centre for Tropical  Agriculture (CIAT), available  from
    http://srtm.csi.cgiar.org.

     
         
      REFERENCES
     
      Reuter  H.I,  A.  Nelson,  A.  Jarvis,  2007,  An  evaluation  of  void  filling interpolation  methods  for  SRTM  data,  International  Journal  of  Geographic Information Science, 21:9, 983-1008.  
         


    and from the Global Land Cover Facility:
    How to Cite This Data Set

    Citation Format: Author (Publication Date), Collection Name, Product Name, Processing Level, Publisher, Publisher Location, Product Coverage Date.

    Citation Parameters Example:

    • Author: Hansen, M., R. DeFries, J.R.G. Townshend, and R. Sohlberg
    • Publication Date: (1998)
    • Collection Name: UMD Global Land Cover Classification
    • Product Name: {specify 1 Degree, 8 Kilometer, or 1 Kilometer}
    • Version: 1.0
    • Publisher: Department of Geography, University of Maryland
    • Publisher Location: College Park, Maryland
    • Product Coverage Date: 1981-1994

    Full Example Citation: Hansen, M., R. DeFries, J.R.G. Townshend, and R. Sohlberg (1998), UMD Global Land Cover Classification, 1 Kilometer, 1.0, Department of Geography, University of Maryland, College Park, Maryland, 1981-1994.

    Associated Peer-Reviewed Publication: Hansen, M., R. DeFries, J.R.G. Townshend, and R. Sohlberg (2000), Global land cover classification at 1km resolution using a decision tree classifier, International Journal of Remote Sensing. 21: 1331-1365.

    Intellectual Property Rights

    University of Maryland; Department of Geography; use is free to all if acknowledgement is made. UMD holds ultimate copyright.

    Source

    Source for this data set is the Global Land Cover Facility, www.landcover.org.

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