This project approaches raster terrain visualization by converting 2d data layers to a point cloud. While traditional terrain viewers often use triangle meshes, this implementation represents landscape as individual points, each carrying elevation and vegetation (NDVI) data.
The viewer addresses common performance challenges in terrain visualization through viewport-based filtering - only rendering points within the user's current view. This practical approach maintains smooth performance even with large datasets while providing a clear view of the landscape. Points are colored based on NDVI data and use elevation-based transparency, helping users identify relationships between terrain height and vegetation coverage.
Built with Python and OpenGL, the project users familiar mouse and keyboard controls for flyover interaction. This basic interface makes terrain data accessible for various applications, from educational use to preliminary site analysis, exploring the morphology of a region.