GEOG 473/673: Advanced R for Spatial Analysis and Visualization

Online Meeting via Zoom – MW 9am-10am

Phase 1: Spatial Analysis & Visualization in R - 02/15/2021 - 04/16/2021 – 2cr

Phase 2: Machine Learning in R – 4/19/2021 to 5/18/2021 – 1cr

The objective of the Spring installment of GEOG 473/673 is to expand on the topics covered in the Fall version of GEOG 473/673 (Intro to R, sections 2-9 of this book). The course will be split into 2 phases. The first phase is a 2-credit course focused on using advanced tools within the R programming language (sections 10-16 of this book). The goal of this phase is for students to gain practical experience with challenging R topics that can be used for generating publication quality material. The second phase is a 1-credit course focused on introducing machine learning practices and implementing these via R (sections 17-19 of this book). Machine Learning is a growing practice in data science and can be useful for geospatial sciences. Students will apply R programming knowledge and gain confidence in machine learning techniques and application with R. This challenging, fast-paced course is intended for students that already have programming experience with R or Python.

Course Website:

https://jsimkins2.github.io/geog473-673/

Course Textbook:

https://jsimkins2.github.io/geog473-673/r-for-geospatial-sciences.html

Syllabus:

https://github.com/jsimkins2/geog473-673/blob/master/documents/spring_geog473_673_syllabus.pdf

Datasets:

https://github.com/jsimkins2/geog473-673/tree/master/datasets

GEOG 473/673: Course Notebooks

Advanced R - Phase 1 of GEOG 473/673: Course Notebooks

Welcome Video

https://youtu.be/H3GzOLGUP7A

Week 1 - Plot Customization

https://jsimkins2.github.io/geog473-673/plot-customization.html

Video Lecture: https://youtu.be/KQxzRCzikJU

Week 2 - Basic Statistics

https://jsimkins2.github.io/geog473-673/basic-statistics.html

Video Lecture: https://youtu.be/wEI0KApqWak

Week 3 - ggplot2 Tutorial

https://jsimkins2.github.io/geog473-673/plotting-with-ggplot2.html

Video Lecture: https://youtu.be/45SkenXgEJ8

Week 4 - Spatial ggplot2

https://jsimkins2.github.io/geog473-673/spatial-plots-with-ggplot2.html

Video Lecture: https://youtu.be/Ik36PeMZ3SY

Week 5 - Plotting Shapefiles

https://jsimkins2.github.io/geog473-673/shapefiles.html

Video Lecture: https://youtu.be/0Qt1vPcddss

Week 6 - Data Extraction

https://jsimkins2.github.io/geog473-673/remote-data-extraction.html

Video Lecture: https://youtu.be/CIp1q6l4uZ8

Week 7 - Functions and Presentations

https://jsimkins2.github.io/geog473-673/functions-and-code-presentation.html

Video Lecture: https://youtu.be/pY6CoNm5qwA

Weeks 8 & 9 - Advanced R Project

https://github.com/jsimkins2/geog473-673/blob/master/documents/AdvancedR_finalproject.pdf

Video Lecture: https://youtu.be/t8QfldJG_vM

Machine Learning in R - Phase 2 of GEOG473/673: Course Notebooks

Week 1 - Intro to Machine Learning

https://jsimkins2.github.io/geog473-673/machine-learning-with-r.html

Video Lecture: https://youtu.be/vj5Sc9Fz_b0

Weeks 2 & 3 - Time Series Forecasting

https://jsimkins2.github.io/geog473-673/time-series-forecasting.html

Video Lecture: https://youtu.be/mL5CVdmjZes

Weeks 4 & 5 - Random Forest Modeling

https://jsimkins2.github.io/geog473-673/random-forest-modeling.html

Video Lecture: https://youtu.be/Ptd2NXdtHl4