Workshop Schedule
22 April 2018
R and Spatial Data
This workshop provides an introduction to working with spatial data in R and doing exploratory spatial data analysis (ESDA). Examples of ESDA methods include lagged scatter plots, Moran scatter plots, and linked micromaps. We will briefly mention some R packages that have been specifically developed to meet the needs of monitoring and modeling aquatic resources, such as lakes, rivers, and streams. Lastly, we will show how R and ArcGIS software can be integrated. The objective of this workshop is to provide users with the fundamentals of reading, visualizing and analyzing spatial data in R.
Introductions and Workshop Logistics
- Pre-workshop software installation instructions
- Brief Introductions
- Why we each use R working with spatial data
- How R integrates with some example workflows
- Discuss Logistitcs
Lesson 1 - Spatial Objects and Libraries in R
- R primary spatial packages
- How spatial data is read into and structured in R
- Some introductory exploratory spatial data analysis examples using vector data
Lesson 2 - Working with simple features in R using sf package
- What are simple features?
- What is advantage of learning this package compared to using the
sppackage and object structure? - Some examples of reading data in with
sf, working with projections, simple analyses
Break
Lesson 3 - Exploring raster data in R
- Raster data packages and working with rasters in R
- Example raster data analyses in R
Lesson 5- Exploratory Spatial Analysis in R
Lesson 6- ArcGIS and R-ArcGIS Bridge (demonstration)
- Live demo of using the R - ArcGIS bridge