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Spatial Information Programming (GEOM90042)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Overview
Availability | Semester 1 |
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Fees | Look up fees |
AIMS
Many application problems in spatial information cannot be solved with standard tools but require programming for fast and effective solutions. Using case studies, this subject will enable students to develop software programs that address specific spatial information problems, beginning with learning the syntax, program structure and data types of an object oriented programming language such as Python. Course projects involve many aspects of the software development life cycle, from algorithm design to software implementation. This subject assumes students are familiar with spatial information data and the varied ways it is used by various stakeholders. Students who successfully complete this subject may find work in specialist consulting practices, spatial information research organisations or as software developers for the spatial information industry.
INDICATIVE CONTENT
- Variables and data types (including dictionaries)
- Input and output
- Selection and iteration
- Scripting and geo-processing (customise a GIS)
- Store and process spatial data
- Manipulate spatial data
- Visualise spatial data
- Access dynamically changing data from the Web.
Intended learning outcomes
INTENDED LEARNING OUTCOMES (ILO)
On completion of this subject the student is expected to:
- Design and generate an algorithmic solution to a specified spatial information problem
- Use an object oriented programming language to design, implement and test solutions
- Use dynamically changing web content in these solutions
- Document and maintain software programs.
Generic skills
The following generic skills will be strengthened as a result of this course of study:
- Ability to apply knowledge of science and engineering fundamentals
- Ability to undertake problem identification, formulation, and solution
- Ability to communicate effectively, with the engineering 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: 3 November 2022
Eligibility and requirements
Prerequisites
None
Corequisites
None
Non-allowed subjects
Students cannot enrol in and gain credit for this subject and:
GEOM30010 Programming Geomatics Applications
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
Additional details
- One 2-hour examination (60%) held in end of semester examination period. Intended Learning Outcomes (ILOs) 1 to 4 are addressed in this examination
- Two written programs and the relevant documentation to support the program (20% each, 40% in total) 3000 words equivalent, due mid-semester and end of semester, requiring approximately 50-55 hours of work in total. ILOs 1 to 4 are addressed in this assessment
Hurdle requirement:
- Students will be required to receive a passing mark for a 1-week assignment which will introduce into principles of GIS at the beginning of semester
- To pass this subject, students must obtain a pass in the examination.
Last updated: 3 November 2022
Dates & times
- Semester 1
Principal coordinator Martin Tomko Mode of delivery On Campus (Parkville) Contact hours 48 hours (Lectures: 2 hours per week; Tutorials/Practicals: 2 hours per week - tutorials and practicals in computer lab) Total time commitment 200 hours Teaching period 27 February 2017 to 28 May 2017 Last self-enrol date 10 March 2017 Census date 31 March 2017 Last date to withdraw without fail 5 May 2017 Assessment period ends 23 June 2017 Semester 1 contact information
Time commitment details
200 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
Recommended texts and other resources
- Jennings, N., 2011. A Python Primer for ArcGIS. CreateSpace Independent Publishing Platform
- Cogliati, J. 2005, Non-Programmer's Tutorial for Python
- Downey, A.B., Elkner, J. and Meyers, C., 2008. Think Python: How to Think Like a Computer Scientist. O’Reilly Media
- Mark Lutz: Learning Python (3rd ed.), O'Reilly Media
- van Rossum, G. and Drake, F.L. Jr. (Editor), 2003. The Python Language Reference Manual, (Version 3.2) Network Theory Ltd
- Beazley, D.M., 2006. Python Essential Reference (4th ed.), Addison-Wesley
- Subject notes
LEARNING AND TEACHING METHODS
There will be lectures covering the addressed topics. Additionally, there will be computer labs, which will allow students to apply previously learnt concepts, methods and approaches. Students will also have time to work on the practical assignments. Labs start in week 1 and then run until the end of the semester.
INDICATIVE KEY LEARNING RESOURCES
- Jennings, N., 2011. A Python Primer for ArcGIS, CreateSpace Independent Publishing Platform
- Cogliati, J., 2005, Non-Programmer's Tutorial for Python
- Downey, A.B., Elkner, J. and Meyers, C., 2008. Think Python: How to Think Like a Computer Scientist. O’Reilly Media
- Mark Lutz: Learning Python (3rd ed.). O'Reilly Media
- van Rossum, G. and Drake, F.L. Jr.(Editor), 2003. The Python Language Reference Manual, (Version 3.2) Network Theory Ltd
- Beazley, D.M., 2006. Python Essential Reference (4th ed.), Addison-Wesley
CAREERS / INDUSTRY LINKS
Spatial information services have grown into a major sector. Being able to combine a deep understanding of the fundamentals of spatial information with the ability to develop custom-made tools and analysis methods is a significant advantage in many areas of the spatial industry. Thus, successfully participating in this subject increases students’ attractiveness for employers and broadens their career opportunities.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Course Master of Spatial Information Science Course Master of Information Technology Course Master of Geographic Information Technology Course Master of Information Systems Course Ph.D.- Engineering Specialisation (formal) Spatial Major MIT Spatial 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