Unit Outline

This unit builds on the theory and skills of KGG103 Remote Sensing: observing the Earth from above, and focuses on advanced aspects of remotely sensed image analysis that turn raw remote sensing data into valuable information. These additional remote sensing analysis skills are highly valued by employers in the geospatial industry. The unit will provide you with practical skills in image analysis techniques, such as geometric and atmospheric image correction, image filters, texture measures, image enhancements and transformations, classification algorithms, object-based image analysis, change detection, and accuracy assessment. The theory is illustrated with a range of real-world applications using optical, multispectral, hyperspectral, and LiDAR data. Computer practicals and an independent project (in pairs) promote practical remote sensing skills using the latest image processing tools. The unit is likely to be of interest to students in geography, environmental studies, earth sciences, plant science, zoology, agricultural science, computing and information systems, archaeology, and engineering who want to enhance their remote sensing knowledge and professional skills.

Intended Learning Outcomes

As per the Assessment and Results Policy 1.3, your results will reflect your achievement against specified learning outcomes.

On completion of this unit, you will be able to:


1	Explain image analysis techniques to inform the interpretation and enhancement of remote sensing datasets.
2	Apply analysis techniques on remote sensing datasets to solve environmental and social problems that require spatial solutions
3	Operate remote sensing software to produce enhanced spatial information from basic datasets

Requisites


REQUISITE TYPE	REQUISITES
Pre-requisite	KGG103

Alterations as a result of student feedback

This unit has reduced the duration of the live seminars and these will focus more on demonstrations, case studies and examples (with some theory) while the weekly pre-recorded content will provide the theoretical background in preparation for the seminars.

How will I be Assessed?

For more detailed assessment information please see MyLO.

Assessment schedule


ASSESSMENT TASK #	ASSESSMENT TASK NAME	DATE DUE	WEIGHT	LINKS TO INTENDED LEARNING OUTCOMES
Assessment Task 1:	Assignment 1: Practicals 1 - 4	Week 5	30 %	LO1, LO2, LO3
Assessment Task 2:	Assignment 2: Practicals 5 - 7	Week 9	30 %	LO1, LO2, LO3
Assessment Task 3:	Assignment 3: Project	Week 14	40 %	LO1, LO2, LO3

Assessment details

Assessment Task 1: Assignment 1: Practicals 1 - 4

Task Description:

Submission of report with answers to questions and completion of tasks in weekly computer practicals for weeks 1 – 4, including presentation of results in figures and interpretation of analysis output.

Task Length:

1000 - 1500 words

Due Date:

Week 5 (28/Mar/2025)

Weight:

30 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Apply remote sensing techniques and software tools focusing on vegetation indices, lidar processing, and image transforms and filters	LO2, LO3
2	Interpret and compare outputs from image processing techniques	LO2, LO3
3	Present analysis results in a report including appropriate figures and plots for visual communication and references to source material	LO1, LO2

Assessment Task 2: Assignment 2: Practicals 5 - 7

Task Description:

Submission of report with answers to questions and completion of tasks in weekly computer practicals for weeks 5 – 7, including presentation of results in figures and interpretation of analysis output.

Task Length:

1000 - 1500 words

Due Date:

Week 9 (02/May/2025)

Weight:

30 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Apply remote sensing techniques and software tools focusing on geographic object-based image analysis and image data cube analysis	LO2, LO3
2	Interpret and compare outputs from image processing techniques	LO2, LO3
3	Present analysis results in a report including appropriate figures and plots for visual communication and references to source material	LO1, LO2

Assessment Task 3: Assignment 3: Project

Task Description:

For the Remote Sensing Project, you are expected to select a topic from a range of pre-defined project topics in different application areas. The project is carried out in a team of two students with the aim to enhance your image analysis skills. You will use the knowledge obtained in the lectures and practicals to process and analyse remote sensing data to solve a real-world problem. Practical time is available to work on the project under supervision. The assessment is based on a poster and an oral presentation. You are expected to work in a team of two students.

Your presentation is due on the due date listed, your project poster is due by 5pm on Friday 6th June.

Task Length:

Poster and 3-min presentation + Q&A

Due Date:

Week 14 (03/Jun/2025)

Weight:

40 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Explore the scientific remote sensing literature to inform selection of image analysis techniques and include reference to source material in written work	LO1, LO2
2	Develop an image analysis workflow and apply remote sensing software tools to solve a spatial problem	LO2, LO3
3	Interpret and analyse outputs from an image analysis workflow	LO1, LO2
4	Present remote sensing workflow, including processing techniques and results, in a poster and presentation using effective and concise visual communication	LO1, LO2

How your final result is determined

To pass this unit, you need to demonstrate your attainment of each of the Intended Learning Outcomes, achieve a final unit grade of 50% or greater, and pass any hurdle tasks.

Academic progress review

The results for this unit may be included in a review of your academic progress. For information about progress reviews and what they mean for all students, see Academic Progress Review in the Student Portal.

Submission of assignments

Where practicable, assignments should be submitted to an assignment submission folder in MYLO. You must submit assignments by the due date or receive a penalty (unless an extension of time has been approved by the Unit Coordinator). Students submitting any assignment in hard copy, or because of a practicum finalisation, must attach a student cover sheet and signed declaration for the submission to be accepted for marking.

Academic integrity

Academic integrity is about acting responsibly, honestly, ethically, and collegially when using, producing, and communicating information with other students and staff members.

In written work, you must correctly reference the work of others to maintain academic integrity. To find out the referencing style for this unit, see the assessment information in the MyLO site, or contact your teaching staff. For more detail about Academic Integrity, see Important Guidelines & Support.

Requests for extensions

If you are unable to submit an assessment task by the due date, you should apply for an extension.

A request for an extension should first be discussed with your Unit Coordinator or teaching support team where possible. A request for an extension must be submitted by the assessment due date, except where you can provide evidence it was not possible to do so. Typically, an application for an extension will be supported by documentary evidence: however, where it is not possible for you to provide evidence please contact your Unit Coordinator.

The Unit Coordinator must notify you of the outcome of an extension request within 3 working days of receiving the request.

Late penalties

Assignments submitted after the deadline will receive a late penalty of 5% of the original available mark for each calendar day (or part day) that the assignment is late. Late submissions will not be accepted more than 10 calendar days after the due date, or after assignments have been returned to other students on a scheduled date, whichever occurs first. Further information on Late Penalties can be found on the Assessments and Results Procedure.

Required Resources

Required reading materials