Spatial Data Visualisation using TMAP Visualise spatial data in R using the tmap package. Learn to create static and interactive maps, customise layouts, and publish high-quality visualisations.
https://www.prstats.org/course/spatial-data-visualisation-using-tmap-tmap02/ Duration: 5 Days, 5 hours per day Next Date: September 8 – 12, 2025 Format: Live Online Format Course Description R statistical software is becoming increasingly popular for spatial analysis and visualization—and for good reason. It is reproducible, flexible, and supported by a vast ecosystem of R packages dedicated to spatial data. An essential part of working with spatial data is visualization, not only for communication but also for exploration and analysis. This in-depth course focuses on the R package tmap, one of the most widely used packages for spatial data visualization. The course covers all key steps, from reading spatial data to publishing high-resolution static maps or interactive maps that can be embedded in web articles and dashboards. Participants will work with essential spatial data packages in particular sf, terra, and stars. The course also addresses key methodological aspects of spatial data visualization, including map projections, selecting the most appropriate visualization method for a given task, and choosing color schemes that account for accessibility and cultural considerations. Innovative spatial visualization techniques are also explored via several tmap extension packages, including cartograms, glyph-based visualizations, and 3d maps. During the course will cover the following: - Know how to use the core packages sf, terra, and stars to read and process spatial data in R, including joining data sources and performing geospatial data manipulations. - Be able to use tmap for exploring, analysing, and presenting spatial data. - Create various types of thematic maps. - Understand the methodological advantages and limitations of different map types, enabling informed decisions based on data characteristics and target users. - Recognize key considerations when selecting a suitable colour palette. - Be able to fine-tune map layouts in tmap, including adding map components, customizing legends, and incorporating map insets. - Know how to export maps in various static and interactive formats. - Learn how to use tmap extension packages. Please email oliverhoo...@prstatistics.com with any questions. Please book at this link https://www.prstats.org/course/spatial-data-visualisation-using-tmap-tmap02/ -- Oliver Hooker PhD. PR stats [[alternative HTML version deleted]] _______________________________________________ R-sig-Epi@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-epi
