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rspatialdata: a collection of data sources and tutorials on downloading and visualising spatial data using R.

Paula Moraga1, Laurie Baker2

  • 1Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.

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Summary

This study introduces rspatialdata, a website offering tutorials and diverse datasets for spatial data analysis in R. It aims to empower researchers and communities in addressing local environmental and health challenges using spatial visualization tools.

Keywords:
RSpatial datamapsopen datasustainable development goalsvisualization

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Area of Science:

  • Environmental Science
  • Public Health
  • Geographic Information Systems (GIS)

Background:

  • Spatial and spatio-temporal data are crucial across environmental, health, and social sciences.
  • The R statistical software has seen development of packages for accessing spatial databases.
  • A centralized resource for tutorials on using these spatial data packages is needed.

Purpose of the Study:

  • To present rspatialdata, a website consolidating spatial data sources and R tutorials.
  • To facilitate easy downloading and visualization of spatial data.
  • To support research and community engagement in spatial data analysis.

Main Methods:

  • Development of the rspatialdata website.
  • Curating a diverse range of spatial datasets (e.g., administrative boundaries, OpenStreetMap, population, environmental, health data).
  • Providing tutorials for spatial data analysis and visualization using R.

Main Results:

  • The rspatialdata website is now available.
  • It offers access to multiple datasets and practical guidance.
  • Users can learn to perform spatial analysis and visualization in R.

Conclusions:

  • rspatialdata serves as a valuable, accessible resource for spatial data.
  • It equips researchers and communities with tools for local issue analysis.
  • The platform supports efforts towards sustainable development goals through data-driven insights.