Speakers
Description
R has become one of the most widely used languages for geographic data science. Its strength lies in a well-established ecosystem of several hundred spatial packages that support geographic data handling, analysis, and visualization, while integrating seamlessly with R’s wider tools for data processing and statistical analysis. R's flexibility and statistical capabilities make it attractive for researchers and practitioners working with geographic data across disciplines.
This hands-on tutorial introduces R's geospatial capabilities, building on the second edition of the book Geocomputation with R (https://r.geocompx.org/) by the tutorial instructors. We cover three core topics that provide a solid foundation for working with geographic data in R:
- Vector data with the sf package, implementing the simple features standard for representing points, lines, and polygons.
- Raster data with the terra package for gridded data such as remote sensing imagery and digital elevation models.
- Spatial data visualization using the tmap package for creating static and interactive maps.
In addition, time permitting, we include an additional applied topic (e.g., cloud-native geospatial workflows or Python interoperability).
Participants will learn to import, manipulate, and visualize geographic data through a mixture of presentations, live coding demonstrations, and interactive exercises. By the end of the tutorial, participants will have a practical understanding of how to work with spatial data in R and will be equipped with resources to continue learning and applying geocomputation techniques in their own work.
Additional Material or Paper
Please see the online version of our book under https://r.geocompx.org/
Prerequisites (only for tutorials)
Participants should have basic R knowledge. A laptop with Docker installed is recommended, as a pre-built Rocker image containing R, RStudio, and all required packages will be provided; alternatively, participants may use a local installation of R and RStudio/Positron/VSCode. Familiarity with the tidyverse is helpful but not required, and no prior experience with spatial data or GIS software is assumed.
Target audience (only for tutorials)
This course is aimed at researchers, data scientists, and practitioners who work with geographic or spatial data, as well as those who are interested in incorporating spatial analysis and visualization into their existing data science workflows across disciplines.
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Learning goals (only for tutorials)
Participants will learn to import, manipulate, and visualize geographic data through a mixture of presentations, live coding demonstrations, and interactive exercises. By the end of the tutorial, participants will have a practical understanding of how to work with spatial data in R and will be equipped with resources to continue learning and applying geocomputation techniques in their own work.
| Keywords: Please list up to 5 keywords to help us find the right session for your contribution. | geocomputation, spatial data, vector, raster, visualization |
|---|---|
| Virtual Option | This submission is for onsite presentation only |
| Video Recording | Video sharing is fine |
| The author(s) agree(s) to take responsibility and be accountable for the contents of the submission and is/are authorized to present it. | Confirm |
| Interested in serving as reviewer? | jannes@cynkra.com |