Course Title: Conduct advanced remote sensing analysis
Part B: Course Detail
Teaching Period: Term1 2022
Course Code: GEOM5194C
Course Title: Conduct advanced remote sensing analysis
School: 530T Built Environment and Sustainability
Campus: City Campus
Program: C6175 - Advanced Diploma of Surveying
Course Contact: Thierry Demathieu
Course Contact Phone: +61 3 9925 8359
Course Contact Email: thierry.demathieu@rmit.edu.au
Name and Contact Details of All Other Relevant Staff
Greg Patterson
Spatial Scientist and Surveying Teacher
School of Vocational Engineering, Health & Sciences
RMIT University
Building 56
Carlton, Vic, 3053, Australia
Phone: +61 400 231 518
Email: gregory.patterson@rmit.edu.au
Nominal Hours: 120
Regardless of the mode of delivery, represent a guide to the relative teaching time and student effort required to successfully achieve a particular competency/module. This may include not only scheduled classes or workplace visits but also the amount of effort required to undertake, evaluate and complete all assessment requirements, including any non-classroom activities.
Pre-requisites and Co-requisites
None
Course Description
In this course you will develop the skills and knowledge required to conduct advanced remote sensing analysis on digital imagery. This includes using software and image processing systems to perform the required image enhancements, manipulations and analysis. The course also includes performing supervised and unsupervised classifications on datasets and conducting related error analysis.
This course is suitable for surveyors and skilled spatial information system (SIS) technicians who use broad theoretical and technical knowledge to analyse information as well as interpret and provide solutions to unpredictable and sometimes complex surveying/spatial information problems. The course supports those who work in a technical management role in a spatial information services team, in areas such as cartography, town planning and mapping.
National Codes, Titles, Elements and Performance Criteria
National Element Code & Title: |
CPPSSI6037 Conduct advanced remote sensing analysis |
Element: |
1. Plan remote sensing analysis |
Performance Criteria: |
1.1 Analyse project specifications and determine appropriate remote sensing analysis methods. 1.2 Select suitable image sources according to project specifications. 1.3 Identify suitable images and examine metadata to meet project specifications. 1.4 Obtain image data required to meet project specifications. 1.5 Assess constraints of use of remote sensing data and plan contingencies to meet project requirements. 1.6 Apply legislative and organisational requirements for accessing and using spatial data. |
Element: |
2. Analyse image using spectral indices |
Performance Criteria: |
2.1 Perform radiometric correction on image, including converting images to reflectance or radiance values to enhance quality of image data. 2.2 Apply spectral indices to image data and interpret results. |
Element: |
3. Analyse image using image classification algorithms |
Performance Criteria: |
3.1 Apply convolution matrices to enhance quality of image data. 3.2 Determine information classes required according to project specifications. 3.3 Create training samples for required information classes. 3.4 Evaluate training areas and create spectral signature file. 3.5 Apply supervised classification algorithms to signature file. 3.6 Conduct error analysis to calculate approximate accuracy of classification. 3.7 Interpret results according to project specifications. |
Element: |
4. Document image analysis |
Performance Criteria: |
4.1 Write up the methodology used to compile and analyse image data. 4.2 Write up interpretation of results, noting accuracy and limitations. 4.3 Present results in graphical, tabular or map format according to project requirements. |
Learning Outcomes
On successful completion of this course you will have developed and applied the skills and knowledge required to demonstrate competency in the above elements.
Details of Learning Activities
You will learn to:
- Determine project requirements
- Identify key spatial references
- Combine remote sensing imagery bands
- Use remote sensing software to determine healthy vegetation
- Interpret and evaluate results using error analysis
The total number of scheduled hours of teaching, learning and assessment involved in this course includes all planned activities (face to face classes, lectures, workshops and seminars; workplace visits, online learning and other forms of structured teaching and learning). It also covers the amount of effort necessary to undertake, evaluate and complete all assessment requirements, observation of work performance, discussions with supervisors and others providing third party evidence and one on one and group assessment sessions with students.
Teaching Schedule
Course Syllabus
| Week 1 |
Monday 1. Meet with teacher and students 2. Subject / Assessments 3. Provide GIS Software licences (ArcGIS, FME) Wednesday 1. Intro to Remote Sensing |
|
| Week 2 |
Monday 1. Intro to Spatial References 2. Intro to classifying images - Different Techniques 3. Intro to Imagery Formats 4. Intro to Imagery bands - Combinations Landsat and Sentinel 5. Intro to Characteristics of imagery / Resolution Wednesday 1. Calculate burnt areas - Landsat |
Learning Activities 1. Calculate burnt areas |
| Week 3 |
Monday 1. Download Sentinel imagery 2. Determine Constraints 3. Validate imagery Wednesday 1. Calculate burnt areas - Continued |
Learning Activities Monday 1. Download Sentinel Imagery 2. Determine Constraints 3. Validate Imagery Wednesday 1. Calculate burnt areas (Continued) |
| Week 4 |
Monday 1. Introduction to NDVI 2. Assessment 1 - Part 1 - Determine and Document requirements Wednesday 1. Assessment 1 - Part 2 - Obtain Suitable Imagery |
Assessment 1 Activities: Part 1: Determine and Document requirements Part 2: Obtain Suitable Imagery |
| Week 5 |
Monday 1. Assessment 1 - Part 3: Determine health of vegetation (NDVI) - FME Wednesday 1. Assessment 1 - Part 3: Determine health of vegetation (NDVI) - ArcGIS |
Assessment 1 Activities: Part 3: Determine health of vegetation (NDVI) |
| Week 6 |
Monday 1. Assessment 1 - Part 3: Determine health of vegetation (NDVI) - FME (Continued) Wednesday 1. Assessment 1 - Part 3: Determine health of vegetation (NDVI) - ArcGIS (Continued) |
Assessment 1 Activities: Part 3: Determine health of vegetation (NDVI) |
| Week 7 |
Monday 1. Assessment 1 - Part 3: Determine health of vegetation (NDVI) - FME (Continued) Wednesday 1. Assessment 1 - Part 3: Determine health of vegetation (NDVI) - ArcGIS (Continued) |
Assessment 1 Activities: Part 3: Determine health of vegetation (NDVI) |
| Week 8 |
Monday 1. Assessment 1 - Part 5: Interpret results from univariate and multivariate statistics 2. Assessment 1 - Part 6: Conduct error analysis to determine accuracy of results Wednesday 1. Assessment 1 - Part 4: Interpret spectral response patterns |
Assessment 1 Activities: Part 4: Interpret spectral response patterns Part 5: Interpret results from univariate and multivariate statistics Part 6: Conduct error analysis to determine accuracy of results |
| Week 9 |
Monday 1. Assessment 1 - Part 7: Document Methodology Wednesday 1. Assessment 1 - Part 8: Identify limitations affecting accuracy |
Assessment 1 Activities: Part 7: Document Methodology Part 8: Identify limitations affecting accuracy Assessment 1 Due |
| Week 10 |
Monday 1. Intro to Supervised and Unsupervised Classification 2. Perform Unsupervised Classification Wednesday 1. Perform Supervised Classification 2. Calculate Percent Error |
Learning Activities 1. Unsupervised Classification 2. Supervised Classification 3. Calculate Percent Error |
| Week 11 |
Monday 1. Perform Unsupervised Classification Wednesday 1. Perform Supervised Classification |
Learning Activities 1. Unsupervised Classification 2. Supervised Classification 3. Calculate Percent Error |
| Week 12 |
Monday 1. Assessment 2 - Part 1: Determine and document requirements Wednesday 1. Assessment 2 - Part 2: Determine suitable imagery |
Assessment 2 Activities: Part 1: Determine and document requirements Part 2: Determine suitable imagery |
| Week 13 |
Monday 1. Assessment 2 - Part 3: Perform Supervised Classification Wednesday 1. Assessment 2 - Part 3: Perform Supervised Classification |
Assessment 2 Activities: Part 3: Perform Supervised Classification |
| Week 14 |
Monday 1. Assessment 2 - Part 3: Perform Supervised Classification Wednesday 1. Assessment 2 - Part 3: Perform Supervised Classification |
Assessment 2 Activities: Part 3: Perform Supervised Classification |
| Week 15 |
Both Classes Complete Portfolio |
Assessment 2 Activities: Work on assessment requirements |
| Week 16 |
Both Classes Complete and submit completed portfolio |
Assessment 2 Activities: Complete assessment requirements |
Learning Resources
Prescribed Texts
References
Other Resources
Overview of Assessment
Assessment for this course is ongoing throughout the semester. Your knowledge and understanding of course content is assessed through participation in class exercises, oral presentations and through the application of learned skills and insights to your written tasks. Full assessment briefs will be provided and can be found on CANVAS.
Assessment Tasks
- Assessment 1: Determine healthy vegetation using NDVI
- Assessment 2: Supervised / Unsupervised Classification
Assessment Matrix
Mapping Assessments to the Unit of Competency – Instructions
Performance Evidence | ||
To demonstrate competency a candidate must meet the elements and performance criteria of this unit by using a computer and remote sensing software system to conduct and report an advanced remote sensing analysis for two different projects: |
Assessment Task 1: Determine healthy vegetation using NDVI |
Assessment Task 2: Supervised / Unsupervised Classification |
One project must analyse remote sensing data using spectral indices to transform the image to identify landscape patterns or features. |
NDVI |
|
One project must focus on performing classifications on datasets using supervised and unsupervised classification algorithms and training samples. |
Supervised Classification |
Knowledge Evidence | ||
To be competent in this unit a candidate must demonstrate knowledge of: |
Assessment Task 1: Determine healthy vegetation using NDVI |
Assessment Task 2: Supervised / Unsupervised Classification |
Metadata relating to remote sensing data |
1B |
1B |
|
Characteristics of multispectral imagery, including:
|
1C |
1C |
Spectral response patterns of common landcovers |
1D |
|
Geometric and radiometric corrections applied to multispectral imagery |
1C |
1C |
|
Functions and statistics available in image processing systems:
|
1C & 1E |
|
|
Remote sensing indices:
|
1C |
|
Industry-accepted techniques for applying supervised and unsupervised classification algorithms to remote sensing data |
1C |
|
Legislative requirements for data privacy, intellectual property and licensing when using remotely sensed data |
1B |
|
Digital image data formats |
1A |
1A |
Sources of spatial datasets |
1A |
1A |
Image enhancement and processing techniques, including convolution matrices |
1C |
1C |
Methods for validating spatial data sources and constraints on use |
1B |
1A |
Key features of coordinate reference systems |
1B |
1A |
Assessment conditions |
Describe how assessments meet the assessment conditions |
Assessors must meet the requirements for assessors contained in the Standards for Registered Training Organisations. |
RMIT employment requires all trainers and assessors to comply with the Standards for RTOs in respect to holding the TAE40116, or higher VE qualification including any necessary updated units. All employees must show currency within their vocational specialty along with their professional employment. |
Competency is to be assessed in the workplace or a simulated environment that accurately reflects performance in a real workplace setting where these skills and knowledge would be performed. |
Assessments reflect the workspace environment. Assessors to have appropriate industry experience and knowledge. Students have access to computers with the latest GIS software packages during scheduled class times that comply with current industry practices. |
|
Candidates must have access to:
|
All labs will have the appropriate computers and software installed. Software that students required include:
Students will have access to additional software through Office 365. The students can sign in with your RMIT email address and password. |
Other Information
Credit Transfer and/or Recognition of Prior Learning (RPL):
You may be eligible for credit towards courses in your program if you have already met the learning/competency outcomes through previous learning and/or industry experience. To be eligible for credit towards a course, you must demonstrate that you have already completed learning and/or gained industry experience that is:
- Relevant
- Current
- Satisfies the learning/competency outcomes of the course
Please refer to http://www.rmit.edu.au/students/enrolment/credit to find more information about credit transfer and RPL.
Study Support:
Study Support provides free learning and academic development advice to you.
Services offered by Study Support to support your numeracy and literacy skills are:
assignment writing, thesis writing and study skills advice
maths and science developmental support and advice
English language development
Please Refer https://www.rmit.edu.au/students/study-support to find more information about Study and learning Support
Equitable Learning Services (ELS):
If you are suffering from long-term medical condition or disability, you should contact Equitable Learning Services (ELS) to seek advice and support to complete your studies.
Please refer to https://www.rmit.edu.au/students/support-and-facilities/student-support/equitable-learning-services to find more information about services offered by Equitable Learning Services (ELS).
Late submission:
If you require an Extension of Submittable Work (assignments, reports or project work etc.) for 7 calendar days or less (from the original due date) and have valid reasons, you must complete and lodge an Application for Extension of Submittable Work (7 Calendar Days or less) form and lodge it with the Senior Educator/ Program Manager.
The application must be lodged no later than one working day before the official due date. You will be notified within no more than 2 working days of the date of lodgement as to whether the extension has been granted.
If you seek an Extension of Submittable Work for more than 7 calendar days (from the original due date) must lodge an Application for Special Consideration form under the provisions of the Special Consideration Policy, preferably prior to, but no later than 2 working days after the official due date.
Submittable Work (assignments, reports or project work etc.) submitted late without approval of an extension will not be accepted or marked.
Special consideration:
Please Refer https://www.rmit.edu.au/students/student-essentials/assessment-and-exams/assessment/special-consideration to find more information about special consideration
Academic Integrity:
"Academic integrity means acting with the values of honesty, trust, fairness, respect and responsibility in learning, teaching and research."
It means referencing the work of others while developing your own insights, knowledge and ideas.
Breaches of academic integrity include:
- plagiarism and failure to correctly acknowledge sources
- contract cheating or paying/getting another person to prepare an assignment
- submitting work prepared by another person
- copying other people’s work
- cheating in exams
- breaching the Research Code
- using unauthorised materials or devices
Please Refer: https://www.rmit.edu.au/students/student-essentials/assessment-and-exams/academic-integrity to find more information about plagiarism.
All email communications will be sent to your RMIT email address and you must regularly check your RMIT emails.
Students will be able to access course information and learning materials through the Learning Hub and may be provided with additional materials in class. Lists of relevant reference books, resources in the library and accessible Internet sites will be provided where possible. You will also use equipment and software packages in the laboratory for the project work. During the course, you will be directed to websites to enhance your knowledge and understanding of difficult concepts
Check the Library Subject Guides: http://rmit.libguides.com/geospatial
Course Overview: Access Course Overview