Initial Publication Date: December 11, 2015


Concepts on this page were derived from participant presentations, discussions, and breakout groups at the 2015 Teaching Geoscience with MATLAB workshop and benefitted from the editing of Charly Bank, University of Toronto. This page has been expanded upon in Teaching Computation in the Sciences

Visualizations are used to represent and explain ideas and explore data. Using data visualization is a core skill in the geosciences, and there are multiple, important approaches that are commonly used across sub-disciplines. Within a particular course or activity the focus may be on the data visualization and interpretation itself, or on learning and practicing the computational skills needed to successfully and appropriately do data visualization. The purpose of a course will dictate the balance of coding versus data visualization and when is each emphasized and this should be explicit in the course design.

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Visualizations with MATLAB

MATLAB is a powerful tool for providing students capacity to visualize data from a wide variety of sources and understanding complex systems and for representing complex data. Students can visualize and manipulate data to SEE how the data behave. Students can also visualizing how to model fundamental Earth Science formulas, such as heat flow through oceanic lithosphere. In addition to the overarching benefits of MATLAB, MATLAB lends itself to this type of exploration and visualization through:

  • Very flexible and easily customized
  • Tuned for scientific data – raster and vector
  • Capable of displaying in a map

The MathWorks, MATLAB Plot Gallery provides examples of many of the ways data can be represented visually in the program.

Approaches to Getting Students Started

When providing pre-written code to students, they can get started right away with visualizing data. A scaffolded lab can provide students with the very basic skills needed to manipulate and explore the data (see the activity examples below).

  • Students can model responses of different scenarios (for example how a gravity anomaly of a sphere changes with depth to center of the sphere); they can compare such models to real data
  • MATLAB allows students to quickly produce profiles and scatterplots of collected data, overlay datapoints on drone/satellite/google images, grid data and plot the resulting maps as contours or shaded relief maps
  • Students can integrate visualization of their own data with simple models, and play with parameters to obtain match. This can be very powerful to understand which parameters may have the biggest effect on the model.
  • MATLAB GUI and stand-alone runtime approaches can be used for students to work with models without having to know MATLAB. This first step can also get students curious about programming.