Geospatial Analysis with R

Lecturer:

Anto Aasa, PhD, senior research fellow
Mobility Lab
Department of Geography
University of Tartu

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The aim: This introductory course provides students with a diverse set of skills of spatial analysis in R environment. The aim for students is to understand and explore the benefits of using a non GUI approach for spatial analytics and statistics, based on the standard approaches in R & RStudio.

Learning outcomes:
After completing the course student

• knows basic concepts, skills, and tools for working with the R scripting environment;
• is familiar with set of of practical R libraries for everyday scientific and professional GIS use;
• is able to solve common data-related tasks using R in concrete GIS (Geographic Information System) projects;
• is competent of using spatial and non-spatial data in order to answer a research question;
• knows how to conduct and automate different standard GIS related tasks that support clear documentation of methods in the R scripting environment;

These lessons assume no prior knowledge of the skills or tools. It is a hands-on teaching course, so the majority of this course will be independent work in front of a computer and working on exercises.

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All the materials are available via course webpage: http://aasa.ut.ee/tbilisi/

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Schedule: April - May, 2020

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Additional reading:

• Intro to Geospatial Analysis in R
• Introduction to GIS with R by Jesse Sadler
  
• Short introduction to R
  
• Tutorial of the statistical analysis (and graphs) in R

If you are more interested:

• Book “Geocomputaion with R”
  
• GIS in R by Nick Eubank
  
• Simple Features for R

Lecture videos & slides:

1st lecture “Introduction to spatial analysis and GIS”

• Video
  
• Slides

2nd lecture “Notes before working with R”

• Video
• Slides

3rd lecture “Principles of scientific visualization”

• Video
• Slides
• Slides with animations (in video the animations are not working)

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Practical sessions:

1. Introduction to R
2. Data wrangling
3. Simple thematic maps
4. Physical map of Georgia & spatial queries
5. Mobile Data Collection Methods
6. Interactive plots & maps
7. Find and get the data

Passing the course:

To pass the course, students must

• solve independent practical task after every practical session based on previous materials. Results must be formatted as pdf-files and R-code. Independent works make up 70% of the grade.
• write short essay (30% of the grade). Topic and more detailed description will be available here on May 11th, 2020.

The essay

The title of final essay: “Spatial analysis in economic studies. Is it useful for me?”
During the last weeks you had short insight into the world of geospatial analysis. Hopefully you have seen, that “aerial view” can reveal new facets and patterns of specific phenomena. You have analysed the data from scratch, where the most time consuming part is searching, selecting, cleaning and tidying the data.
Please share your thoughts about geospatial analysis in economic studies and support it with real-life examples. What are benefits, shortcomings and challenges?
Please try to fit your essay on 4 pages.

Deadline for all the submissions is May 15th 2020.

The new deadline for all the submissions is May 20th 2020!!

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Author of tutorial & lecturer: Anto Aasa
in ISET, Tbilisi
Last update: 2020-05-11 13:31:51

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