Geospatial Data Science and Remote Sensing

Open-Source Spatial Analytics (R)


In this course, you will learn to work within the free and open-source R environment with a specific focus on working with and analyzing spatial data. We will cover a wide variety of data and spatial data analytics topics, and you will learn how to code in R along the way. The Introduction module provides more background info about the course and course set up. This course is designed for someone with some prior GIS knowledge. For example, you should know the basics of working with maps, map projections, and vector and raster data. You should be able to perform common spatial analysis tasks and make map layouts. If you do not have a GIS background, I would recommend checking out the West Virginia View Introduction to GIScience class. We do not assume that you have any prior experience with R or with coding. So, don't worry if you haven't developed these skill sets yet. That is a major goal in this course.

Background material will be provided using code examples, videos, and presentations. We have provided twenty assignments to offer hands-on learning opportunities. Data links for the lecture modules are provided within each module while data for the assignments are linked at the bottom of this page.

After completing this course you will be able to:


Using R for Data Analysis


Introduction

Set Up

R Language P1

Data Manipulation

Strings/Factors

A1: Data Manipulation

R Language P2

A2: Functions/Loops

Summary/Stats

A3: Summary/Stat

R Markdown

A4: R Markdown

ggplot2 P1

A5: Aesthetic Mappings

ggplot2 P2

A6: Graph Design

tables gt

A7: Tables


Spatial Analytics in R


Spatial Data

Maps tmap

A8: tmap

More Maps

Leaflet

A9: Leaflet

Vector Analysis

A10: Vector

Raster Analysis

A11: Raster

terra

A12: terra

LiDAR/Images

A13: dNBR


Machine Learning and Spatial Predictive Modeling


Machine Learning

Regression

A14: Fire Severity

A15: MLR

Random Forest

A16: Wetland Pred

caret

A17: caret Classification

A18: caret Regression

A19: caret Optimize

tidymodels

A20: Pulsars

Wrap Up


Data for Assignments


A1

A2

A3

A6

A8

A10

A11

A12

13

A14

A15

A16

17

A18

A19

A20