Course coordinator
Dr David Pullar
Please contact me by email to arrange a time for consultation by Zoom or in person.
Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- The Environment School
This course develops computing skills in Geographical Information Systems for processing tasks and web mapping. It includes: i) basic skills in programming with the Python scripting language to automate GIS processing tasks and to develop analysis tools, and ii) interactive web mapping and apps for publishing on the Internet. The course provides a highly desired industry competency for GIS analysts.
Geographical information is best utilized when it is managed as a shared resource on the web. The course adopts a spatial data science approach to extract useful information from data forﾠurban and environmental applications. Students learn: i) principles for organising geospatial data and its subsequent exploration, visualisation and analysis, and ii) online accessﾠand publishing geospatial dataﾠto create engaging webmaps. You gain skills to combine data science tools, such as Python programming and web notebooks, with popular online GIS software packages such as ArcGIS, Google and open source GIS.
All the teaching resources are online and the course only requires reliable Internet access. Learning resources include lecture presentations (recorded on zoom), practical instructions to demonstrate exercises (recorded on Zoom), quizzes, links to web resources, facilitated discussion boards, etc. Students get the most out of this course when they reinforce lectures and practicals with self-study.
Course requirements
Assumed background
Note that a recommended pre-requisite is Theory & Practice in Science (SCIE1000) which introduces students to a broad range of computational concepts and tools; including computer programming (using theﾠPython language). While programming is not a deeply theoretical endeavour or difficult to do, it does require working with data and looking at problems in a logical way. Details will matter, and also ability to think abstractly at different levels about geographical information and its representation.ﾠSo the main background required is that students have worked with data and analysis methods (either GIS, statistics or programming).
Prerequisites
You'll need to complete the following courses before enrolling in this one:
GEOM2001 or GEOM2002, (SCIE1000 from 2020)
Recommended prerequisites
We recommend completing the following courses before enrolling in this one:
SCIE1000
Incompatible
You can't enrol in this course if you've already completed the following:
GEOM7004
Jointly taught details
This course is jointly-taught with:
- GEOM7004
All activities are same, however assessment there are difference in assessment performance for undergraduates and postgraduates.
Course contact
Course staff
Lecturer
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
To provide skills and knowledge on automating geospatial processing tasks and web mapping.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Explore geographical concepts with geospatial computation
LO2.
Use Python programming to do computer tasks
LO3.
Automate geoprocessing tasks for GIS/RS applications
LO4.
Appreciate use of integrated geospatial data by society
LO5.
Appreciate how the web works for information communication and delivering GIS services
LO6.
Appreciate future directions in geospatial technology
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Computer Code, Quiz, Tutorial/ Problem Set |
Geospatial data processing
|
30% |
Quiz is automatically marked, followed by submitting Python notebook file that is manually marked. 13/08/2024 - 21/08/2024 |
| Computer Code, Quiz, Tutorial/ Problem Set |
Geospatial data handling
|
30% |
Quiz is automatically marked, followed by submitting Python notebook file that is manually marked. 10/09/2024 - 18/09/2024 |
| Computer Code, Paper/ Report/ Annotation, Project, Quiz |
Geospatial project and web mapping
|
40% |
Quiz and report manually marked, followed by submitting Python notebook file that is manually marked. 19/09/2024 - 18/10/2024 |
Assessment details
Geospatial data processing
- Online
- Mode
- Written
- Category
- Computer Code, Quiz, Tutorial/ Problem Set
- Weight
- 30%
- Due date
Quiz is automatically marked, followed by submitting Python notebook file that is manually marked. 13/08/2024 - 21/08/2024
Task description
Practical exercises that build skills and confidence in geospatial processing and computation. Covers weeks 1-4.
i) Quiz questions related to weekly lectures and readings. Marked on correct answer.
ii) Geoprocessing exercises related to practicals completed in a Python notebook file which is uploaded. Marked on criteria for programming practice and worked example.
Submission guidelines
To be submitted via Blackboard
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Geospatial data handling
- Online
- Mode
- Written
- Category
- Computer Code, Quiz, Tutorial/ Problem Set
- Weight
- 30%
- Due date
Quiz is automatically marked, followed by submitting Python notebook file that is manually marked. 10/09/2024 - 18/09/2024
Task description
Practical exercises that build skills and confidence in solving geographical problems using geospatial data and analysis. Covers weeks 5-8.
i) Quiz questions related to weekly lectures and readings. Marked on correct answer.
ii) Geoprocessing exercises related to practicals completed in a Python notebook file which is uploaded. Marked on criteria for programming practice and worked example.
Submission guidelines
To be submitted via Blackboard
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Geospatial project and web mapping
- Online
- Mode
- Written
- Category
- Computer Code, Paper/ Report/ Annotation, Project, Quiz
- Weight
- 40%
- Due date
Quiz and report manually marked, followed by submitting Python notebook file that is manually marked. 19/09/2024 - 18/10/2024
Task description
Practical exercise on web mapping and small project to solve a geographical inquiry-driven problem using geospatial data and analysis.
i) Quiz questions related to weekly lectures and readings on web cartography. Marked on correct answer.
ii) Lab report on development of a multiscale web map. Marked on criteria for short answer and worked example.
iii) Small project for a geographical problem with options for a human or environmental focus, and expectation that students select a specific issue following an inquiry-driven investigation. The small project is submitted as report following IMRaD structure and is accompanied with Python notebook file with worked analysis. Marked on criteria for structured answer, programming practice, and worked example.
Submission guidelines
To be submitted via Blackboard
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Description |
|---|---|
| 1 (Low Fail) |
Absence of evidence of achievement of course learning outcomes. Course grade description: The minimum percentage required for this grade is: 0% |
| 2 (Fail) |
Minimal evidence of achievement of course learning outcomes. Course grade description: The minimum percentage required for this grade is: 30% |
| 3 (Marginal Fail) |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: The minimum percentage required for this grade is: 45% ASSESSMENT HURDLE - see 'Other Requirements and Comments' below. |
| 4 (Pass) |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: The minimum percentage required for this grade is: 50% ASSESSMENT HURDLE - see 'Other Requirements and Comments' below. |
| 5 (Credit) |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: The minimum percentage required for this grade is: 65% ASSESSMENT HURDLE - see 'Other Requirements and Comments' below. |
| 6 (Distinction) |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: The minimum percentage required for this grade is: 75% ASSESSMENT HURDLE - see 'Other Requirements and Comments' below. |
| 7 (High Distinction) |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: The minimum percentage required for this grade is: 85% ASSESSMENT HURDLE - see 'Other Requirements and Comments' below. |
Additional course grading information
The final grade for the course will typically fall within the above mentioned ranges.
Supplementary assessment
Supplementary assessment is available for this course.
Should you fail a course with a grade of 3, you may be eligible for supplementary assessment. Refer to my.UQ for information on supplementary assessment and how to apply.
Supplementary assessment provides an additional opportunity to demonstrate you have achieved all the required learning outcomes for a course.
If you apply and are granted supplementary assessment, the type of supplementary assessment set will consider which learning outcome(s) have not been met.
Supplementary assessment can take any form (such as a written report, oral presentation, examination or other appropriate assessment) and may test specific learning outcomes tailored to the individual student, or all learning outcomes.
To receive a passing grade of 3S4, you must obtain a mark of 50% or more on the supplementary assessment.
Additional assessment information
Applications for Extensions
Information on applying for an extension can be found here - my.UQ Applying for an extension
Extension applications must be received by the assessment due date and time.
If you are unable to provide documentation to support your application by the due date and time you must still submit your application on time and attach a Word document outlining why you cannot provide the documentation and upload the documentation to the portal within 24 hours.
Please note: While your extension request is being considered, you should work towards completing and submitting your assessment as soon as possible.
If you have been ill or unable to attend class for more than 4 weeks in a semester, we advise you to carefully consider whether you are capable of successfully completing your courses. You might need to consider applying for removal of course. We strongly recommend you seek advice from the Faculty that administers your program.
Extensions with Student Access Plans (SAP)
For extensions up to 7 days, your SAP is all that is required as documentation to support your application. However, extension requests longer than 7 days (for any one assessment item) will require the submission of additional supporting documentation e.g., a medical certificate. A maximum of two applications may be submitted for any one assessment item, unless exceptional circumstances can be demonstrated. All extension requests must be received by the assessment due date and time.
Artificial Intelligence (AI)
The assessment tasks in this course evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute misconduct under the Student Code of Conduct.
Turnitin
By submitting work through Turnitin you are deemed to have accepted the following declaration “I certify that this assignment is my own work and has not been submitted, either previously or concurrently, in whole or in part, to this University or any other educational institution, for marking or assessment.”
All students must ensure they receive their Turnitin receipt on submission of any assessments. A valid Turnitin receipt will be the only evidence accepted if assessments are missing. Without evidence, the assessment will receive the standard late penalty, or after five days, will receive zero.
In the case of a Blackboard outage, please contact the Course Coordinator as soon as possible to confirm the outage with ITS.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Library resources are available on the UQ Library website.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Lecture |
Week 1: Nature of geospatial data processing What are the benefits of programming to support spatial data handling and analytics. |
|
Lecture |
Week 2: Data and information How is data used in a meaningful way? How is it organised for analysis? |
|
Lecture |
Week 3: Concepts for geospatial data analysis Explore basic geospatial concepts and measurements used in geospatial data analysis and mapping. |
|
Lecture |
Week 4: Introduction to web mapping Architecture of the web for data storage and serving web outputs. |
|
Lecture |
Week 5: Formats for exchanging geospatial data Formats to share data between devices such as GPS, mobile data collectors, etc. |
|
Lecture |
Week 6: Geospatial data storage and use Spatial databases and the competing aims for efficient storage versus ease of use in applications. |
|
Lecture |
Week 7: Geoprocessing feature workflows Geospatial processing for map exploration and describing spatial patterns. |
|
Lecture |
Week 8: Geoprocessing imagery workflows Online access and processing of raster data and satellite imagery. |
|
Lecture |
Week 9: Web cartography Concepts for map generalisation and multiscale web maps. |
|
Workshop |
Week 10: Geospatial project overview Lecture gives overview of small project expectation. Lectures and practicals (over weeks 10-12) incorporate individual consultation; students expected to show data for study area and discuss their issue and approach for inquiry-driven investigation. |
|
Lecture |
Week 11: Web linked geospatial information Lecture presents future technology for geospatial data storage and organisation with knowledge graphs. Lectures and practicals (over weeks 10-12) incorporate individual consultation; students expected to show data for study area and discuss their issue and approach for inquiry-driven investigation. |
|
Workshop |
Week 12: Geospatial Project Review Lectures and practicals (over weeks 10-12) incorporate individual consultation; students expected to show data for study area and discuss their issue and approach for inquiry-driven investigation. |
|
Lecture |
Week 13: Course wrap-up Summary and feedback on course. |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.