Spatiotemporal tidy arrays for R

Hello,

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 https://github.com/r-spatial/stars, where you can also have a look at the proposal.

Best regards,
Matthias

Matthias

Matthias studied Environmental and Bio-Resources Management with a specialization in Environmental Information Management at the University of Natural Resources and Life Sciences (Vienna). He is currently a PhD student working at the Austrian Institute of Technology. Having written his master's thesis about extreme weather risk identification for the Austrian road network, he currently focuses on modeling of adverse weather events as a basis for risk assessment of road infrastructure networks.

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