Spatiotemporal tidy arrays for R


today I’d like to draw your attention to an upcoming, interesting R package for handling spatial data.

Following the successful release of the sf package, which simplifies and optimizes many aspects of handling spatial (vector) data in R by implementing simple features as native R data (alongside with many R convenience functions, such as support for pipe-based workflows, dplyr-style verbs and integration with ggplot), the R masterminds for geospatial data analysis around Edzer Pebesma are currently working on a new package related to the management and analysis of spatiotemporal arrays. The package will be called stars and is specifically targed to facilitate work with spatiotemporal data, coming in the form of dense arrays, with space and time being array dimensions.

The package is not intended to replace the very powerful raster package, but should be rather seen as a modern, efficient and convenient package featuring tidy, scalable and optimized (due to its implementation in C++) workflows for spatiotemporal arrays, thus also improving some of raster‘s functionality.

The project is currently under development, you can follow the progress on github at, where you can also have a look at the proposal.

Best regards,

About This Author

Matthias studied Environmental Information Management at the University of Natural Resources and Life Sciences Vienna and holds a PhD in environmental statistics. The focus of his thesis was on the statistical modelling of rare (extreme) events as a basis for vulnerability assessment of critical infrastructure. He is working at the Austrian national weather and geophysical service (ZAMG) and at the Institute of Mountain Risk Engineering at BOKU University. He currently focuses the (statistical) assessment of adverse weather events and natural hazards, and disaster risk reduction. His main interests are statistical modelling of environmental phenomena as well as open source tools for data science, geoinformation and remote sensing.

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