spcanelon / geospatial-learning

Resources for learning geospatial analysis in R

Geospatial learning resources for biomedical applications

Resources related to geospatial analysis in (mostly) R. Most are applicable to any context, but some are geared more for biomedical applications.

• R package resources
• Spatial data visualization
• Spatial analysis
• Geocoding (offline)

R package resources

• CRAN Task View: Analysis of Spatial Data • Roger Bivand & Jakub Nowosad
• r-spatial.org • Edzer Pebesma, Marius Appel & Daniel Nüst: Website and blog for those interested in using R to analyse spatial or spatio-temporal data
• rspatial.org - Spatial Data Science with R — R Spatial: Materials that teach spatial data analysis and modeling with R using the raster and terra packages

Spatial data visualization

• Workshop (R/Medicine 2022): Using Public Data and Maps for Powerful Data Visualizations • Joy Payton
  • Video
  • Slides
  • Repo
• Talk (RStudio Conf 2022): Accelerating geospatial computing using Apache Arrow • Dewey Dunnington:
  • Video
  • Slides
  • Package (geoarrow)
• Course: Geospatial Workshop • The Carpentries
  • Introduction to Geospatial Concepts
  • Introduction to Geospatial Raster and Vector Data with R
• Course: GIS in R • Earth Lab
  • Shapefile Structure
  • Coordinate Reference System (CRS) and Spatial Projection
  • Projected vs Geographic Coordinate Reference Systems
  • Understand EPSG, WKT and other CRS definition styles
  • How to Reproject Vector Data in Different CRS
  • Making Interactive Maps with Leaflet Earth Lab • Earth Lab
• Course: Introduction to Spatial Data Science • Luc Anselin & Grant Morrison
  • Spatial Data Handling
  • Basic Mapping
• Tutorial: Space - Data Visualization • Andrew Wheiss
• Tutorial: Mapping Environmental Exposures • CHOP Arcus Education
• Tutorial: How to use open vector file formats in R: GeoPackage & GeoJSON • Floris Vanderhaeghe
• Tutorial: Astonishingly easy mapping in R with mapview - InfoWorld • Sharon Machlis (H/T Sharon Machlis)
• Workshop notes: R Spatial Workshop - Center for Spatial Data Science • Angela Li
  • Book of notes
• Book: Spatial Data Science • R Spatial
  • Spatial data with terra
• Book: Spatial Analysis with R • Chia Jung, Yeh
  • Shapefile
• Book: Geospatial Health Data • Paula Moraga
  • Coordinate reference systems
  • Shapefiles
  • Making maps with
• Book: Introduction to Spatial Data Programming with R • Michael Dorman
  • Vector layers
• Workshop (useR!2020): First steps in spatial handling and visualization • Sébastien Rochette, Dorris Scott & Jakub Nowosad
  • Repo
  • Video
• Workshop: Creating maps in R (sp package) • Robin Lovelace
  • Repo
• Site: Designing accessible maps
  • Maps & Geospatial: Accessibility Resources • Library Guides at Penn State University
• Package: Load US Census Boundary and Attribute Data as tidyverse and sf-Ready Data Frames • tidycensus (H/T Hansi Munasinghe)
• Tutorial(s): Blog | Milos Popovic - personal website and blog (H/T Milos Popovic)
• Workshop: Introduction to Geospatial Data in R - ResBaz 2021 • André Bellvé (H/T André Bellvé)

Spatial analysis

• Workshop (R/Medicine 2022): Analyzing Geospatial Data in R • Sherrie Xie
  • Video
  • Slides (pptx)
  • Repo
• Book: Geocomputation with R • Robin Lovelace, Jakub Nowosad & Jannes Muenchow (H/T Kjetil Haukås)
• Talk: Geocomputation with R’s guide to reproducible spatial data analysis • Jakub Nowosad
  • Slides
• Talk (RStudio Conf 2018): Tidy spatial data analysis • Edzer Pebezma
  • Video
  • Slides
• Webinar: Introduction to Geospatial Analysis in R - ORNL DAAC • Alison Boyer & Jessica Welch
  • Video
  • Slides
  • Repo
• Workshop (RStudio Conf 2020): Modern Geospatial Data Analysis • Zev Ross
  • Repo
• Book: Spatial data analysis • R Spatial
  • Spatial autocorrelation
  • Spatial interpolation techniques
  • Spatial distribution models
  • Spatial regression models
• Book: Geospatial Health Data • Paula Moraga
  • Spatial modeling of areal data
  • Spatio-temporal modeling of areal data
  • Geostatistical data
• Book: Intro to GIS and Spatial Analysis • Manuel Gimond
  • Point pattern analysis
  • Hypothesis testing
• Course: Applied Spatial Statistics in R • Yuri Zhukov
• Course: GIS in R • Earth Lab
  • Shapefile Structure
• Tutorials: The Center for Spatial Data Science
  • Univariate and bivariate analysis
  • Multivariate exploration
  • Rate mapping
  • Applications of spatial weights
  • Dimension reduction methods
  • Classic clustering methods
• Workshop notes: R Spatial Workshop - Center for Spatial Data Science • Angela Li
  • Book of notes
• Workshop: Introduction to Geographic Data Science • Francisco Rowe
  • Website
  • Repo
• Book: Spatial Modelling for Data Scientists • Francisco Rowe & Dani Arribas-Bel
• Book: [An Introduction to Spatial Data Analysis and Statistics: A Course in R • Antonio Paez (H/T Antonio Paez)
• Book: Public Policy Analytics: Code & Context for Data Science in Government • Ken Steif (H/T Matt Harris)
  • Book site
  • Repo w/ data
• Book: 16 Geospatial | Big Book of R • Oscar Baruffa (H/T Oscar Baruffa)
• Book: Bayesian inference with INLA • Virgilio Gómez-Rubio (H/T Jose Luis Cañadas)
• Course (OpenGeoHub Foundation): Analysing spatial data (ECS530 01) • Roger Bivand (H/T @datamaps)
  • Video playlist
  • Site

Geocoding (offline)

• Residential mobility¹
• R programming language
  • Decentralized and reproducible geocoding and characterization of community and environmental exposures for multisite studies² (H/T Zev Ross)
    • Video
  • DeGAUSS: Decentralized Geomarker Assessment for Multi-Site Studies³
    • Tool & instructions: https://degauss.org/
  • Challenges and solutions for private and reproducible environmental exposure assessment at scale
  • OpenStreetMap data to PostgreSQL converter: openstreetmap/osm2pgsql
• Geocoding Made Easy • tidygeocoder
  • Geocoding Services - Data Privacy • tidygeocoder
• ArcGIS software
  • What is geocoding?—ArcMap | Documentation
  • Geocode Addresses (Geocoding)—ArcGIS Pro | Documentation
  • R + ArcGIS
    • Leveraging ArcGIS World Geocoding Service in R
    • R-ArcGIS/r-bridge: Bridge library to connect ArcGIS and R, including arcgisbinding R library.
    • R-ArcGIS Bridge | Spatial Analysis in R & GIS for Spatiotemporal Data
    • R Notebooks in ArcGIS Pro for Spatial Data Science

Footnotes

1. J.R. Meeker, H. Burris, M.R. Boland, An algorithm to identify residential mobility from electronic health-record data, International Journal of Epidemiology. 50 (2021) 2048–2057. https://doi.org/10.1093/ije/dyab064. ↩

2. C. Brokamp, C. Wolfe, T. Lingren, J. Harley, P. Ryan, Decentralized and reproducible geocoding and characterization of community and environmental exposures for multisite studies, J Am Med Inform Assoc. 25 (2018) 309–314. https://doi.org/10.1093/jamia/ocx128. ↩

3. C. Brokamp, DeGAUSS: Decentralized Geomarker Assessment for Multi-Site Studies, JOSS. 3 (2018) 812. https://doi.org/10.21105/joss.00812. ↩