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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
8/29 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.
9/5 Labor day (no class) Read Introduction to R
9/12 Data Wrangling Data structures (vectors, matrices, data frames). Base graphics. Reading and writing data (from disk and internet). Practice homework submitted during class.
9/19 Data Wrangling 2 Filtering, selecting, joining data sets. Data gymnastics with dplyr. Homework #1
9/26 Graphics More base graphics (scatterplots, histograms). The grammar of graphics: ggplot2 and extensions (ggmap, rasterVis, etc.).
10/3 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
10/10 Spatial Raster I Working with gridded spatial data Project Proposal Due
10/17 Spatial Raster II Raster calculations, working with climate datasets. Homework # 3
10/24 Spatial Raster III A ‘mini’ project - looking at sea level rise in Bangladesh
10/31 Reproducible Research & Literate Programming RMarkdown to create dynamic research outputs. Publishing to github/word/html/etc.
11/7 Weather/Climate Data Processing Processing daily weather data from NOAA First draft of project for peer assessment
11/14 Satellite Data Processing Working with MODIS Satellite data Peer Evaluation Due
11/21 High Performance Computing & Software Integration Parallel processing and high performance computing in R, Calling other programs from within R. Homework # 4
11/28 Version Control Managing code with “version control”" using Github. Second draft of project Due 12/1 at midnight
12/5 Final Project Presentations 5 minute presentation of your final project
12/14 Final Project Due in UBLearns at midnight See Project description for more information


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