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Description

Would you like to leverage spatial data to start exploring the relationships of agricultural processes across geographies? This course is designed for those who are interested in explicitly accounting for location in their analyses. Through this 3-week 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 basic geocomputation on vector and raster data. In each 2.5 hour lecture, you will have the opportunity to immediately practice your new skills via hands-on exercises focused on agri-food applications.

Week 1: Introduction to spatial data and mapping in R
Week 2: Basic geocomputation with vector data in R
Week 3: Basic geocomputation with raster data in R 

The course will be delivered via a Jupyter Notebook hosted on the GEMS Informatics Platform. You do not need to have R or RStudio installed on your machine to participate.

Prerequisites: Introductory Knowledge of R

Outline

Week1: Introduction to spatial data and mapping in R
  • Introduction to the GEMS platform and Jupyter Notebook
  • Describe why spatial?
  • Importing point, polygon & raster data
  • Creating basic maps
  • Layering features in maps
Week 2: Basic geocomputation with vector data in R
  • Introduction to vector data
  • Attribute data operations
  • Spatial data operations
  • Geometry operations
Week 3: Basic geocomputation with raster data in R
  • Raster data in R
  • Raster manipulation
  • Spatial operations
  • Geometry operations
  • Raster-Vector interactions
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