Note: This is an archived Handbook entry from 2016.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2016:Semester 2, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 48 hours (Lectures: 2 hours per week; Laboratory Exercises: 2 hours per week) |
Total Time Commitment:
|Recommended Background Knowledge:||None|
|Non Allowed Subjects:||None|
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
CoordinatorAssoc Prof Allison Kealy
Associate Professor Allison Kealy
In this subject students will learn about the range of computational techniques applicable to problems commonly arising in surveying and spatial information. This subject applies the mathematical and computational knowledge acquired in COMP20005 Engineering Computation; MAST10007 Linear Algebra (or its equivalent). The content of this subject is relevant to GEOM90033 Satellite Positioning Systems, and GEOM90039 Advanced Surveying and Mapping. The subject is of particular relevance to students wishing to establish a career in surveying engineering, mining, mapping, or spatial information in general, and is also relevant to a range of civil engineering disciplines where the capture and processing of spatial or survey measurements to meet a specific performance specification should be considered.
Least squares adjustment, survey measurement errors, survey network design and adjustment, coordinate systems, geodetic datum, datum transformations.
INTENDED LEARNING OUTCOMES (ILO)
On completion of this subject the student is expected to:
|Prescribed Texts:|| |
|Breadth Options:|| |
This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
LEARNING AND TEACHING METHODS
The subject is based principally on presentations by experienced industry professionals who present case studies in their area of expertise. Computer laboratory exercises are used reinforce the theory as well as to showcase the practical application of this material.
INDICATIVE KEY LEARNING RESOURCES
Lecture materials and notes will be provided via the LMS.
CAREERS / INDUSTRY LINKS
Presenters from the private land surveying industry will provide students with the material for this subject. Real world case studies will demonstrate the applicability of this material across the broader surveying and spatial industry.
Doctor of Philosophy - Engineering |
Master of Information Technology
Master of Philosophy - Engineering
MIT Spatial Specialisation |
Master of Engineering (Spatial)
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