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Spatial and temporal thinking is important not just because everything happens at some places and at some time, but because knowing where and when things are happening is key to understanding how and why they happened or will happen. Spatial data science is concerned with the representation, modeling, and simulation of spatial processes, as well as with the publication, retrieval, reuse, integration, and analysis of such space- and place-centric data.
The Statistical analysis of spatial Data in Agro-Environmental research summer school (SDAE) aims to present statistical analysis of agro-environmental data at different scales, from catchment to regional scale.