Geospatial Data Analytics is an innovative unit designed to provide you with foundational knowledge and practical skills in geospatial programming, building on the knowledge gained in KGG212 GIS: Spatial Analysis. With a primary focus on Python, a powerful and widely used programming/scripting language, this unit explores the latest tools and techniques in geospatial data processing and analysis, encompassing GIS and remote sensing applications. In this unit, you will engage with various Python libraries and frameworks specifically created for geospatial data manipulation, visualisation, and analytics. The unit fosters an understanding of custom GIS solution development, automation of geospatial workflows, and insightful analysis of geospatial data, enabling students to thrive as highly competent professionals in the spatial industry.
|Geospatial Data Analytics
|College of Sciences and Engineering
School of Geography, Planning, and Spatial Sciences
|Geography, Planning, and Spatial Sciences
|Professor Arko Lucieer
|Available as an elective?
|University of Tasmania
- International students
- Domestic students
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- Apply Python programming techniques to effectively manipulate, analyse, and visualise geospatial data, including GIS and remote sensing datasets.
- Automate geospatial workflows through Python scripting.
- Develop custom geospatial algorithms and tools using Python scripting for real-world spatial challenges.
- Justify coding choices to produce code that meets industry standard for coding style and documentation.
|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.
|Automating GIS Workflows with Python and QGIS (30%)|Fundamentals of Python Programming for Geospatial Data Processing (30%)|Developing Custom Spatial Algorithms in Python for Raster Operations (40%)
|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 to these tutorials is provided during the unit)
|Booktopia textbook finder
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