Courses & Units

Environmental and Spatial Data Analysis KSM203


Environmental scientists increasingly need to deal with complex and large quantitative data sets collected from a variety of sources (i.e. remote sensing, moored instrumentation arrays and autonomous vehicles). As a result, computational and data analysis skills are highly desirable and useful across the many sub-disciplines of the environmental and marine sciences. This unit provides and introduction to processing, visualizing, and interpreting quantitative, spatial marine and environmental science data using scientific computing techniques.  Computation methods and visualizations will be performed using a variety of software and computing languages including MATLAB, ArcGIS and Python.


Unit name Environmental and Spatial Data Analysis
Unit code KSM203
Credit points 12.5
Faculty/School College of Sciences and Engineering
Institute for Marine & Antarctic Studies
Discipline Ecology and Biodiversity

Andrew Fischer

Level Intermediate
Available as student elective? Yes
Breadth Unit? No


This unit is currently unavailable.


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* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (see withdrawal dates explained for more information).

Unit census dates currently displaying for 2019 are indicative and subject to change. Finalised census dates for 2019 will be available from the 1st October 2018.

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Learning Outcomes

On completion of this unit students will be able to:

  1. Apply the basics of computer programming and mathematical principles relevant to marine science.
  2. Apply an understanding of data aggregation, processing and visualization to marine management.
  3. Construct custom tools that automate computation and visualization tasks.
  4. Apply computation skills in addressing a timely and relevant marine science question.



Band Field of Education
2 010799

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Teaching Pattern

Lecture - 120 minutes x weekly, Tutorial - 120 minutes x weekly


Tutorials and weekly lab reports (30%), exam 1 (15%), exam 2(15%). Final exam (40%)

TimetableView the lecture timetable | View the full unit timetable



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