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

Paula Moraga, Laurie Baker

Research output: Contribution to journalArticlepeer-review

Abstract

Spatial and spatio-temporal data are used in a wide range of fields including environmental, health and social disciplines. Several packages in the statistical software R have been recently developed as clients for various databases to meet the growing demands for easily accessible and reliable spatial data. While documentation on how to use many of these packages exist, there is an increasing need for a one stop repository for tutorials on this information. In this paper, we present rspatialdata a website that provides a collection of data sources and tutorials on downloading and visualising spatial data using R. The website includes a wide range of datasets including administrative boundaries of countries, Open Street Map data, population, temperature, vegetation, air pollution, and malaria data. The goal of the website is to equip researchers and communities with the tools to engage in spatial data analysis and visualisation so that they can address important local issues, such as estimating air pollution, quantifying disease burdens, and evaluating and monitoring the United Nation’s sustainable development goals.
Original languageEnglish (US)
Pages (from-to)770
JournalF1000Research
Volume11
DOIs
StatePublished - Jul 11 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-09-14
Acknowledgements: The author(s) declared that no grants were involved in supporting this work.

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)
  • Immunology and Microbiology(all)
  • Pharmacology, Toxicology and Pharmaceutics(all)

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