R is perhaps the most powerful computer environment for data analysis that is currently available. R is both a computer language, that allows you to write instructions, and a program that responds to these instructions. R has core functionality to read and write files, manipulate and summarize data, run statistical tests and models, make fancy plots, and many more things like that. This core functionality is extended by hundreds of packages (plug-ins). Some of these packages provide more advanced generic functionality, others provide cutting-edge methods that are only used in highly specialized analysis such as geospatial computation.
Tim Appelhans joins me on the show today to talk about his journey from learning R too developing new packages and extending the geospatial visualization capabilities of R
This episode is sponsored by HiveMapper
A platform that takes video and creates 3D mapping layers based on that data. The video can be from avariety of different sensors, does not need to be vertically looking down on the geography and each 3D output is georeferenced!
For most people, when they think aboutthe relationship between GIS and COVID-19, the obvious solution is tracking data. At the highest level, if there is any spatial relationship between where we are in our societies, where we go, who we interact with, and spread the disease, our measurements, thenour policy tools must also have a geospatial component to capture that effect.It's not a question of whether spatial data and spatial analysis matter for COVID-19. The problem is understanding what tools exactly can be used for specific insights and decisions.