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Tutorials Using the R Programming Language

Tutorials on this page use the R programming language.

2016

Overview: Quantifying The Drivers and Impacts of Natural Disturbance Events – The 2013 Colorado Floods

This lesson demonstrates ways that scientists identify and use data that they use to study disturbance events. Further, it encourages students to think about why we need to quantify change and different types of data needed to quantify the change. This lesson focuses on flooding as a natural disturbance event with impacts on the local human populations. Specifically, it focuses on the causes and impacts of flooding that occurred in 2013 throughout Colorado with an emphasis on Boulder County.

Quantifying The Drivers and Impacts of Natural Disturbance Events – The 2013 Colorado Floods

This lesson demonstrates ways that scientists identify and use data that they use to study disturbance events. Further, it encourages students to think about why we need to quantify change and different types of data needed to quantify the change. This lesson focuses on flooding as a natural disturbance event with impacts on the local human populations. Specifically, it focuses on the causes and impacts of flooding that occurred in 2013 throughout Colorado with an emphasis on Boulder county.

2015

Raster 00: Intro to Raster Data in R

This tutorial reviews the fundamental principles, packages and metadata/raster attributes that are needed to work with raster data in R. It covers the three core metadata elements that we need to understand to work with rasters in R: CRS, Extent and Resolution. It also explores missing and bad data values as stored in a raster and how R handles these elements. Finally, it introduces the GeoTiff file format.

Raster 03: Raster Calculations in R - Subtract One Raster from Another and Extract Pixel Values For Defined Locations

This tutorial covers how to subtract one raster from another using efficient methods - the overlay function compared to basic subtraction. We also cover how to extract pixel values from a set of locations - for example a buffer region around plot locations at a field site. Finally, it explains the basic principles of writing functions in R.

2014