Introduction
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.
Summary
| Unit name | Geospatial Data Analytics |
| Unit code | KGG375 |
| Credit points | 12.5 |
| College/School | Sciences and Engineering School of Geography, Planning, and Spatial Sciences |
| Discipline | Geography, Planning, and Spatial Sciences |
| Coordinator | Doctor Mark Williams |
| Available as an elective? | Yes |
| Delivered By | University of Tasmania |
| Level | Advanced |
Sustainable Development Goals
The Unit Coordinator has identified that this unit aligns with the following UN Sustainable Development Goals. We welcome your thoughts and feedback on the alignment of the unit with these goals.
Availability
Specific information on 2027 unit availability will be available in August
Learning Outcomes
- 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.
Fee Information
2027 fee information will be available in August.
Requisites
Prerequisites
KGG212Teaching
| Teaching Pattern | 12 x 1-hr seminars (online only), 12 x 1-hr pre-recorded videos, 12 x 3-hr practicals (on campus with Zoom). Seminars and practical introductions will be recorded and made available on MyLO. |
|---|---|
| Assessment | Fundamentals of Python Programming for Geospatial Data Processing (20%)|Automating GIS Workflows with Python (40%)|GIS Project (40%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
You will be required to purchase a heavily discounted series of textbooks. https://leanpub.com/b/geopython/c/utas. You will work through parts of this textbook through practical sessions. |
|---|---|
| Recommended | You will be working through Python tutorials provided by DataCamp: https://www.datacamp.com/ (access to these tutorials is provided during the unit) |
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.