- Code ENGN3903
- Unit Value 6 units
- Offered by School of Engineering
- ANU College ANU College of Engineering and Computer Science
- Course subject Engineering
- Areas of interest Engineering, Environmental Science
- Academic career UGRD
- AsPr Marta Yebra
- Mode of delivery In Person
Second Semester 2022
See Future Offerings
In Sem 2 2022, this course is delivered on campus with adjustments for remote participation due to unavoidable COVID constraints.
To better understand and manage the rapid pace of environmental change, there is a need to develop accurate and effective environmental sensing, mapping and modelling techniques. In this course, students will learn about and compare the methods used to investigate environmental systems and parameters including techniques for measuring water, air, soil, vegetation, light, noise and vibration. Students will also learn about remote sensing from ground-, and space-based platforms, including how these platforms allow the collection of information essential to monitor, quantify and forecasting the condition and behaviour of the environment. Students will then investigate mapping tools to represent spatial and temporal changes of environmental values and develop computational methods and models to extrapolate societal understanding of the measured and mapped environmental data. Collectively, the topics explored in the course will give students experience in using spatiotemporal environmental data to underpin evidence based environmental decision making. This course will provide an important focus on indigenous perspectives and contributions to this field of study. Students will be able to draw on course materials that provide diverse gender, cultural, and geographical perspectives on these topics.
Upon successful completion, students will have the knowledge and skills to:
- Identify and evaluate appropriate monitoring and modelling strategies to characterise environmental systems and processes.
- Understand and explain the key principles and components of a remote sensing system.
- Understand and demonstrate how to collect, handle and analyse environmental data obtained from various measurement and remote sensing techniques.
- Demonstrate the application of environmental mapping and modelling techniques to investigate environmental systems and processes.
- Communicate informed critique or analysis of environmental sensing and modelling across a range of mediums.
Course will be offered from Semester 2, 2022 onwards.
- Workshop / lab exercises (25) [LO 1,2,4]
- Presentation (10) [LO 3,4,5]
- Assignment (25) [LO 1,2,3,5]
- Exam (40) [LO 1,2,3,5]
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130 hours per semester consisting of the following activities each week:
- Face-to face component which may consist of 2 x 1 hour lecture plus 1 x 2 hour workshop per week
- Approximately 80 hours of self-study which will include preparation for lectures and other assessment tasks.
- Field trip- Half day local trips discussing application with industry stakeholders?
Students are expected to actively participate and contribute towards discussions.
Information on inherent requirements for this course are currently not available
Requisite and Incompatibility
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
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Offerings, Dates and Class Summary Links
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Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|7338||25 Jul 2022||01 Aug 2022||31 Aug 2022||28 Oct 2022||In Person||N/A|