Geospatial analytics gathers, manipulates and displays geographic information system (GIS) data. Geospatial data analytics rely on geographic coordinates and specific identifiers such as street address and zip code. They are used to create geographic models and data visualizations for more accurate modeling and predictions of trends. Geospatial data analytics lets the eye recognize patterns like distance, proximity, contiguity and affiliation that are hidden in massive datasets. The visualization of spatial data also makes it easier to see how things are changing over time and where the change is most pronounced. Join this workshop series to discover how to implement geospatial analysis into your research through the R programming language. This session expands on the previous session by incorporating more advanced features for geospatial analysis in R. Familiarity in R is required. Feel free to bring your laptop with R installed so you can follow along.

Instructor: Kanika Khanna

Pre-requisites: Introductory R knowledge(Watch CCSS R recording here)