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A series of MATLAB learning modules to enhance numerical competency in applied marine sciences


Fischer, AM and Lucieer, V and Burke, C, A series of MATLAB learning modules to enhance numerical competency in applied marine sciences, American Geophysical Union Fall Meeting abstracts, 12-16 December 2016, San Francicso, USA, pp. ED51J-02. (2016) [Conference Extract]

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Enhanced numerical competency to navigate the massive data landscapes are critical skills students need to effectively explore, analyse and visualize complex patterns in high-dimensional data for addressing the complexity of many of the world’s problems. This is especially the case for interdisciplinary, undergraduate applied marine science programs, where students are required to demonstrate competency in methods and ideas across multiple disciplines. In response to this challenge, we have developed a series of repository-based data exploration, analysis and visualization modules in MATLAB for integration across various attending and online classes within the University of Tasmania. The primary focus of these modules is to teach students to collect, aggregate and interpret data from large on-line marine scientific data repositories to, 1) gain technical skills in discovering, accessing, managing and visualising large, numerous data sources, 2) interpret, analyse and design approaches to visualise these data, and 3) to address, through numerical approaches, complex, real-world problems, that the traditional scientific methods cannot address. All modules, implemented through a MATLAB live script, include a short recorded lecture to introduce the topic, a handout that gives an overview of the activities, an instructor’s manual with a detailed methodology and discussion points, a student assessment (quiz and level-specific challenge task), and a survey. The marine science themes addressed through these modules include biodiversity, habitat mapping, algal blooms and sea surface temperature change and utilize a series of marine science and oceanographic data portals. Through these modules students, with minimal experience in MATLAB or numerical methods are introduced to array indexing, concatenation, sorting, and reshaping, principal component analysis, spectral analysis and unsupervised classification within the context of oceanographic processes, marine geology and marine community ecology.

Item Details

Item Type:Conference Extract
Keywords:mapping, remote sensing
Research Division:Engineering
Research Group:Geomatic engineering
Research Field:Photogrammetry and remote sensing
Objective Division:Environmental Management
Objective Group:Terrestrial systems and management
Objective Field:Assessment and management of terrestrial ecosystems
UTAS Author:Fischer, AM (Dr Andy Fischer)
UTAS Author:Lucieer, V (Dr Vanessa Lucieer)
UTAS Author:Burke, C (Dr Chris Burke)
ID Code:113601
Year Published:2016
Deposited By:Ecology and Biodiversity
Deposited On:2017-01-09
Last Modified:2017-01-10

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