Course Title: Conduct advanced remote sensing analysis
Part B: Course Detail
Teaching Period: Term1 2025
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: Matthew Sweeney
Course Contact Phone: +61 3 9925 4105
Course Contact Email: matthew.sweeney@rmit.edu.au
Name and Contact Details of All Other Relevant Staff
Greg Patterson
Surveying & Spatial Educator
Building, Surveying & Land Management
Built Environment & Sustainability
RMIT University
MELBOURNE 3001
Victoria, Australia
Email: gregory.patterson@rmit.edu.au
Work: +61 3 9925 9218
Mobile: 0400231518
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
This will include:
- Determine project requirements
- Identify key spatial references
- Combine remote sensing imagery bands
- Use remote sensing software to determine healthy vegetation
- Perform unsupervised classification
- Perform supervised classification
- Document methodology
- Interpret and evaluate results using error analysis
- Document methodology
- Finalise portfolio
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
Syllabus
The following syllabus provides you with this course's Training and Assessment schedule. Refer to this page to find out what themes will be discussed each week and when assessments are due. You will also find important information on census dates, excursions and practices. While we endeavor to deliver and assess in line with this syllabus, we reserve the right to make changes to accommodate unexpected circumstances.
Session/Date |
Theme |
Assessments |
|
10-16 February |
Lesson Title: Introduction to the subject Description: During this session, the student will be provided with an overview of the assessment. The teacher will guide the students through the assessment documentation, explaining the requirements and expectations. Furthermore, software licenses will be distributed to the students, enabling them to install and utilize the required software on their personal computers. This will allow them to work on the assessment tasks conveniently from their home environment. In addition to the assessment materials, students will also be introduced to various supplementary training resources. These resources may include platforms like LinkedIn Training, where they can access additional training modules and materials to enhance their knowledge and skills beyond the scope of the assessment. |
Assessment 1 Released |
|
17-23 February |
Lesson Title: Introduction to Remote Sensing Description: In this session, students will be introduced to remote sensing and its terminology. The student will be required to answer a series of knowledge questions pertaining to the topic. By engaging with these concepts and answering a series of questions, students will cultivate a comprehensive understanding of remote sensing principles and practices. This understanding will empower them to effectively apply their knowledge in practical situations and make informed decisions when working with remote sensing data and imagery. |
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24 February -2 March |
Lesson Title: Determine and document requirements Description: During this session, the student will be assigned an assessment task that involves participating in a meeting with the client. The purpose of the meeting is to engage in extensive discussions and document all project requirements, while also addressing a series of questions. The main objective of these discussions and documentation is to establish a clear and precise understanding of the project scope, ensuring alignment among all stakeholders. This meticulous process will facilitate effective planning and execution of the assessment task, ultimately leading to a successful outcome. By successfully completing these tasks, the student will demonstrate their proficiency in understanding and managing project requirements, as well as their ability to communicate effectively with clients and stakeholders. |
Assessment 1 Determine healthy vegetation using NDVI Section B – Marking Guide 1A |
|
3 - 9 March |
Lesson Title: Determine suitable imagery Description: In this session, the student will receive an assessment task that involves the identification of suitable imagery through the examination of metadata, as well as obtaining and validating the associated imagery. In addition to these tasks, you will be responsible for documenting the URL from which you obtained the imagery and noting any constraints related to its usage. It is essential to identify potential contingencies in situations where the imagery is unsuitable or cannot be utilized due to legal reasons. This may require exploring alternative sources or approaches to ensure the project requirements are fulfilled. Furthermore, the student is expected to answer knowledge questions that demonstrate their understanding of selecting appropriate imagery. This will serve as evidence of their comprehension of the subject matter and their ability to apply theoretical concepts to practical scenarios. By successfully completing these tasks and showcasing their knowledge, the student will demonstrate their proficiency in identifying and validating suitable imagery for geospatial projects. |
Assessment 1 Determine healthy vegetation using NDVI Section B – Marking Guide 1B |
|
10-16 March |
Lesson Title: Conduct NDVI – ArcGIS Pro Description: During this session, the students will be introduced to the process of determining healthy vegetation using the Normalized Difference Vegetation Index (NDVI). They will be required to obtain the necessary multispectral imagery and utilize ArcGIS Software, analyze the imagery and identify areas with healthy vegetation. Additionally, the students will document the process and answer a series of questions related to the topic. This exercise will enable them to reinforce their understanding and demonstrate their knowledge of the NDVI analysis for vegetation assessment. Note: 10 Mar - Labour Day public holiday |
|
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17-23 March |
Lesson Title: Conduct NDVI – Safe Software FME Description: During this session, the students will be introduced to the process of determining healthy vegetation using the Normalized Difference Vegetation Index (NDVI). They will be required to obtain the necessary multispectral imagery and utilize Safe Software FME to analyze the imagery and identify areas with healthy vegetation. Additionally, the students will document the process and answer a series of questions related to the topic. This exercise will enable them to reinforce their understanding and demonstrate their knowledge of the NDVI analysis for vegetation assessment. |
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|
24-30 March |
Lesson Title: Determine Healthy vegetation using Multispectral Imagery Description: During this session, the student will engage in an assessment task focused on determining healthy vegetation using the Normalized Difference Vegetation Index (NDVI) method. The task involves obtaining multispectral imagery and utilizing appropriate GIS software to analyze the imagery and identify areas with healthy vegetation. The student will be responsible for validating and processing the imagery according to specified requirements while documenting the employed process. Additionally, the student will need to answer a series of questions related to the topic. This assessment aims to evaluate the student's understanding of the NDVI method and their ability to apply it effectively in practical scenarios. Successful completion of these tasks will demonstrate the student's proficiency in determining healthy vegetation using the NDVI method. By successfully completing these tasks, the student will showcase their proficiency in analyzing multispectral imagery, applying the NDVI method, and interpreting the results to identify areas with healthy vegetation. |
Assessment 1 Determine healthy vegetation using NDVI Section B – Marking Guide 1C |
|
31 March - 06 April |
Lesson Title: Interpret results from univariate and multivariate statistics Description: In this session, the student will engage in an assessment task focused on interpreting and creating histogram plots based on univariate and multivariate statistics. The task includes two main components: creating a pie chart to visualize the correlation range with percentage coverage, and generating a histogram plot to depict the correlation range and its corresponding percentage coverage. By completing these tasks, the student will demonstrate their ability to analyze statistical data, effectively represent correlations through visualizations, and interpret the information conveyed by the histogram plots. |
Assessment 1 Conduct error analysis to determine accuracy of results Section B – Marking Guide 1E |
|
7-13 April |
Lesson Title: Conduct error analysis to determine accuracy of results Description: In this session, the student will finalise and upload Assessment 1.
Agenda:
|
Assessment 1:
Finalise portfolio. Section B – Marking Guide 1I
Assessment 1 Due: 13 April 2025 |
|
14-17 April |
Lesson Title: Introduction to Unsupervised and Supervised Classification Description: During this session, the student be introduced to unsupervised and Supervised classification |
Assessment 2 Released |
|
18 - 25 April
|
The Mid-semester break is a scheduled break in the semester. No teaching or assessment will occur during this time. Also, your Trainer/Assessor won't be available during this time. If you need to contact them, please email them via your student email account, and they will respond once they return from the break. |
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29 April - 5 May |
Lesson Title: Determine and document requirements Description: During this session, the student will be assigned an assessment task that involves participating in a meeting with the client. The purpose of the meeting is to engage in extensive discussions and document all project requirements, while also addressing a series of questions. The main objective of these discussions and documentation is to establish a clear and precise understanding of the project scope, ensuring alignment among all stakeholders. This meticulous process will facilitate effective planning and execution of the assessment task, ultimately leading to a successful outcome. By successfully completing these tasks, the student will demonstrate their proficiency in understanding and managing project requirements, as well as their ability to communicate effectively with clients and stakeholders. |
Assessment 2 Project specifications and documented requirements Section B – Marking Guide 1A |
|
5-11 May |
Lesson Title: Determine suitable imagery Description: In this session, the student will receive an assessment task that involves the identification of suitable imagery through the examination of metadata, as well as obtaining and validating the associated imagery. In addition to these tasks, you will be responsible for documenting the URL from which you obtained the imagery and noting any constraints related to its usage. It is essential to identify potential contingencies in situations where the imagery is unsuitable or cannot be utilized due to legal reasons. This may require exploring alternative sources or approaches to ensure the project requirements are fulfilled. Furthermore, the student is expected to answer knowledge questions that demonstrate their understanding of selecting appropriate imagery. This will serve as evidence of their comprehension of the subject matter and their ability to apply theoretical concepts to practical scenarios. By successfully completing these tasks and showcasing their knowledge, the student will demonstrate their proficiency in identifying and validating suitable imagery for geospatial projects. |
Assessment 2 Determined suitability of imagery: Section B – Marking Guide 1B |
|
12-18 May |
Lesson Title: Conduct Supervised and Unsupervised classification – ArcGIS Pro Description: During this session, the students will learn about the process of conducting supervised and unsupervised classification using ArcGIS Pro software. The objective is to classify the obtained multispectral imagery and identify features such as Bare Earth, Vegetation (including forest areas, pine trees, and grass), and Hydrography features (such as dams, lakes, and reservoirs). The tasks assigned to the students include:
By successfully completing these tasks, the students will showcase their proficiency in conducting supervised and unsupervised classification using ArcGIS Pro software. They will demonstrate their ability to accurately classify the imagery and identify specific features based on their spectral characteristics. |
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19 - 25 May |
Lesson Title: Perform supervised classification Description: In this session, the student will participate in an assessment task focused on supervised classification using ArcGIS Pro software. The task entails obtaining multispectral imagery and utilizing ArcGIS Software to analyze the imagery and identify Bare Earth, Vegetation (Forest areas, Pine Trees, grass), and Hydrography features (Dams, Lakes reservoirs, etc). Additionally, the student will be responsible for documenting the methodology used during the classification process. The student's responsibilities include:
By successfully fulfilling these tasks, the students will demonstrate their proficiency in conducting supervised classification using ArcGIS Pro software. They will showcase their aptitude in effectively analyzing imagery, accurately classifying diverse features, and providing well-documented methodologies for their classification processes. |
Assessment 2 Performed supervised classification Section B – Marking Guide 1C, 1D |
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26 May - 01 June |
Lesson Title: Conduct error analysis Description: During this session, the student will undertake an assessment task that centers on calculating the approximate percentage error to evaluate the accuracy of their classification using error analysis techniques. The task involves completing and interpreting the results, evaluating the outcome, identifying and rectifying any identified issues, updating the documentation, and including a copy of it in the portfolio. Additionally, the student will be required to explain the difference between supervised and unsupervised classification. By successfully accomplishing these tasks, the students will demonstrate their proficiency in error analysis, result interpretation, problem-solving, and understanding the distinctions between supervised and unsupervised classification methods. |
Assessment 2 Interpreted the error analysis Section B – Marking Guide 1C |
|
02 - 08 June |
Lesson Title: Finalise and submit project assessment Description: During this session, the student will be assigned an assessment task focused on finalizing all documentation. The completed portfolio is to be uploaded onto canvas |
Assessment 2 Finalise portfolio Section B – Marking Guide 1E
Assessment 2 Due: 08 June 2025 |
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09 - 15 June |
Revision and feedback on work completed | |
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16 - 22 June |
Assessment marking and finalising results King's Birthday public holiday 09 June |
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03 July |
Important: It is your responsibility to check your results on this date. Your official results for this course will be released on this date. Your teacher will not inform you of your final result. It will only be available via My Student Record on RMIT's website. It is not your Trainer/Assessors responsibility to let you know your final result. Your teacher will not be available to comment on your assessment or final results from 23 June - 2 July 2025. After this date, you can contact them to talk about your final result if you need it. |
Learning Resources
Prescribed Texts
References
Other Resources
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
Accessed Via the RMIT Library Link:
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 Tasks:
Assessment Name |
Description |
Release Date |
Due Date |
Assessment 1: Determine healthy vegetation using NDVI |
In this assessment you will create a portfolio for the team leader that documents the full process required in determining healthy vegetation using Normalised Difference Vegetation Index (NDVI). |
10 Feb 2025 |
13 April 2025 |
Assessment 2: Supervised / Unsupervised Classification |
In this assessment you will capture and classify natural environment feature using remote sensing imagery classification techniques and classification algorithms for the topographic mapping program. |
14 April 2025 |
08 June 2025 |
Assessment Matrix
Mapping Assessments to the Unit of Competency – Instructions
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Performance Evidence | ||
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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 |
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One project must analyse remote sensing data using spectral indices to transform the image to identify landscape patterns or features. |
NDVI |
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One project must focus on performing classifications on datasets using supervised and unsupervised classification algorithms and training samples. |
|
Supervised Classification |
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Knowledge Evidence | ||
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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 |
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Metadata relating to remote sensing data |
1B |
1B |
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Characteristics of multispectral imagery, including:
|
1C |
1C |
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Spectral response patterns of common landcovers |
1D |
|
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Geometric and radiometric corrections applied to multispectral imagery |
1C |
1C |
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Functions and statistics available in image processing systems:
|
1C & 1E |
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Remote sensing indices:
|
1C |
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Industry-accepted techniques for applying supervised and unsupervised classification algorithms to remote sensing data |
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1C |
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Legislative requirements for data privacy, intellectual property and licensing when using remotely sensed data |
1B |
|
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Digital image data formats |
1A |
1A |
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Sources of spatial datasets |
1A |
1A |
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Image enhancement and processing techniques, including convolution matrices |
1C |
1C |
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Methods for validating spatial data sources and constraints on use |
1B |
1A |
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Key features of coordinate reference systems |
1B |
1A |
|
Assessment conditions |
Describe how assessments meet the assessment conditions |
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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. |
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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. |
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Candidates must have access to:
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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
Attendance Requirement - 85% for all students.
Resubmission Policy:
To pass this course, students must achieve a Satisfactory (S) result for all their Assessments (and parts of those assessments).
Students who do not achieve a Satisfactory (S) result for their entire original submission for an Assessment will be provided with 1 (one) more submission opportunity (e.g. the resubmission) with a specific due date by their assessor. Students must achieve a Satisfactory (S) result on their resubmission for that Assessment, by the due date given to them by their Assessor.
Students who fail to submit their assessment by the due date will be issued a DNS (Did Not Submit) result which will not be overturned by teaching or managing staff. A DNS result will be overturned based on an approved Extension of Time or approved Special Consideration.
To be deemed Competency Achieved, students must achieve a satisfactory result in all assessment tasks. Students who fail to receive a Satisfactory result on all assessment tasks and have exhausted their resubmissions, extension of time applications, special consideration applications or Equitable Learning Plan provisions will be deemed as Not Yet Competent.
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 the following link for more information about Credit Transfer and/or Recognition of Prior Learning (RPL):
http://www.rmit.edu.au/students/enrolment/credit
Study and learning Support:
Study and Learning Centre (SLC) provides free learning and academic development advice to you.
Services offered by SLC 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 to the following link for more information about study and learning support:
http://www.rmit.edu.au/studyandlearningcentre
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 the following link for more information about equitable learning services:
https://www.rmit.edu.au/students/support-and-facilities/student-support/equitable-learning-services
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 to the following link for more information about special considerations:
http://www.rmit.edu.au/students/specialconsideration
Plagiarism:
Plagiarism is a form of cheating, and it is very serious academic offence that may lead to expulsion from the University.
Please refer to the following link for more information about plagiarism:
www.rmit.edu.au/academicintegrity
All email communications will be sent to your RMIT email address, and you must regularly check your RMIT emails.
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