GISC412-24S2 (C) Semester Two 2024

Spatial Data Science

15 points

Details:
Start Date: Monday, 15 July 2024
End Date: Sunday, 10 November 2024
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 28 July 2024
  • Without academic penalty (including no fee refund): Sunday, 29 September 2024

Description

This course introduces students to the field of spatial data science and is designed to develop students' understanding of some fundamental algorithms and code libraries that are used to manipulate, analyse, and map spatial data, and to explore how they are implemented in software. Students will use Python and Javascript programming languages. The course is largely lab and project based, with context and theoretical frameworks presented in lectures and tutorials in order to 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

GISC401 or COSC121 or COSC480 or equivalent

Timetable 2024

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 12:00 - 13:00 Psychology - Sociology 252 Lecture Theatre (15/7-29/7)
A5 Lecture Theatre (5/8)
F3 Lecture Theatre (12/8-19/8, 9/9-14/10)
15 Jul - 25 Aug
9 Sep - 20 Oct
Lecture B
Activity Day Time Location Weeks
01 Wednesday 13:00 - 14:00 Jack Erskine 242 (17/7)
John Britten 117 HP Seminar Room (24/7-21/8)
Jack Erskine 446 (11/9-16/10)
15 Jul - 25 Aug
9 Sep - 20 Oct
Computer Lab A
Activity Day Time Location Weeks
01 Wednesday 09:00 - 11:00 211A GIS Comp Lab
Ernest Rutherford 211
22 Jul - 25 Aug
9 Sep - 20 Oct
02 Friday 09:00 - 11:00 211A GIS Comp Lab
Ernest Rutherford 211
22 Jul - 25 Aug
9 Sep - 20 Oct
Optional A (Optional)
Activity Day Time Location Weeks
01 Wednesday 09:00 - 11:00 211A GIS Comp Lab
Ernest Rutherford 211
15 Jul - 21 Jul
02 Friday 09:00 - 11:00 211A GIS Comp Lab
Ernest Rutherford 211
15 Jul - 21 Jul

Timetable Note

There is a weekly lecture, seminar style discussion, and lab.

Course Coordinator

Carolynne Hultquist

Lecturer

Vanessa Bastos

Assessment

Assessment Due Date Percentage 
Lab Assignments 40%
Quizzes 20%
Final Project 40%

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: GISC401 or COSC121 or COSC480 or equivalent

Recommended preparation: Experience in Python is highly recommended. GISC401 is the preferred preparation course, as it provides a foundation for working with spatial data in Python.  Otherwise, preparation could involve COSC121 or COSC131 or COSC480, or an equivalent introductory programming course.

Indicative Fees

Domestic fee $1,145.00

* 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 .

All GISC412 Occurrences

  • GISC412-24S2 (C) Semester Two 2024