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.

Continuous data of soil CO₂ efflux can improve model prediction of climate warming, and automated data are becoming increasingly available. However, aggregating chamber-based data to plot scale pose challenges. Therefore, we showed, using 1 year of half-hourly data, how using the lognormal assumption tackles several challenges. We propose that plot-scale SO₂ efflux observations should be reported together with lognormally based uncertainties and enter model constraining frameworks at log scale.

CÆLIS is a software system which aims at simplifying the management of a photometric ground-based network, providing tools by monitoring the instruments, processing the data in real time and offering the scientific community a new tool to work with the data. The present work describes the system architecture of CÆLIS and some examples of applications and data processing.

The paper demonstrates that isotopologue disequilibrium can be created in the SIMS ionization process, and that the specific conditions under which it is created during the oxygen bombardment of geological materials are consistent with known conditions where traditional interrelationships between ion abundances break down. Further study to determine the degree of radiation dosage at which extreme disequilibrium appears involved Raman and helium dating on a variety of well-characterized zircons.

Ecosystem-scale manipulation experiments are getting more complicated and require innovative approaches that help manage high volumes of in situ observations. New large-scale, well-designed, and reliable data acquisition and management systems will become common it the future. The presented approach shows an example of such a system that was built in a remote and harsh environmental location. The provided details can be used for the design of similar systems for other experiments in future.