When: 03 - 07 October 2022 

The University of Melbourne, Parkville campus, School of Earth Sciences, Baragwanath Room (#204); on campus only.

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.


1. 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 teaching has concluded. 50% of final mark.

 2. Submission of a technical report (~2000 words) describing steps of data processing, GIS interpretations and final summary. Due one week after teaching has concluded. 50% of final mark.



Dr Fabian Kohlmann, kohlmann@unimelb.edu.au

Dated: Monday 30th May to 3rd June. 

Location: Room G42 (ground floor), Building 28, 9 Rainforrest Walk, Clayton campus

Time: Blended lectures and practical exercises from 9:30 am till 5 pm each day

11 April 2022: The course is now fully booked. Unfortunately, we cannot accept additional enrollments.

The abundance of digital spatial data coupled with the development of technologies like Geographical Information Systems (GIS) has changed the way in which information about spatial phenomena is collected, managed, analysed and depicted. A GIS is not simply a computer system for making maps; although it can readily and very effectively accomplish this. The main difference between a GIS and computer mapping or drafting systems is that a GIS enable analysis of complex spatial interrelationships that exist between phenomena in the real world as well as their non-spatial attributes. This allows us to go beyond making static digital maps from digital data, by providing a technology with the capacity to answer questions that relate to what objects are, where they occur, and how they relate to each other.

For example, a digital map can depict the magnitude and distribution of earthquakes relative to major faults and the earths topography. A GIS can also do this, and it can be used to answer questions about the various phenomena shown on the map. How many quakes of a chosen minimum magnitude occur within a specified area and specified time period? Is there a correlation between the density of quakes and faults in a particular orientation? What is the relationship between the topographic gradient and elevation within a chosen area? Are Cu anomalies in a sediment geochemistry survey correlated with a particular lithology, regolith type or structure, and if so, where do these phenomena occur together?

This course will introduce the concept of a GIS as a problem-solving technology within the geosciences, and through hands-on practical classes and lectures will provide the basic hands-on skills needed to design and implement a GIS project. Specific topics will include map projections and georeferencing, distortions in image data, raster and vector data models, incorporating digital terrain models and geophysical data, introduction to boolean logic and functions, data accuracy and access issues and limitations of GIS. The course will include an examination of case histories of GIS projects and students will also build a GIS project of their own to solve a simulated exploration problem using QGIS and real-world data sets.

If you have your own data for your research projects please bring it along to the course. We will schedule some time during the week to discuss and assist you with your own GIS projects.

Special Requirements: None; however basic computer skills and some knowledge of statistics would be an advantage. 

For further course and assessment information please contact Robin Armit

Cost: None!

University of Melbourne course information can be found at: https://handbook.unimelb.edu.au/subjects/geom90044