Introduction to Spatial Data Analysis in R

Welcome to GEMS X003.1 Explicitly Accounting for Location in Agriculture: Introduction to Spatial Data Analyis in R. This course is designed for those who are interested in explicitly accounting for location in their analyses. Through this introductory course, you will learn how to work with spatial data in R, starting from importing different spatial datasets and creating simple maps, to conducting exploratory analysis. You will have the opportunity to immediately practice your new skills via hands-on exercises focused on agri-food applications throughout the 2-hour workshop.

This workshop is part of a 5-module series on working with and analyzing spatial agricultural data in R.

Prerequisites:

Introductory Knowledge of R & RStudio

Class Setup

1. Login to GEMS Platform at https://gems.agroinformatics.org/webui/#

   • GEMS Platform uses Globus to authenticate your account, so if your institution is already linked to Globus (for example, University of Minnesota and many other universities), you can search and select your institution from the list and use your institutional account to log into GEMS Platform. Alternatively, you can log in using Google or ORCID iD, or create your own Globus account to log in.

2. Once logged in, click Analyze > JupyterLab from the homepage

3. Open a bash terminal by clicking 'Terminal' icon in the Launcher OR by clicking File > New > Terminal

4. In bash terminal, create directories for this class

   mkdir classes  
   cd classes  
   mkdir GEMSX003  
   cd GEMSX003

5. Clone repository for this classes

   git clone https://github.com/y-chai/GEMS-Learning-R-Geospatial-Intro.git

Class and Exercises

In your JupyterLab environment, open the newly cloned directory GEMS-Learning-R-Geospatial-Intro and then open x003_Module1_Intro.ipynb to follow along for in-class exercises