OpenSpat, spread the spatial wor(l)d

The availability of spatial data is increasing every year, with the growing access to free satellite imagery, to cheap drone cameras and the omnipresence of GPS on all sort of devices, from our phones to farm tractors. Many applications in agriculture and environmental sciences, which are often dealing with the organization of space and territories, can profit from those new sources of data, like precision farming, land-use use planning, environmental monitoring,etc.

Those information can be extracted, analysed and turned into models to support better decisions: apply the right amount of fertilizer at the right place in the field, predict the future extension of an urban zone, draw a map of the flooding or fire risks. But to do that, people need skills and tools to access, extract, explore and analyse such data.

That's why we started a project to design a lifelong learning course on spatial data analysis at the european level, with three partners (University of Liege, University of Lisboa and Montpellier SupAgro), based on free and open tools like *QGIS* and *R* so that everybody can install and use them, because knowledge access shouldn't be restricted to organizations which can afford costly licenses.

We will present the construction of the program and the pedagogical approach we'll use. Blended learning will be tested for a european master level course for adult learning.