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Spatial Analysis (GEOM90006)
Graduate courseworkPoints: 12.5On Campus (Parkville)
For information about the University’s phased return to campus and in-person activity in Winter and Semester 2, please refer to the on-campus subjects page.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Dr Jaganath Aryal
Please refer to the LMS for up-to-date subject information, including assessment and participation requirements, for subjects being offered in 2020.
Overview
Availability | Semester 2 |
---|---|
Fees | Look up fees |
AIMS
In this subject students will learn about the foundations of spatial data and their analysis. Emphasis will be placed on learning how to investigate the patterns that arise as a result of processes that may be operating in space. For example, students will learn to identify geographic clusters of disease cases, or hotspots of crime. A variety of scientific tools including probability theory, combinatorics, descriptive statistics, distributions and matrix algebra will be taught. Students will learn essential skills that are fundamental for all applications of geographic information.
The subject partners with other subjects on spatial data management and visualization, and is of particular relevance to people wishing to establish a career in the spatial information industry, the environmental or planning industry. Spatial Analysis builds on the fundamental knowledge of probability and statistics, mathematics, as well as computer literacy to write simple algorithms, and the preparation and management of data for sophisticated analysis software.
INDICATIVE CONTENT
Spatial autocorrelation, spatial data structures and algorithms, point patterns, measures of dispersion, measures of arrangements, line and network analysis, patterns of areas and in fields, and the role of spatial scale and spatial aggregation problems.
Intended learning outcomes
On completion of this subject the student is expected to:
- Describe and discuss data structures and analysis procedures to analyse spatial data
- Design and run a spatial analysis appropriate to a given phenomenon
- Distinguish and characterise patterns and processes in geographic space
- Apply GIS software for spatial analysis, and interpret the results.
Generic skills
On successful completion students should have the:
- Ability to apply knowledge of science and engineering fundamentals
- Ability to undertake problem identification, formulation, and solution
- Ability to conduct an engineering project
- Ability to communicate effectively, with the engineering team and with the community at large
- Ability to manage information and documentation
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Successful completion of the following is required to enrol in this subject:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
GEOM90008 | Foundations of Spatial Information |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Due to the impact of COVID-19, assessment may differ from that published in the Handbook. Students are reminded to check the subject assessment requirements published in the subject outline on the LMS
Description | Timing | Percentage |
---|---|---|
A 30 minute written mid-semester exam. Intended Learning Outcomes 1 to 3 are addressed in this examination
| Mid semester | 10% |
A written examination. ILOs 1 to 3 are addressed in this examination
| End of semester | 45% |
Four practical assignment reports of approximately 5 pages length each (500 words plus computer output) due evenly throughout the semester. ILO 4 is addressed in these reports.
| Throughout the teaching period | 45% |
Last updated: 3 November 2022
Dates & times
- Semester 2
Coordinator Jagannath Aryal Mode of delivery On Campus (Parkville) Contact hours 48 hours (Lectures: 2 hours per week; Laboratory Sessions: 2 hours per week) Total time commitment 200 hours Teaching period 3 August 2020 to 1 November 2020 Last self-enrol date 14 August 2020 Census date 21 September 2020 Last date to withdraw without fail 16 October 2020 Assessment period ends 27 November 2020 Semester 2 contact information
Dr Jaganath Aryal
Time commitment details
200 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
O'Sullivan, D. and Unwin, D.J. (2002). Geographic Information Analysis. Hoboken, NJ: John Wiley & Sons
- Subject notes
LEARNING AND TEACHING METHODS
The subject is based principally on presentations by academic lecturers. In addition each student prepares four practical assignment reports. A computer laboratory will be used by students to undertake the tutorials.
INDICATIVE KEY LEARNING RESOURCES
Major text book: O'Sullivan, D. and Unwin, D.J. (2002). Geographic Information Analysis. Hoboken, NJ: John Wiley & Sons
CAREERS / INDUSTRY LINKS
Spatial data analysis offers necessary skills to students to work in variety of disciplines such as geomatics, geography, economics, social science, the environmental sciences and statistics.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Data Science Course Doctor of Philosophy - Engineering Course Ph.D.- Engineering Course Master of Philosophy - Engineering Specialisation (formal) Spatial Specialisation (formal) Spatial Major Energy Studies Major Energy Studies Major Tailored Specialisation Major Tailored Specialisation Major Tailored Specialisation - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 3 November 2022