GEOG324-25S2 (C) Semester Two 2025

Web GIS and Geoinformatics

15 points

Details:
Start Date: Monday, 14 July 2025
End Date: Sunday, 9 November 2025
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 27 July 2025
  • Without academic penalty (including no fee refund): Sunday, 28 September 2025

Description

This course develops skills in geospatial data science and is designed to form understanding of fundamental algorithms and code libraries that are used to manipulate, analyse, and map spatial data, and to explore how they are implemented. Students will use the Python programming language. The course is largely lab and project based, with context and theoretical frameworks presented in lectures while labs guide hands-on development.

This course focuses on expanding your geospatial data science skills, deepening your understanding of how analysis works and developing background knowledge of geospatial research.

Learning Outcomes

- Understand best practices to access, process, and visualise spatial data in Python Jupyter Notebooks

- Identify geospatial methods, packages, and tools to accomplish workflow tasks

- Gain programming literacy to understand and modify code in programming environments to meet your geospatial analysis needs

University Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attributes specified below:

Critically competent in a core academic discipline of their award

Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.

Employable, innovative and enterprising

Students will develop key skills and attributes sought by employers that can be used in a range of applications.

Globally aware

Students will comprehend the influence of global conditions on their discipline and will be competent in engaging with global and multi-cultural contexts.

Prerequisites

GISC101 (preferred) or GEOG205/DIGI205 or COSC121, or
equivalent. Recommended preparation: This course requires regular programming for spatial data so background skills in these areas are highly desirable.

Restrictions

Recommended Preparation

This course requires regular programming for spatial data so background skills in these areas are highly desirable.

Timetable 2025

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 11:00 - 12:00 F3 Lecture Theatre
14 Jul - 24 Aug
8 Sep - 19 Oct
Computer Lab A
Activity Day Time Location Weeks
01 Monday 13:00 - 15:00 Ernest Rutherford 211A GIS Comp Lab (14/7-18/8, 8/9-13/10)
Ernest Rutherford 211 GIS Comp Lab (14/7-18/8, 8/9-13/10)
 14 Jul - 24 Aug
8 Sep - 19 Oct
02 Thursday 12:00 - 14:00 211A GIS Comp Lab
Ernest Rutherford 211
14 Jul - 24 Aug
8 Sep - 19 Oct

Course Coordinator

Carolynne Hultquist

Lecturer

Vanessa Bastos

Textbooks / Resources

Recommended textbook(s):  
J. VanderPlas, Python Data Science Handbook: Essential Tools for Working with Data. (Second ed.) 2023.  

Python for Geospatial Data Analysis: Theory, Tools, and Practice for Location Intelligence Bonny Clain

Notes

Prerequisites: GISC101 (preferred) or GEOG205/DIGI205 or COSC121, or
equivalent.

Restrictions:GISC412

Recommended preparation: This course requires regular programming for spatial data so background skills in these areas are highly desirable.

Indicative Fees

Domestic fee $998.00

International fee $5,188.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see School of Earth and Environment on the departments and faculties page .

All GEOG324 Occurrences

  • GEOG324-25S2 (C) Semester Two 2025
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