With AutoMap, the handling of satellite images has never been easier! We simplify the production of maps based on earth observation data and handle the application of machine learning algorithms for land surface classifications by providing a solid data processing pipeline in a fully managed cloud infrastructure. Bring your own samples or use our default solution, while we take care of the thousands of images that fit your request, all the clouds in your area of interest and every aspect of process optimization and secure data storage. Don't worry about machine learning concepts, intelligent training data collection, hyperparameter optimization or informative feature spaces - That's our job as well! Seeing the world from above is now as demanding as ordering a pizza!

Continous Snow Monitoring System is available as global 500 m resolution snow cover, regional 20 m resolution snow cover for various areas and 20 m resolution snow depth product for Switzerland, the Rocky Mountains and Sierra Nevada. All algorithms can be further extended to any regions of interest.

The complexity of modern urban environments has led to the introduction of 3D Land Information Systems (LISs), which tend to replace traditional 2D LIS architectures for the purposes of urban planning and regeneration, land administration, real estate management and civil development. Both the need for 3D visualization of the geometry of buildings in various time instances through the years and the need for acquisition of 3D models in various levels of detail (LoDs), which not only fulfill the requirements of the various users but also they speed up the visualization process, are obvious. Thus, additional dimensions, that is, for time and scale, need to be supported by a modern LIS. This service introduces a 5D modelling pipeline that may be adopted by a multi-purpose LIS for the selective creation of 3D models of an urban area in various time instances and at various LoDs, enriched with cadastral and other spatial data. The methodology is based on automatic change detection algorithms for spatial-temporal analysis of the spatial changes that took place in subsequent time periods, using image orientation, dense image matching and structure from motion algorithms, the procedure requires photogrammetric stereo plotting, implements procedural modelling and relies on the availability of overlapping aerial and terrestrial imagery, ground control points and cadastral information.

LCA stands for Land Cover Analysis and is used to provide an up to date, digital overview of what covers the surface of our earth split out into 10 key land cover classes. The LCA is often the first step in many environmental monitoring or site selection processes.