Analyzing and visualising spatial and spatiotemporal data cubes

Edzer Pebesma & Martijn Tennekes

Data cubes are a modern way to denote array data, and we focus on array data where some of the dimensions refer to space and time. Examples are spatial raster data, multivariate time series for multiple locations, and time series of raster images such as satellite data or weather predictions. In this workshop we will show a variety of cases where such data arise, and demonstrate how they can be analysed and visualised with R. While doing so, we mainly focus on using the R packages sf, stars, tmap and mapview, but also address a number of other useful packages for this context.

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Target Audience

R users, who are somewhat familiar with (or have a demand for learning about) spatial data handling in R, and who are interested in analysing and dealing with raster data and spatiotemporal data cubes.


Some familiarity with R and R-spatial, as well as some prior knowledge about time series and spatial data analysis is recommended, but is not a hard requirement.