Spatial Analysis in R

with a Focus on Environmental Health

Summer 2022 Workshop Course
University of Science and Technology Beijing


Edmund Seto
Associate Professor
Department of Environmental & Occupational Health Sciences
University of Washington

Lilian Liu
PhD Student
Department of Environmental & Occupational Health Sciences
University of Washington

Xioashi Chen
Graduate Student
University of Science & Technology Beijing

Course description

This is an introductory course in analyzing spatial data for environmental epidemiology. The course will describe common types of spatial datasets used in environmental epidemiology, including population census data, air pollution data, land use and land cover data, and data collected from mobile apps. Geographic Information System/Science (GIS) and spatial analysis methods for creating maps and for identifying spatial relationships will be described. Course modules will cover applications in air pollution, infectious disease, built environment, and environmental justice. The course will be taught using open source software, R and its packages for spatial analysis.


Students are expected to have access to a computer to attend video lectures and discussions, and for completing lab exercises in R. Students should have a basic understanding of epidemiology, environmental health, environmental engineering, and/or environmental sciences.

Learning objectives

By the end of the course, students should be able to:

  • Work with basic spatial data objects (points, lines, polygons, rasters)
  • Be familar with methods for accessing data from online services
  • Understand cartographic concepts of coordinate systems
  • Make both static and interactive maps from spatial data
  • Use R and its spatial packages to import, manipulate, analyze, and display spatial data
  • Describe applications of GIS and spatial analyses for environmental health

Not covered in this course

This is not intended to be an advanced course. So the course will not cover advanced statistical methods such as statistical testing, regression modeling, or geostatistical methods such as kriging.

Class Format

All instruction will occur online via video conference. Please see class email/messages for the link to video.

Each instructional day will consist of a first period of 45 minutes of lecture/discussion, followed by a 5 minute break, and then a second period of 45 online computer modules.

Students are encouraged to work together during class, ask questions, and participate in discussions and learning activities.

Online course modules are available here:


The assignments are for each student to share their thoughts, ideas, and comments over the concepts that we covered each week. There is no right or wrong answer and you will not get marked down for sharing your honest feedback. You are welcome to discuss the questions with your peers but limit your answers to your original work. Let’s work together and help each other learn better!

For each assignment, you will have approximately one week to complete (due every Sunday at 23:59 Beijing Time). Try to keep your answers concise. Group discussions are welcomed but make sure your answers are original. Submit your assignment answers using the online Assignments submission website, linked below in the Schedule.

Let us know anytime if you have questions or concerns. Potential delayed WeChat and email responses should be expected due to time differences. 


Students will be graded based on attendance to each online class period. All students are expected to attend all periods unless there is an emergency situation.

Instructors will provide weekly assignments. Students are expected to complete and submit the assignment to the instructors by the due date.

Students will receive full credit for the course based on their attendance and satisfactory completion of the assignments.

Schedule (Beijing Time)
Times are tentative and may change

July 6 . 9:00-10:35 am

Class 1. Course Introduction / Introduction to GIS

Module 1. Introduction to R

July 8 . 9:00-10:35 am

Class 2. Spatial Data

Module 2. Spatial packages for R

**Assignment 1 (week of July 4-10) – Due July 10 at 23:59 Beijing Time 
Submit assignment

July 11 . 9:00-10:35 am

Class 3. Cartography (Map-making) and Spatial Analysis

Module 3. Cartography concepts

July 13 . 9:00-10:35 am

Class 4. Global Positioning System (GPS) and Mobile Applications

Module 4. GPS and mobile app data

July 15 . 9:00-10:35 am

Class 4. Air pollution

Module 5. Air pollution

**Assignment 2 (week of July 11-17) – Due July 17 at 23:59 Beijing Time 
Submit assignment

July 18 . 9:00-10:35 am

Class 5. Infectious disease

Module 6. Infectious disease

July 20 . 9:00-10:35 am

Class 6. Built environment

Module 7. Built environment

July 22 . 9:00-10:35 am

Class 8. Environmental justice / Course Review

Module 8. Environmental justice

**Assignment 3 (week of July 18-22) – Due July 24 at 23:59 Beijing Time 
Submit assignment