Compared with Other Tools

Terrain Viewer is a browser viewer for elevation data: nothing to install, data streamed from where it already lives, every view shareable as a link. That makes it quick for looking, comparing and sharing, and lighter than the tools below for heavy processing. When one of them is the better choice, it says so. Most of them also work well alongside it.

RVT, the Relief Visualization ToolboxCopy Anchor Link

RVT, from ZRC SAZU in Ljubljana, is the reference for relief visualization in archaeology. Sky-view factor, openness, the local relief model, multi-scale variants and the blended VAT recipes all have their reference implementation there, as a Python library and a QGIS plugin, and most of the papers on the Research References page either built it or used it.

Terrain Viewer implements several of the same visualizations after RVT's formulations. The difference is where and how they are computed. RVT processes a whole raster on your disk, at full resolution, the same way every time: the right tool for a figure in a paper or for systematically going through a survey. Terrain Viewer computes tile by tile in the browser, at the zoom being viewed, on data streamed from a national LiDAR service or a global model. There is nothing to download first, and you can change a radius and see the result immediately, compare two sources side by side, and send the view to a colleague as a link. RVT has more algorithms and blends; Terrain Viewer is quicker for finding where to look.

The two work together: find the area in Terrain Viewer, export the elevation as a GeoTIFF from Export and Share, and run RVT on that file.

QGISCopy Anchor Link

QGIS is a complete desktop GIS. It reads any format in any projection, chains GDAL, GRASS and SAGA through its processing toolbox, and lays out printed maps. For anything that is analysis rather than looking, QGIS is the tool.

What Terrain Viewer adds is the part before that: no project to set up, national LiDAR services and global models already in its library, relief modes that update as you pan, split views to compare sources or dates, and a link that restores the whole view. It suits the question "what is there, and which dataset shows it best?", for yourself or for someone who does not use GIS. Its GeoTIFF exports, in Web Mercator with real elevation values, open directly in QGIS when the work moves on.

Google EarthCopy Anchor Link

Google Earth is the best-known 3D globe: global imagery, photorealistic 3D cities, and in Earth Pro a timeline of historical imagery. Its terrain is for looking at, though. You cannot load your own elevation model, read a height at full precision, or restyle the relief.

Terrain Viewer works the other way round: elevation first, imagery as an optional layer. Its historical mode reads the same Google Earth historical imagery, next to ESRI Wayback and other archives, in split views by date. The Open In button sends the current view to Google Earth or Google Maps 3D when a photorealistic look is what you need.

CesiumCopy Anchor Link

CesiumJS is an open-source library for building 3D globe applications, and Cesium ion is the hosting platform behind it. It is built for 3D Tiles, photogrammetry meshes, point clouds and global terrain on a precise ellipsoid: a foundation for developers building their own application.

Terrain Viewer is an application, not a library, and it concentrates on what Cesium leaves to the developer: terrain analysis and relief visualization. It reads Cesium's quantized-mesh terrain format as one of its sources, swisstopo's Terrain 3D service among them. For 3D Tiles, meshes or a custom 3D application, Cesium is the right foundation.

OpenTopographyCopy Anchor Link

OpenTopography is where much high-resolution topography is published and processed: point clouds, on-demand DEMs and derivatives, global datasets through an API, and DOIs that make datasets citable.

Terrain Viewer complements it by displaying that data without downloading it. It reads OpenTopography's cloud-optimized rasters and VRT mosaics in the browser, including the Aguada Fénix and Haiti LiDAR surveys in its library. For the data itself, point-cloud processing or bulk downloads, go to OpenTopography.

OpenTopography also runs on-demand processing on its global rasters and lists community tools in its Tool Registry. One service has no equivalent here: Global Solar Irradiation, which computes for each pixel the monthly sum of global irradiation (beam, diffuse and reflected, in Wh/m²/day) and the monthly hours of sunlight on the DEM or DSM surface, with terrain shading, through GRASS's r.sun. Terrain Viewer's Sun Position tool and cast shadows show one moment; r.sun integrates a whole month. For a monthly irradiation map, use OpenTopography on a global raster, or r.sun in GRASS or QGIS on any DEM.

Other toolsCopy Anchor Link

Making your own DEM from stereo imageryCopy Anchor Link

Terrain Viewer displays elevation models; it does not produce them. When no LiDAR or national DEM covers a site, a surface model can be built from stereo satellite or aerial pairs. The NASA Ames Stereo Pipeline (ASP) is the open-source reference: command-line tools that turn stereo pairs from WorldView, Pléiades, SPOT, ASTER, declassified KH-9 frames or planetary orbiters into point clouds, DEMs and orthoimages, with bundle adjustment, co-registration and DEM differencing. The WorldView and Pléiades stereo models behind the library's Ridgecrest, Xinmo and Melamchi change sources are this kind of product. Geopera Parallax is a commercial neural stereo matcher that replaces ASP's dense-matching step and keeps the rest of the pipeline: trained on satellite pairs labelled with airborne LiDAR, it grids 30 to 80 cm imagery (WorldView-3, WorldView Legion, Gaofen-7, Beijing-3N) to 0.5 m surface models with fewer holes and noise than the classical matcher, by their benchmark. Either output loads into Terrain Viewer as a custom COG source, or as a difference source once two dates are co-registered.

Where the algorithms come fromCopy Anchor Link

Much here is ported rather than invented: slope and aspect follow GDAL's gdaldem (the Horn gradient), the relief visualizations follow RVT's formulations, Google Earth historical imagery follows GEHistoricalImagery, and the histogram matching of Compare and Blend comes from Iconem's historical-satellite. The full list is on Credits and Inspiration.