Course content is designed to be flexible to accommodate student interest and abilities. The order and timing of course topics may change as the semester progresses.

Date Title Description Assignment Package Presentation Group
8/31 Introduction & Overview Course Motivation & Objectives. Workflow & repeatable research in an era of big data for spatial environmental analysis. Getting started with the R Project for Statistical Computing & RStudio. Read Introduction to R
9/7 Data Wrangling Data structures (vectors, matrices, data frames). Base graphics. Reading and writing data (from disk and internet). Practice homework submitted during class.
9/14 Data Wrangling 2 Filtering, selecting, joining data sets. Data gymnastics with dplyr. Homework #1 due before class 1
9/21 Graphics More base graphics (scatterplots, histograms). The grammar of graphics: ggplot2 and extensions (ggmap, rasterVis, etc.). 2
9/28 Spatial Data Spatial Libraries: raster, sp, rgeos, rgdal. Integrating ‘traditional GIS’ analyses with statistical modelling. Data intersection (e.g. connecting points with polygons and rasters), overlays, zonal statistics Homework # 2 3
10/5 Spatial Raster I Working with gridded spatial data Project Proposal Due 10/10 4
10/12 Spatial Raster II A ‘mini’ project - looking at sea level rise in Bangladesh 5
10/19 Reproducible Research & Literate Programming RMarkdown to create dynamic research outputs. Publishing to github/word/html/etc. 6
10/26 Weather/Climate Data Processing Processing daily weather data from NOAA Homework # 3 7
11/2 Satellite Data Processing Working with MODIS Satellite data First draft of project for peer assessment 8
11/9 High Performance Computing & Software Integration Parallel processing and high performance computing in R, Calling other programs from within R. Peer Evaluation Due 9
11/16 Dynamic Visualization Homework # 4 10
11/23 Thanksgiving (no class)
11/30 Species Distribution Modeling Exploring spatial regression Second draft of project Due 12/1 at midnight
12/7 Final Project Presentations 5 minute presentation of your final project
12/8 Final Project Due in UBLearns See Project description for more information