OB1. The definition of a new environmental monitoring methodology based on real-time adaptive sampling of environmental variables. The points to be measured, by real-time sensors, will be established during the survey, to optimize accuracy and evaluate spatial uncertainty. That approach enhances the phenomena description by shrinking time resources and by reducing the sample number, making the procedure efficient and repeatable. This approach will be relevant when the sampling of high-frequency spatial information at a lower level of precision with immediate results is preferred over high precision measurement of a single or a limited number of samples delayed by laboratory requirements.

OB2. Representation of data uncertainty. Through the development of a theoretical and computational infrastructure, the research intends to address issues of geostatistics and mathematical, stochastic and geometric modelling for the representation and management of data affected by uncertainty to support informed decisions by operators in the field.

OB3. The reduction of the observation gap between data from short-scale remote sensing and in situ surveys, but also satellite-to-satellite, satellite-to-modelling, satellite-to spatial
databases. The results of adaptive monitoring (OB1) can be used to calibrate and validate remote sensing data or simulation/forecast models, bringing a rich insight into the environmental state of an area of interest. The issues of compliance with Open Data principles (e.g., Copernicus Programme European/Italian Geoportal) and of metadata quality through the adoption of recommendations provided by standards (W3C, FAIR, OGC, …) to facilitate the access and use of products and information will also be considered.