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Spatial Data Analytics and Geoprocessing (ERTH90060)
Graduate courseworkPoints: 6.25Not available in 2021
Please refer to the return to campus page for more information on these delivery modes and students who can enrol in each mode based on their location.
Overview
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This subject introduces the fundamentals of spatial data analytics and geoprocessing. By using hands-on exercises with real-life geological datasets, the students learn how to handle data in relational databases, query data with simple SQL statements, cleaning, formatting and exporting geospatial datasets and geo-processing the data in GIS software packages. At the start the subject will focus on looking at the basics of database structures, data analytics and data querying. In the second part of the course the students will create GIS projects, plot spatial data, start analysing and geoprocessing geospatial data, creating interpolated heatmaps, rasterizing point clouds and combining and standardizing disperse datasets. We will also practice data extraction, such as how-to geo-reference a map in Google Earth and in GIS, extract data locations from a geo-referenced image and how to create a final GIS project, including legend and map. Finally, the course concludes with bringing all the data together and creating a final GIS project visualizing all pre-analysed data.
Intended learning outcomes
At the completion of this subject, students should be able to:
- Critically examine and assess the feasibility of creating big data projects;
- Have an advanced understanding of how to analyse data in GIS and create own technical advanced projects;
- Gain unique skills in geoprocessing of spatial data and interpretation of the outcomes; and
- Gain insights into the potential of machine learning and artificial intelligence use in exploration workflows.
Generic skills
Upon completion of this subject, students should be able to:
- Handle large datasets in digital format;
- Exercise critical judgement;
- Undertake rigorous and independent thinking;
- Adopt a problem-solving approach to new and unfamiliar tasks;
- Develop high-level written report and/or oral presentation skills;
- Interrogate, synthesise and interpret the published literature; and
- Work as part of a team.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
None
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
Description | Timing | Percentage |
---|---|---|
Completion of a final data and GIS project based on provided dataset and individual tasks. The final mark will be assessed by means of a 15 – 20 min presentation by each student. | Due one week after the classroom teaching has concluded. | 50% |
Submission of a technical report (~2000 words) describing steps of data processing, GIS interpretations and final summary
| Due one week after the classroom teaching has concluded. | 50% |
Last updated: 3 November 2022
Dates & times
Not available in 2021
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Links to additional information
This subject is taught through the Victorian Institute of Earth and Planetary Sciences: https://vieps.earthsci.unimelb.edu.au/.
Last updated: 3 November 2022