Course Title: Digitally enhance and process image data
Part B: Course Detail
Teaching Period: Term2 2023
Course Code: GEOM5192C
Course Title: Digitally enhance and process image data
Important Information:
Please note that this course may have compulsory in-person attendance requirements for some teaching activities.
To participate in any RMIT course in-person activities or assessment, you will need to comply with RMIT vaccination requirements which are applicable during the duration of the course. This RMIT requirement includes being vaccinated against COVID-19 or holding a valid medical exemption.
Please read this RMIT Enrolment Procedure as it has important information regarding COVID vaccination and your study at RMIT: https://policies.rmit.edu.au/document/view.php?id=209.
Please read the Student website for additional requirements of in-person attendance: https://www.rmit.edu.au/covid/coming-to-campus
Please check your Canvas course shell closer to when the course starts to see if this course requires mandatory in-person attendance. The delivery method of the course might have to change quickly in response to changes in the local state/national directive regarding in-person course attendance.
School: 530T Built Environment and Sustainability
Campus: City Campus
Program: C4417 - Certificate IV in Surveying and Spatial Information Services
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
Spatial and Surveying Teacher
School of Vocational Engineering, Health & Science
RMIT University, MELBOURNE 3001
Victoria, Australia
Email: gregory.patterson@rmit.edu.au
Nominal Hours: 40
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 extract information from original digital data before processing using remote sensing/geographic information system (GIS) software to manipulate, enhance, classify and process data. The image data can be multispectral or from aircraft, unmanned aerial vehicles or satellites.
This course is suitable for entry-level technicians who use a broad range of cognitive, technical and communication skills to select and apply a range of methods, tools, materials and information to complete routine and non-routine activities and provide and transmit solutions to a variety of predictable and sometimes unpredictable problems.
National Codes, Titles, Elements and Performance Criteria
National Element Code & Title: |
CPPSSI4026 Digitally enhance and process image data |
Element: |
1. Identify image data |
Performance Criteria: |
1.1. Analyse project specifications to determine study area and image data requirements for task in consultation with appropriate persons. 1.2 Identify potential sources of image data to meet task requirements. 1.3 Identify constraints of different types and formats of image data in relation to task requirements. |
Element: |
2. Process and analyse image data |
Performance Criteria: |
2.1. Access image data and open in software. 2.2. Interpret graphical and technical information, including landscape features within digital images. 2.3 Enhance visual display to analyse image features. 2.4. Classify image data and interpret results to achieve task requirements. 2.5. Check results for accuracy and resolve identified problems. |
Element: |
3. Present and document results |
Performance Criteria: |
3.1 Present results of analysis in map, table or graph form. 3.2 Document results of analysis to meet task and organisational requirements. 3.3 Comply with health and safety requirements when using screen-based equipment and completing records and documentation. 3.4 Comply with legislative and organisational requirements relating to data privacy, copyright and licensing. |
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
In this course you will learn:
- Raster and Vector data
- Sourcing imagery
- imagery interpretation
- Spatial References
- Types of Satellite images: Sentinal Imagery, Landsat Imagery
- supervised and unsupervised classification.
Teaching Schedule
Syllabus - Digitally enhance and process image data
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 endeavour to deliver and assess in line with this syllabus, we reserve the right to make changes to accommodate unexpected circumstances.
Session/Date |
Theme |
Assessments |
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10-16 July
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Lesson Title: Introduction to the subject Description: During this session, you will be provided with an overview of the assessment. The teacher will guide you through the assessment documentation, explaining the requirements and expectations. In addition to the assessment materials, you 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. |
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17-23 July |
Lesson Title: Introduction to imagery and analysis techniques Description: In this session, you will be introduced to the fundamental properties and characteristics of imagery, providing you with valuable insights into various types and formats of imagery and potential sources for obtaining it. You will also learn about imagery interpretation techniques, exploring six basic factors: size, shape, shadow, tone, pattern/texture, and associated features. As a group activity, we will analyze imagery together, employing these techniques to identify different features within the imagery. This practical exercise will enhance your skills in interpreting and analyzing imagery effectively. |
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24-30 July |
Lesson Title: Introduction to spatial references Description: In this session, you will receive an introduction to the key features of spatial references, which include projections, datums, and coordinate systems. You will learn about the importance of spatial references in accurately representing and locating geographic data. The session will cover different types of map projections and their characteristics, datums and their role in defining the Earth's shape and orientation, and coordinate systems used to specify positions on the Earth's surface. By understanding these key features of spatial references, you will be equipped with the knowledge to work with geospatial data effectively. This understanding will enable you to properly interpret and analyze geographic information, ensuring accurate spatial analysis and decision-making. |
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31 July - 6 August |
Lesson Title: Aerial Calculations Description: In this session, you will receive an introduction to aerial calculations, focusing on determining the sizes of objects and the scale using relevant formulas. You will learn about the necessary calculations involved in determining object sizes from aerial imagery and how to apply appropriate formulas to obtain accurate measurements. Additionally, you will understand the concept of scale and its significance in aerial calculations. By successfully engaging with these concepts and applying the provided formulas, you will develop the skills to accurately determine object sizes and scale from aerial imagery. This understanding will enable you to effectively analyze aerial data and make informed decisions based on accurate measurements. |
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7-13 August |
Lesson Title: Imagery Interpretation / Imagery Analysis Description: In this session, you will be introduced to imagery interpretation techniques aimed at identifying features within the imagery. You will receive a basic introduction to ESRI ArcGIS Software, where they will learn how to open the software, access image data, enhance the visual display including contrast stretches, and identify various features within the imagery. By the end of the session, you will have acquired the necessary skills to interpret imagery effectively using ESRI ArcGIS Software and identify key features with confidence |
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14-20 August |
Lesson Title: Assessment 1: Meeting and clarifying requirements Description: During this session, you 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. This meticulous process will facilitate effective planning and execution of the assessment task, ultimately leading to a successful outcome. By successfully completing these tasks, you will demonstrate your proficiency in understanding and managing project requirements, as well as their ability to communicate effectively with clients. |
Assessment 1 Interpretation Guide-built environment focus Section B – Marking Guide 1A - 1F, 2A |
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21-27 August |
Lesson Title: Assessment 1: Interpretation Guide Description: In this session, you will be assigned an assessment task that focuses on collecting, collating, processing, and analyzing information and imagery to create an interpretation guide. Your task will involve gathering relevant data and imagery from various sources, organizing and consolidating the information, applying appropriate processing techniques to enhance the quality of the imagery, and conducting a thorough analysis to identify and document important features and patterns. By successfully completing this assessment task, you will demonstrate your ability to effectively collect, process, and analyze information and imagery, and create a comprehensive interpretation guide. This will showcase your proficiency in interpreting and extracting valuable insights from the collected data and imagery. |
Assessment 1 Interpretation Guide-built environment focus Section B – Marking Guide 3A, 4A |
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Mid-semester break 28 August - 3 September |
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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4-10 September |
Lesson Title: Assessment 1: Interpretation Guide
Description: In this session, you will continue working on your interpretation guide. |
Assessment 1 Interpretation Guide-built environment focus Section B – Marking Guide 3A, 4A |
|
11-17 September |
Lesson Title: Assessment 1: Finalise and upload requirements Description: In this session, you will be assigned an assessment task that involves verifying the accuracy of analyzed results and submitting the required materials on Canvas. You will also be responsible for analyzing the results obtained and providing a concise summary that assesses whether the imagery interpretation guide aligns with the given task requirements. Furthermore, you will need to answer a set of knowledge questions related to the assessment task. Successfully completing this assessment will demonstrate your ability to critically evaluate and validate analyzed results, effectively communicate findings through a summary, and showcase your understanding of the subject matter through the knowledge questions. |
Assessment 1 Project Finalisation Interpretation Guide-built environment focus Section B – Marking Guide 5A, 6A, 6B Submission 17 Sep 2023 23:59 |
|
18-24 September |
Lesson Title: Introduction to satellite images Description: In this session, you will be introduced to the sources of satellite images, the spectral properties of images, and the key features of spectral signatures. You will explore various sources from which satellite images can be obtained and understand the significance of these sources in acquiring relevant and high-quality imagery. Additionally, you will learn about the spectral properties of images, which involve the different wavelengths and bands captured by remote sensing instruments. This knowledge will enable you to interpret and analyze imagery based on the unique characteristics of its spectral signature. By the end of this session, you will have a solid understanding of the sources of satellite images, the spectral properties that influence image composition, and the key features found in spectral signatures. This knowledge will serve as a foundation for effectively working with satellite imagery and extracting valuable information from it. |
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18-24 September |
Lesson Title: Imagery unsupervised classification techniques Description: In this session, you will be introduced to image classification techniques used in remote sensing, with a focus on unsupervised classification algorithms. You will explore the concept of image classification and its importance in analyzing remote sensing data. Specifically, you will learn about unsupervised classification algorithms, which allow for the automatic grouping of pixels in an image based on their spectral properties. These algorithms help identify patterns and clusters within the data without the need for predefined training samples. Furthermore, you will also delve into common band combinations used in remote sensing. Band combinations involve selecting specific spectral bands from an image to enhance certain features or highlight specific land cover types. Understanding these band combinations will enable you to optimize the visual interpretation and analysis of remote sensing data. By the end of this session, you will have a solid understanding of image classification techniques, particularly unsupervised algorithms, and the application of band combinations in remote sensing. This knowledge will equip you with valuable skills for effectively analyzing and interpreting remote sensing imagery. |
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2-8 October |
Lesson Title: Imagery supervised classification techniques Description: In this session, you will be introduced to image classification techniques used in remote sensing, with a focus on supervised classification algorithms. You will explore the concept of image classification and its significance in analyzing remote sensing data. Specifically, you will learn about supervised classification algorithms, which involve training the algorithm using labeled samples to classify pixels in an image. These algorithms rely on the knowledge and expertise of the analyst to define training areas and assign class labels. By leveraging spectral properties and other relevant information, supervised classification algorithms enable the identification and mapping of different land cover classes. Furthermore, you will delve into common band combinations used in remote sensing. Band combinations involve selecting specific spectral bands from an image to enhance certain features or highlight particular land cover types. Understanding these band combinations will enable you to optimize the visual interpretation and analysis of remote sensing data. By the end of this session, you will have a solid understanding of image classification techniques, particularly supervised algorithms, and the application of band combinations in remote sensing. This knowledge will equip you with valuable skills for effectively analyzing and interpreting remote sensing imagery. |
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9-15 October |
Lesson Title: Imagery unsupervised and supervised classification techniques (Practice) Description: In this session, you will actively participate in an exercise that focuses on processing imagery and applying both unsupervised and supervised classification techniques commonly used in remote sensing. You will gain hands-on experience in processing and analyzing remote sensing imagery using appropriate software tools. Through unsupervised classification, you will explore methods that automatically group pixels based on their spectral properties without predefined class labels. This approach allows for the identification of patterns and clusters within the image data, aiding in the understanding of land cover and land use. Additionally, you will learn about supervised classification techniques, which involve training classification algorithms using labeled samples or training data. By applying these supervised methods, you will have the opportunity to classify image pixels into specific land cover classes based on their spectral characteristics. This enables accurate mapping and identification of different features within the imagery. Throughout the exercise, you will be guided on the practical implementation of these techniques and their application in remote sensing analysis. By actively engaging in this exercise, you will develop proficiency in image processing, unsupervised classification, and supervised classification, enhancing your skills in remote sensing data interpretation. By the end of this session, you will have gained practical knowledge and experience in utilizing both unsupervised and supervised classification techniques, empowering you to effectively analyze remote sensing imagery in your future endeavors. |
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16-22 October |
Lesson Title: Assessment 2: Meeting and clarifying requirements Description: During this session, you 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. This meticulous process will facilitate effective planning and execution of the assessment task, ultimately leading to a successful outcome. By successfully completing these tasks, you will demonstrate your proficiency in understanding and managing project requirements, as well as their ability to communicate effectively with clients. |
Assessment 1 Supervised and Unsupervised Classification - Natural environment focus
Section B – Marking Guide 1A – 1E, 2A, 3B, 3C |
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23-29 October |
Lesson Title: Assessment 2: Conduct unsupervised and supervised classification Description: In this session, you will be assigned an assessment task that centers around conducting supervised and unsupervised classification techniques. Using GIS software and multispectral imagery, your task will involve applying spectral signatures to classify various features. You will learn how to interpret and analyze the spectral properties of the imagery, and use this information to classify different objects or land cover types. By successfully completing this assessment task, you will demonstrate your ability to effectively utilize GIS software, understand spectral signatures, and apply classification techniques. This will showcase your proficiency in remote sensing analysis and contribute to your overall skill set in working with multispectral imagery. Through this exercise, you will enhance your knowledge and practical experience in conducting supervised and unsupervised classification, ultimately preparing you for real-world applications where remote sensing data interpretation is required. |
Assessment 1 Supervised and Unsupervised Classification-Natural environment focus
Section B – Marking Guide 4A – 4H, 5A – 5D |
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30 October - 5 November |
Lesson Title: Assessment 2 - Finalise and upload requirements Description: In this session, you will be assigned an assessment task that involves verifying the accuracy of analyzed results and submitting the required materials on Canvas. You will also be responsible for analyzing the results obtained and providing a concise summary that assesses whether the unsupervised and supervised classification aligns with the given task requirements. Furthermore, you will need to answer a set of knowledge questions related to the assessment task. Successfully completing this assessment will demonstrate your ability to critically evaluate and validate analyzed results, effectively communicate findings through a summary, and showcase your understanding of the subject matter through the knowledge questions. |
Assessment 1 Supervised and Unsupervised Classification-Natural environment focus
Section B – Marking Guide 6A – 6L, 7A – 7C
Submission 24 Sep 2023 23:59 |
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6-12 November |
Revision and feedback on work completed | |
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13-19 November |
Assessment marking and finalising results | |
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Official Results Release DateLinks to an external site. 27 November |
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 27 November 2023. After this date, you can contact them to talk about your final result if you need it. |
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 number | Assessment type | Week Due |
| Assessment 1 | Project- Interpretation Guide - built environment focus | Week 9 |
| Assessment 2 | Project - Supervised Classification – Urban Built Environment Focus | Week 16 |
Assessment Matrix
|
Element
|
Performance criteria
|
Assessment 1: Interpretation Guide - built environment focus |
Assessment 2: Supervised and Unsupervised Classification - Natural environment focus |
| 1. Identify image data. | 1.1. Analyse project specifications to determine study area and image data requirements for task in consultation with appropriate persons. | 1A - 1D | 1D |
| 1.2 Identify potential sources of image data to meet task requirements | 1F | 1E | |
| 1.3 Identify constraints of different types and formats of image data in relation to task requirements | 1F | 3C | |
|
2. Process and Analyse image data.
|
2.1. Access image data and open in the software. | 4A | 4H, 5D |
| 2.2. Interpret graphical and technical information, including landscape features within digital images. | 3A | 4H, 5D | |
| 2.3 Enhance visual display to analyse image features. | 5A | 4H | |
| 2.4. Classify image data and interpret results to achieve task requirements. | 3A | 4H, 5D | |
| 2.5. Check results for accuracy and resolve identified problems. | 4A | 4H, 5D | |
|
3. Present and document results.
|
3.1 Present results of analysis in map, table or graph form. | 5A | 7A |
| 3.2 Document results of analysis to meet task and organisational requirements. | 5A | 5B | |
| 3.3 Comply with health and safety requirements when using screen-based equipment and completing records and documentation. | 2A | 2A | |
| 3.4 Comply with legislative and organisational requirements relating to data privacy, copyright and licensing. | 2A | 3B |
| Performance Evidence | ||
|
To demonstrate competency a candidate must meet the elements and performance criteria of this unit by using remote sensing or geographic information system (GIS) applications to digitally enhance, process and classify image data for two projects: |
Assessment Task 1: Interpretation Guide - built environment focus |
Assessment Task 2: Supervised and Unsupervised Classification - Natural environment focus |
| One project with a built environment focus and one project with a natural environment focus |
Assessment 1 built and natural environment focus |
Assessment 2 Natural environment focus |
|
PE1: digital aerial photographs
PE2: digital terrestrial images PE3: images from an unmanned aerial vehicle (UAV) PE4: satellite images. |
PE1 – PE4
3A, 4A |
PE1 - 4H, 5D PE2 - 4H, 5D PE3 – 4H, 5D PE4 - 4C, 4D, 5D |
| Knowledge Evidence | ||
| To be competent in this unit a candidate must demonstrate knowledge of: |
Assessment 1:
Interpretation Guide - built environment focus |
Assessment 2: Supervised and Unsupervised Classification - Natural environment focus |
| sources of image data | 1F | 6A |
|
basic properties and characteristics of image data used in spatial applications.
|
5A | 6B, 6C |
| image classification techniques used in remote sensing, including unsupervised classification algorithms | 4A | 6D |
| spectral properties of images and key features of spectral signatures |
|
4B, 6G |
| techniques for enhancing image display, including contrast stretches and common band combinations | 5A | 4H |
|
organisational guidelines relating to equipment use, work health and safety (WHS), and accessing and formatting image data and copyright.
|
6A, 6B | 6J, 6K, 6L |
| 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 with 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 simulated workspace environment in line with current industry practices.
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| Candidates must have access to: | |
| computer and software with image enhancement functionality |
All labs have the appropriate computers and software installed. Students will be provided home-use licenses for ESRI ArcGIS and Safe Software Feature Manipulation Engine (FME) |
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organisational policies and procedures relating to: WHS data privacy, copyright, and licensing.
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Students will be required to download the appropriate documents relating to work health and safety (WHS), data and information privacy and/or licensing as part of the training and assessment. |
Other Information
Interim Results
After you have submitted an assessment, you will receive an interim result. This is displayed in the Grades section of this Canvas shell. These will be as follows:
Results |
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Satisfactory (S) |
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Not Yet Satisfactory (NYS) |
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Did Not Submit (DNS) |
You will receive this result when you have not submitted your assessment by the due date or time. Your Trainer/Assessor, the Program Coordinator or the Program Manager cannot overturn this interim result. An approved Special Consideration is required to allow further opportunities to complete the assessment. Additionally, moderation panels cannot overturn this result either. |
Note: You must achieve a Satisfactory (S) result for every assessment in this course in order to pass.
Interim results will inform the moderation panel of their decision as to whether or not you are deemed competent and can pass the course. Your final and official result will be published via My Results on RMIT's website. It is your responsibility to check your final results. Your Trainer/Assessor, the Program Coordinator or the Program Manager will not inform you of your final result.
Resubmission Policy:
After you submit your assessment, your Trainer/Assessor will review your submission. If you have met all the requirements of the assessment task, you will receive an S result in your Grades section of this course.
If the Trainer/Assessor determines that you have not met the assessment requirements, you will receive an NYS result in the Grades section. In this case, your Trainer/Assessor will provide you with the following opportunities to resubmit:
- Project/Practical-Based Assessment Task: One Resubmission per assessment.
- Knowledge-Based Assessment Task (Tests): Two Resubmissions per assessment
Important: If you do not submit an assessment by its due date or time, you are not entitled to a resubmission. You will only receive an opportunity to submit an assessment that you have failed to submit on time if you provide an approved Special Consideration. Your Trainer/Assessor, Program Coordinator & Program Manager or the Moderation panel cannot overturn a DNS result without approved Special Consideration.
*Resubmissions cannot be accepted via email or as attachments to the comments of another assessment. Any work submitted in this manner will not be accepted or recognised, regardless of the circumstances. All resubmissions must be uploaded via the original submission folder and by the due date and time set by the Trainer/Assessor.
**Your Trainer/Assessor, Program Coordinator or Program Manager cannot issue further resubmission opportunities beyond those stated here. You will only be provided with further opportunities based on the successful application for Special Consideration or upon the course moderation panel's review and decision at the course's end.
Attendance:
You are required to attend a minimum of 85% of your classes. If you miss classes, you will need to provide a medical certificate to your Trainer/Assessor for classes that result in you not meeting the 85% requirement.
If you fail to attend the minimum required classes and engage in each class, your trainer/assessor will not accept your assessment submissions. You will be required to attend an in-person interview with your trainer/assessor at a time determined by them. Failure to attend this interview will result in your assessment being rejected. Additionally, the trainer/assessor reserves the right to reject your assessment based on the interview's outcome. This is required to ensure RMIT meets the Standards set for RTOs to ensure the validity of your work.
Course Overview: Access Course Overview