Download the Webinar Presentation & Replay: Finding Meaning in Points, Areas and Surfaces: Spatial Analysis in R

Everything happens somewhere and spatial analysis attempts to use location as an explanatory variable. Such analysis is made complex by the very many ways we habitually record spatial location, the complexity of spatial data structures, and the wide variety of possible domain-driven questions we might ask. One option is to develop and use software for specific types of spatial data, another is to use a purpose-built geographical information system (GIS), but determined work by R enthusiasts has resulted in a multiplicity of packages in the R environment that can also be used.

In this webinar, David will present three real-world examples of how spatial statistics are used, each illustrating the analysis of a particular class of spatial data (points, areas and surfaces) with a particular R package (spatstat, maptools, sp, spdep, gstat). He will show the flexibility and power that are gained when the R route is chosen. Join us to explore these uses of spatial data:

  • In geology, we attempt to answer the question ‘are the glacial hills called drumlins randomly distributed?
  • In epidemiology we ask the question ‘where is there an unusual incidence of a disease?
  • And in environmental science we ask ‘what is the value of this spatially continuous variable at this location?

David will also touch on other possibilities: there are packages for lines and network data, for image data, and for easy ‘mash ups onto GoogleMaps and Earth.

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