For the processing of geomatics data, artificial intelligence (AI) offers overwhelming opportunities. The integration of AI approaches in geomatics has developed into the concept of geospatial artificial intelligence (GeoAI), which is a new paradigm for geographic knowledge discovery and beyond. This contribution outlines AI-based techniques for analysing and interpreting complex geomatics data. How AI approaches have been exploited for the interpretation of geomatic data is explained.

Weather balloons are released every day around the world to obtain the latest atmospheric data for weather forecasting. Expanding the range of sensors they carry can make additional quantities available, such as for atmospheric turbulence, cloud electricity, energetic particles from space and, in emergency situations, volcanic ash or radioactivity. An adaptable system has been developed to provide these and other measurements, without interfering with the core weather data.

Global satellite navigation systems are commonly used for timing and synchronization of instrument platforms. These system clocks periodically roll over from limitations in discrete counter math. Due to the rarity of these events (19.6 years for GPS), special consideration must be given to designing instruments intended for use in hard-to-reach locations like the Antarctic Plateau. A few best practices are presented to prevent total system failure from unexpected subsystem faults.