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UseR! Workshop, Jul 9, 2019, Edzer Pebesma, Roger Bivand, Angela Li (helper)
This tutorial dives into some of the modern spatial and
spatiotemporal analysis packages available in R. It will show how
support, the spatial size of the area to which a data value refers,
plays a role in spatial analysis, and how this is handled in R. It
will show how package stars complements package sf for handling
spatial time series, raster data, raster time series, and more
complex multidimensional data such as dynamic origin-destination
matrices. It will also show how stars handles out-of- memory
datasets, with an example that uses Sentinel-2 satellite time
series. This will be connected to analysing the data with packages
that assume spatial processes as their modelling framework,
including gstat, spdep, and R-INLA. Familiarity with package sf
and the tidyverse will be helpful for taking this tutorial.
If you are having trouble installing these packages, you may need to update their geospatial library dependencies (GDAL, GEOS, PROJ.4, or UDUNITS). Please see this guide from Data Carpentry for more information on how to install these dependencies.
