This unit builds on KGG212 GIS: Spatial Analysis and focuses on advanced aspects of spatial data analysis, including practical aspects of programming for GIS customisation. At the start of semester you will spend one day in the field collecting GNSS data on a landslide near Hobart. This datasets is then used in the rest of the unit, starting with exploratory spatial data analysis (ESDA), interpolation techniques and terrain modelling, geostatistics, and error propagation modelling. The second part of the unit focuses on GIS application development using the Python programming language. These skills enable you to develop new algorithms and tools, automate tasks, and build custom GIS solutions. This unit will provide you with highly valued skills in the spatial industry.
|Unit name||GIS: Advanced Spatial Analysis|
|College/School||College of Sciences and Engineering
School of Geography, Planning, and Spatial Sciences
|Discipline||Geography, Planning, and Spatial Sciences|
|Coordinator||Doctor Steve Harwin|
|Available as an elective?||Yes|
|Delivered By||University of Tasmania|
This unit is currently unavailable.
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|Study Period||Start date||Census date||WW date||End date|
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2023 are indicative and subject to change. Finalised census dates for 2023 will be available from the 1st October 2022. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
- Apply techniques in GNSS data sampling, exploratory spatial data analysis, interpolation, and geostatistics to produce continuous raster surfaces from point sample data
- Create and document Python scripts that implement spatial data input/output methods, spatial data structures, and spatial analysis algorithms
- Operate geographic information system (GIS) software and implement Python code to solve complex problems and generate enhanced spatial information from vector, raster, and non-spatial datasets
- Document and evaluate a spatial analysis workflow (including coding) assisted by cartographic maps and other visual means to communicate analysis results
|Field of Education||Commencing Student Contribution 1,3||Grandfathered Student Contribution 1,3||Approved Pathway Course Student Contribution 2,3||Domestic Full Fee 4|
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
13 x 2-hr workshops, 13 x 3-hr practicals. Workshops and practical introductions will be recorded and made available on MyLO.
In week 2 there will be a Field Day at the Home Hill landslide.
|Assessment||Assignment 2: Introductory Python Exercises in QGIS (20%)|Assignment 1: Interpolation & Geostatistics (40%)|Assignment 3: Spatial data handling and analysis in Python (40%)|
|Timetable||View the lecture timetable | View the full unit timetable|
Required readings will be listed in the unit outline prior to the start of classes.
You will be working through Python tutorials provided by DataCamp: https://www.datacamp.com/ (access instructions will be provided)
|Links||Booktopia textbook finder|
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