Courses & Units

Geospatial Data Analytics KGG375

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 College of Sciences and Engineering
School of Geography, Planning, and Spatial Sciences
Discipline Geography, Planning, and Spatial Sciences
Coordinator Professor Arko Lucieer
Available as an elective? Yes
Delivered By University of Tasmania
Level Advanced

Availability

Location Study period Attendance options Available to
Hobart Semester 2 On-Campus International Domestic

Key

On-campus
Off-Campus
International students
Domestic students
Note

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Key Dates

Study Period Start date Census date WW date End date
Semester 2 22/7/2024 16/8/2024 9/9/2024 27/10/2024

* 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 2024 are indicative and subject to change. Finalised census dates for 2024 will be available from the 1st October 2023. Note census date cutoff is 11.59pm AEST (AEDT during October to March).

About Census Dates

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

Field of Education Commencing Student Contribution 1,3 Grandfathered Student Contribution 1,3 Approved Pathway Course Student Contribution 2,3 Domestic Full Fee 4
031101 $1,118.00 $1,118.00 not applicable $3,085.00

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.

If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.

Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.

Requisites

Prerequisites

KGG212

Teaching

Teaching Pattern

13 x 2-hr workshops, 13 x 3-hr practicals. Workshops and practical introductions will be recorded and made available on MyLO.

AssessmentAutomating 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%)
TimetableView the lecture timetable | View the full unit timetable

Textbooks

Required

Required readings will be listed in the unit outline prior to the start of classes.

Recommended

You will be working through Python tutorials provided by DataCamp: https://www.datacamp.com/ (access to these tutorials is provided during the unit)

LinksBooktopia textbook finder

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