This workshop will give participants the tools to say farewell to ArcMap/QGIS and do their geospatial workflow entirely within R. We will begin with a general overview of GIS (Geographic Information Systems) data, the importance of GIS to wildlife management and conservation, and how R can improve your GIS efficiency. Then, we will use the R packages sp, raster, and rgeos to run through typical geospatial tasks, with time for individual exercises based on real-life wildlife data. Topics will include importing vector and raster data into R from a variety of sources (e.g. local directory, handheld GIS unit, online resources), subsetting data based on location or data attributes, reprojecting data to geographic and projected coordinate systems, creating new data (e.g. random or stratified random points, survey grids, buffers, minimum convex polygons, home ranges, centroids within polygons), merging and dissolving shapefiles, calculating geometry (e.g. area, perimeter), extracting values for points/lines/polygons from underlying covariate layers, and automating tasks via looping functions. We will employ a number of hands-on exercises, including, for example, extracting covariate information for buffers around camera traps in Honduras and generating random points for a Resource Selection Function using wildlife telemetry data. The workshop will close with some tips on cartography and creating high-impact maps in R, including use of ggmap. We expect some familiarity with GIS software and/or R, though this workshop will be targeted to a broad audience.
Organizers: Lisanne Petracca, State University of New York College of Environmental Science and Forestry, Syracuse, NY; Amanda Cheeseman, State University of New York College of Environmental Science and Forestry, Syracuse, NY
Supported by: Roosevelt Wild Life Station, SUNY-ESF