Please see below for examples/snapshots of current projects:

Spatial Algorithms

With GIS-based raster data (e.g. precipitation grids or elevation models) new information can be derived from existing data sets using mathematical algorithms. Raster-analysis is one of the major achievements of computer-based cartography. Geographical knowledge is not any more static on one map, but can be combined in ever-new variations with other map layers and made into new layers of information.

Maps that can result from a raster analysis are e.g. Isotope maps (calculated from climate and vegetation grids), landscape structure maps, but also statistical grids where a raster map is queried with another one (or a vector map).

Geo Processing

Interpolation (isarithmic maps)

Spatial interpolation is the step from discrete point data towards a comprehensive map. These maps, also known as Choropleth- or Isarithmic maps, are an important tool to generalize point measurements (eg precipitation, soil samples) into space. With today’s GIS technology, such procedures can be performed automatically. Particular known procedures are the triangulation, inverse distance weighting or kriging.

Current project: Isotope Database for WWF


Visibility Analysis

The planning and construction of large objects such as wind turbines increasingly requires measurements for nature and landscape protection. These are usually provided by environmental reports in terms of Pollution Control (Noise Pollution) and shadows-/ visibility analysis. The visibility analysis is a central part of the landscape assessments, that have increasingly to be carried out in sensitive landscape areas as part of the Environmental Impact Assessment (EIA).



Originally, a satellite or aerial image is in its raw format a representation of the earth’s 3-dimensional surface from a central perspective (the satellite- or airplane-camera). If the satellite-/aerial-image is to be used as a basis for topographical mapping or ground coordinate capturing, it has to be projected to a 2-dimensional surface. This is performed through “ortho-rectification”, where every pixel on the image will be assigned to its corresponding geographical coordinate on the earth. With the help of a digital elevation model and sensor information data of the satellite platform, these geographical coordinates for each image-pixel can be calculated with an ortho-rectification software. To improve the accuracy of the ortho-rectification, ground control points (GCP’s) that have to be collected in the field can be used to be implemented into the process.