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Data management and introduction to QGIS and RStudio for spatial analysis

By Meghan Graham MacLean

University of Massachusetts Amherst

Students learn about the importance of good data management and begin to explore QGIS and RStudio for spatial analysis purposes. Students will explore National Land Cover Database raster data and made-up vector point data on both platforms.

Listed in Datasets | resource by group ESA Data Access - Inclusive Pedagogy

Version 1.0 - published on 22 May 2020 doi:10.25334/48G8-6Y44 - cite this

Licensed under CC Attribution 4.0 International according to these terms

Adapted from: Data Management using National Ecological Observatory Network's (NEON) Small Mammal Data with Accompanying Lesson on Mark Recapture Analysis v 2.1

NLCD_sNE.PNG

Description

Overview

This module covers the importance of good data management as well as is a quick refresh or introduction to GIS and R and RStudio for spatial analysis.  Students will open and visualize a a piece of the 2016 National Land Cover Database raster in QGIS and RStudio along with vector point data and explore properties of each within QGIS and RStudio (given a working script).  They will also estimate the most abundant land cover type in Hampshire County, MA*.  This module is designed to be completed in a team-based learning approach that pairs students with different expertise, and includes supplementary information for students to self-identify as needing additional training in either QGIS or RStudio, althouth the tasks in each are relatively straight forward for a beginning user.  The module also include bonus challenges for students with a bit more experience with either platform.

Connection to other modules

I connected this module with the NEON Data TIEE module presentation published in 2016 by Jim McNeil1 and Megan Jones2 that can be found here to relay the importance of metadata and data organization. I, however, did not use their mark-recapture data and instead used the opportunity to build on this lesson and introduce spatial data and data manipulation in R and GIS.

1 - Smithsonian-Mason School of Conservation, George Mason University, Smithsonian Conservation Biology Institute, Front Royal, VA, 22630

2 - National Ecological Observatory Network – Battelle, Boulder, CO 80301, Corresponding Author: Megan A. Jones (mjones01@battelleecology.org)

Learning objectives

By the end of the module, students should be able to:

  • gain familiarity with land cover
  • gain familiarity with QGIS and RStudio
  • understand land cover types and quantify area of each type
  • create and modify metadata files

Data and code included

  • National Land Cover Database in Massachusetts (or your state of choice) - MA_NLCD.tif*
  • Shapefile of unlabelled points for the students to figure out - points.shp*
  • Code: Raster-explorer.Rmd

*Note: I highly recommend personalizing this module to your area - especially if you are planning to do more with spatial data in your region.  This makes the land cover maps much more accessible to students if they have some real life experience with the landscape.  You can download data from www.mrlc.gov or the state GIS database (if available).

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ESA Data Access - Inclusive Pedagogy

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