Unit Outline

This unit provides an engaging, hands-on introduction to the dynamic field of remote sensing. This unit delves into the latest advancements in satellite and aerial imagery, empowering students to utilise these technologies to understand and address diverse environmental and societal challenges. In today's rapidly changing world, remote sensing is a powerful tool with applications spanning climate change studies, vegetation studies, forestry, environmental management, glaciology, oceanography, and urban studies. Starting with the fundamental physics of light and its interaction with the Earth's atmosphere and surface, this unit covers the technical and practical aspects of a range of satellite and airborne sensors. Through weekly computer practicals using ENVI software, students gain the necessary skills to display, analyse, and extract valuable information from remotely sensed imagery. This unit equips students pursuing careers in geospatial science, geography, environmental science, earth sciences, agricultural science, plant science, computing and information systems, and marine and Antarctic studies with vital scientific and professional skills. As the demand for professionals with expertise in geospatial data analysis grows, this unit prepares students to enter the job market with confidence.

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	Analyse and interpret remote sensing datasets by applying knowledge of electromagnetic energy and its interactions with the Earth's atmosphere and surface.
2	Apply remote sensing data and analysis techniques to investigate environmental and spatial challenges.
3	Apply image analysis software to process, analyse, and visualise remote sensing data and produce spatial products including maps and classified images.
4	Communicate remote sensing concepts, analytical methods, and results through written, oral, and visual means, demonstrating the ability to explain and justify analytical decisions.

Alterations as a result of student feedback

Lectures have been replaced with pre-recorded short videos and one weekly 1-hour seminar that is focused on interactive problem-solving and data analysis demonstrations.

Teaching arrangements


ATTENDANCE MODE	TEACHING TYPE	LEARNING ACTIVITY	CONTACT HOURS	FREQUENCY
On Campus	Seminar	On campus seminar (software demonstrations and Q&A)	1	Weekly
	Practical	3-hour practical on campus (independent computer work in lab with tutoring support)	3	Weekly
	Independent Learning	In addition to the contact hours (1 hr/week seminar + 3hr/week computer pracs) you are expected to dedicate at least 4 hours per week on independent learning. This includes weekly pre-recorded videos that you will need to review before each seminar. You are expected to dedicate additional time to assessment tasks.	4	Weekly
Online	Seminar	Online seminar (software demonstrations and Q&A)	1	Weekly
	Tutorial (Online)	3-hour computer practical (independent computer work with online tutoring support)	3	Weekly
	Independent Learning	In addition to the contact hours (1 hr/week seminar + 3hr/week computer pracs) you are expected to dedicate at least 4 hours per week on independent learning. This includes weekly pre-recorded videos that you will need to review before each seminar. You are expected to dedicate additional time to assessment tasks.	4	Weekly

Attendance / engagement expectations

If your unit is offered On campus, it is expected that you will attend all on-campus and onsite learning activities. This is to support your own learning and the development of a learning community within the unit. If you are unable to attend regularly, please discuss the situation with your course coordinator and/or our UConnect support team.

If your unit is offered Online or includes online activities, it is expected you will engage in all those activities as indicated in the Unit Outline or MyLO, including any self-directed learning.

If you miss a learning activity for a legitimate reason (e.g., illness, carer responsibilities) teaching staff will attempt to provide alternative activities (e.g., make up readings) where it is possible.

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:	Assessment Task 1: Foundations of image interpretation	Week 3	15 %	LO1, LO2, LO3, LO4
Assessment Task 2:	Assignment 2 Applied Remote Sensing Techniques: Weekly Tasks	Week 8	35 %	LO1, LO2, LO3, LO4
Assessment Task 3:	Assessment Task 3: remote sensing case study	Week 12	50 %	LO1, LO2, LO3, LO4

Assessment details

Assessment Task 1: Assessment Task 1: Foundations of image interpretation

Task Description:

This assignment develops foundational skills in the visual interpretation of spectral reflectance values in false colour images. Students analyse a multispectral satellite image of the greater Hobart area, generating spectral profiles and relating pixel values to surface colour in true colour and colour infrared composites. The task requires students to interpret the spectral basis for surface appearance across different band combinations and draw conclusions about the physical properties of surfaces. The assignment is directly linked to Practical 2 and lecture material from weeks 1–3.

GenAI guidance: Students may use GenAI to find related background information. GenAI output must not be submitted as the student's own answer.

Task Length:

Written answers with annotated figures (approximately 600–900 words including screenshots and spectral profile plots). Submitted as a single PDF document to MyLO.

Due Date:

Week 3 (26/Jul/2026)

Weight:

15 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Analyse the interactions between electromagnetic energy and matter, demonstrating an understanding of the principles of electromagnetic energy, atmospheric interactions, and reflectance properties.	LO1
2	Apply theoretical concepts of spectral reflectance and wavelengths to a practical case study, interpreting spectral signatures and image colours in different band combinations.	LO2, LO3
3	Communicate understanding of spectral analysis and reflectance interpretation through clear, concise written responses with appropriate figures.	LO4

Assessment Task 2: Assignment 2 Applied Remote Sensing Techniques: Weekly Tasks

Task Description:

This assignment consolidates practical skills developed in weeks 3–7 into a single portfolio submission. Students complete three to four applied tasks covering image georeferencing and error assessment, spectral enhancement and vegetation index analysis using Digital Earth Australia, hyperspectral mineral identification using spectral feature fitting, and image classification accuracy interpretation. Each task requires students to generate outputs in ENVI or the DEA Map Viewer, include annotated screenshots or spectral plots, and write concise interpretations. Assessment focuses on applied interpretation and written justification of results.

GenAI guidance: Students may use GenAI to find related information and guidance. GenAI output must not be submitted as the student's own answer.

Task Length:

Single PDF submission containing answers to tasks/questions from practicals 3 - 7. Each task comprises annotated screenshots or figures and a written response of 100–200 words. Total submission approximately 8–12 pages including figures.

Due Date:

Week 8 (06/Sep/2026)

Weight:

35 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Apply theoretical principles from lecture material to practical tasks, demonstrating understanding of key remote sensing techniques including georeferencing, spectral enhancement, hyperspectral analysis, and image classification.	LO1, LO2
2	Interpret remote sensing images and derived products by drawing conclusions about surface features using spectral signatures, reflectance characteristics, and accuracy statistics.	LO1, LO3
3	Apply image analysis software to generate correct outputs including spectral profiles, classification results, and accuracy assessments.	LO3
4	Communicate understanding of applied remote sensing techniques through concise, accurate, and well-reasoned written responses with clear figures.	LO4

Assessment Task 3: Assessment Task 3: remote sensing case study

Task Description:

In this capstone assignment, students will conduct an independent analysis of satellite imagery applying classification and change detection techniques in the context of a practical real-world application. This assignment will bring together skills in remote sensing data analysis and knowledge of foundational concepts.

The assignment has two assessed components:
Component 1 Progress video checkpoint (10% of AT3): A single 3-minute narrated screen-capture video submitted in week 10. The student shows their ENVI project with training ROIs on the image, explains their training site rationale, and displays their initial classification output.

Component 2 Live presentation and Q&A (90% of A3 = 45% of unit, Lane 1 hurdle): A 15-minute individual supervised session in week 12. The student shares their screen with and delivers a 7-minute narrated walkthrough of their complete analysis workflow, demonstrating live software interaction and interpreting their results. The assessor then conducts an 8-minute targeted Q&A, probing analytical decisions, accuracy interpretation, method comparison, and limitations. Sessions are conducted via Zoom with camera on, and are recorded for moderation. Students must pass this component to pass the unit.

GenAI guidance: Students may use GenAI to find background information during the analysis phase. The live presentation and Q&A must reflect the student's own understanding. GenAI tools are not permitted during the supervised session.

Task Length:

Component 1: 3-minute screen-capture video (submitted to MyLO). Component 2: 15-minute live session (7-minute presentation + 8-minute Q&A). No written report is required.

Due Date:

Week 12 (02/Oct/2026)

Weight:

50 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Select and apply appropriate image processing techniques, including spectral indices and classification methods, to identify fire-affected areas in satellite imagery. Demonstrate competent use of ENVI software through live screen interaction.	LO1, LO2, LO3
2	Analyse the impact of the bushfire event on the Tasmanian landscape by mapping affected areas, interpreting classification accuracy, and comparing change detection approaches.	LO1, LO2
3	Communicate the results of the analysis through a clear, structured oral presentation with effective visual support, demonstrating the ability to narrate a coherent analytical workflow.	LO4
4	Respond to assessor questions by explaining and justifying analytical decisions, interpreting accuracy statistics, evaluating method trade-offs, and reflecting on limitations of the analysis.	LO4

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.

Assessment Task 3 is a Lane 1 assurance of learning task. You will need to pass this assessment task to pass the unit. This tasks includes a live online presentation and Q&A session associated with the data analysis task.

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.