Unit Outline

This unit builds on the theory and skills of KGG542 Environmental Remote Sensing A 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. Throughout the unit you will explore remote sensing research topics in the scientific literature that will prepare you for a research thesis. This unit is offered at the graduate level.

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.	Evaluate image analysis techniques to enhance the interpretation and classification of remote sensing datasets
2.	Develop remote sensing analysis workflows to solve environmental and social problems that require spatial solutions
3.	Operate remote sensing software to implement image analysis workflows that achieve client-driven outcomes

Requisites


REQUISITE TYPE	REQUISITES
Pre-requisite	KGG542

Alterations as a result of student feedback

The number of assessment tasks have been reduced, and the assignments are better aligned to the weekly topics of lectures and computer practicals.

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: Practical Report #1	Week 5	30 %	LO1, LO2, LO3
Assessment Task 2:	Assignment 2: Practical Report #2	Week 8	30 %	LO1, LO2, LO3
Assessment Task 3:	Assignment 3: Project	Week 14	40 %	LO1, LO2, LO3

Assessment details

Assessment Task 1: Assignment 1: Practical Report #1

Task Description:

You will submit a short report of 1500 words. This report will contain your answers to questions and demonstration of completed tasks from weekly computer practicals in weeks 1 – 4. Your report will include a presentation of results in figures and interpretation of the analysis output.

Task Length:

1500 word report

Due Date:

Week 5

Weight:

30 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Evaluate remote sensing techniques and software tools focusing on vegetation indices, lidar processing, and image transforms and filters	LO2, LO3
2	Create and compare remote sensing products derived from basic datasets using image processing techniques	LO2, LO3
3	Present and evaluate results in a report including appropriate figures and plots for visual communication and references to source material	LO1, LO2

Assessment Task 2: Assignment 2: Practical Report #2

Task Description:

You will submit a short report of 1500 words. This report will contain your answers to questions and demonstration of completed tasks from weekly computer practicals in weeks 5 – 7. Your report will include a presentation of results in figures and interpretation of the analysis output.

Task Length:

1500 words

Due Date:

Week 8

Weight:

30 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Evaluate remote sensing techniques and software tools focusing on geographic object-based image analysis and image data cube analysis	LO2, LO3
2	Create and compare remote sensing products derived from basic datasets using image processing techniques	LO2, LO3
3	Present and evaluate 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:

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.

Task Length:

Poster and 3-min presentation + Q&A

Due Date:

Week 14

Weight:

40 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Synthesise 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 combine remote sensing software tools to solve a spatial problem	LO2, LO3
3	Compare outputs from an image analysis workflow and evaluate results	LO1, LO2
4	Present remote sensing project in a poster and presentation using effective visual communication, including an explanation of analysis methods, an assessment of results and reflection on issues faced and potential improvements	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.

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.

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.

Review of results and appeals

You are entitled to ask for a review of the marking and grading of your assessment task if there is an irregularity in the marking standards or an error in the process for determining the outcome of an assessment. Details on how to request a review of a mark for an assignment are outlined in the Review and Appeal of Academic Decisions Procedure.

Required Resources

Required reading materials