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Spatial Data Analytics (GEOM90006)
Graduate courseworkPoints: 12.5On Campus (Parkville)
To learn more, visit 2023 Course and subject delivery.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Jagannath Aryal
Overview
Availability | Semester 1 |
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Fees | Look up fees |
Much of the world’s data relates to processes and objects situated in space. Spatial data is a rich source of insights about patterns, processes, trends and behaviours in space and time. To tap into these insights, specialised statistical, analytical and computational techniques are required.
This subject exposes students to fundamental aspects of spatial analytics. Students are introduced to key techniques and principles for the analysis of point, area, and field data, covering concepts such as point pattern analysis, spatial autocorrelation and geostatistics. As part of putting these techniques and principles into practice, students learn computational thinking approaches and acquire technical software skills in a high-level scripting language (such as Python and R) that enable them to effectively address spatial data science problems across a variety of domains.
The subject partners with other subjects on spatial data management and visualisation and is of particular relevance to people wishing to establish a career in digital infrastructure, spatial information technology, or the quantitative environmental modelling or planning sectors.
The subject delivers underlying and cross-disciplinary concepts of geographic information science (GIS) and spatial analytics in managing environmental and infrastructure data, and the visual representation of spatial and temporal information. Relating these relevant concepts to applications through case study examples from various sectors such as digital infrastructure, spatial information technology, quantitative environmental modelling, urban sustainability, and planning. Defining and realizing a student-driven project employing a modern scripting language and spatial-temporal relationships of the observed data from real world.
Students will be provided with pointers and material to familiarise themselves with the tools used in this subject before the semester starts; this element of preparation is expected for successful participation in the subject. Advice will be provided on LMS.
Intended learning outcomes
On completion of this subject the student is expected to:
- Distinguish and characterise spatial patterns and processes captured in infrastructure and environmental data;
- Design and apply spatial analyses appropriate to given spatial processes, for example, urban sustainability and environmental management;
- Implement and test data structures and analysis procedures for spatial data in a transparent, collaborative, reusable and replicable manner;
- Interpret and critically evaluate a computational implementation of a spatial analysis project.
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 independently a project
- Ability to communicate effectively, with a team and with the community at large
- Ability to manage information and documentation
- Understanding of professional and ethical responsibilities, and commitment to them
- Capacity for lifelong learning and professional development.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
None
Corequisites
None
Non-allowed subjects
GEOM90042
Recommended background knowledge
Knowledge of geographic information systems (GIS) such as that gained by studying GEOM90008 or GEOM20013
Programming in a procedural programming language, preferably Python
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: 31 January 2024
Assessment
Description | Timing | Percentage |
---|---|---|
Documentation of a training experience by programming of a given task. (10 hours (Documented code - no word equivalent)). Intended Learning Outcomes (ILOs) 3 and 4 are addressed in this assessment.
| Week 4 | 0% |
Individual assessment of a spatial data analysis project. 30 hours (an equivalent of 1000 words). Intended Learning Outcomes (ILOs) 2 and 3 are addressed in this assessment.
| Weeks 6 and 9 | 25% |
Individual assessment of a spatial data analysis project. 30 hours (an equivalent of 1000 words). Intended Learning Outcomes (ILOs) 2 and 3 are addressed in this assessment.
| Weeks 6 and 9 | 25% |
Major spatial data analysis project requiring each team member to commit 40 hours (a contribution to the group report equivalent of 1500 words) of work for the group report, worth 40%. ILOS 1-4 are addressed in this assessment.
| During the examination period | 40% |
A 5-minute video presentation of the group project outcomes and the student's own contributions to the project, worth 10%. (20 Hours; a video equivalent of 500 words) ILOS 1-4 are addressed in this assessment.
| During the examination period | 10% |
Last updated: 31 January 2024
Dates & times
- Semester 1
Coordinator Jagannath Aryal Mode of delivery On Campus (Parkville) Contact hours Total time commitment 200 hours Teaching period 27 February 2023 to 28 May 2023 Last self-enrol date 10 March 2023 Census date 31 March 2023 Last date to withdraw without fail 5 May 2023 Assessment period ends 23 June 2023 Semester 1 contact information
Jagannath Aryal
Time commitment details
200 hours
What do these dates mean
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- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 31 January 2024
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 Ph.D.- Engineering Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Course Master of Digital Infrastructure Engineering Specialisation (formal) Spatial Major Energy Studies Major Tailored Specialisation Major Tailored Specialisation Major Energy Studies 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: 31 January 2024