- title: "Space-Time Data and Models" -- click here to submit an abstract
- ID: H114
- co-convener: Laureline Josset
The problem of estimating a variable at unobserved locations and/or times is important for many areas of research, including geosciences, civil-/ environmental engineering, soil sciences, agriculture, ecology, forestry, meteorology / climatology, oceanography, health / epidemiology.
The amount of data gathered is increasing (e.g., advances in measurement technologies, remote sensing, or citizen science). Challenges remain related to the interplay between heterogeneous measurements and improvements in models that can make use of the various types of data. This session aims to bring contributions together that demonstrate how to improve datasets and maximise their use through measurement techniques, statistics, and modelling, e.g., via
- innovative ways to measure data in the environment;
- the incorporation of innovatively measured data into modelling (usefulness, relevant scale);
- the inclusion of as much information as available to improve prediction (secondary / heterogeneous data, data on different scales);
- the consideration of the variability in the quality of the measurements;
Please find a pdf about the session here.