CEG2709 : Satellite Earth Observation
CEG2709 : Satellite Earth Observation
- Offered for Year: 2024/25
- Module Leader(s): Dr Maria-Valasia Peppa
- Owning School: Engineering
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 2 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
| European Credit Transfer System | |
Pre-requisite
Modules you must have done previously to study this module
| Code | Title |
|---|---|
| CEG1706 | Earth Observation |
Pre Requisite Comment
N/A
Co-Requisite
Modules you need to take at the same time
Co Requisite Comment
-
Aims
To enable students deeply understand and learn advance remote sensing technologies, with a focus on satellite sensor characteristics, advanced image processing techniques and real-world applications. To enable students recognise the latest research and developments in remote sensing technology and techniques and gain an insight into applications from across the geosciences and those related to environmental and sustainability challenges.
Outline Of Syllabus
The students enhance their knowledge on advanced considerations of the interactions of electromagnetic radiation with the Earth’s surface and atmosphere. The students learn to describe and understand multispectral, hyperspectral and radar remote sensing as well as to learn field spectroscopy. The students will gain expertise on advanced image processing techniques. The students apply their knowledge on applications of remote sensing in mapping, environmental Earth observation and global change monitoring. Finally the students recognize the challenges and opportunities for remote sensing now and in the future.
Learning Outcomes
Intended Knowledge Outcomes
By the end of the module students will be able to (C1, C2, C3, C4, C12, C13):
•Describe the physical and technological principles behind remote sensing data acquisition and pre- processing, including radar active sensors.
•Explain the image processing and analysis techniques that can be applied to produce both thematic and quantitative remotely sensed data.
•Discuss the applications of remotely sensed data in the geosciences and assess the suitability of different sensors and processing methods for specific applications.
•Assess the current and likely future direction of research and technological development in remote sensing.
Intended Skill Outcomes
By the end of the module students will be able to (C1, C2, C3, C4, C12, C13):
•Demonstrate advanced analytical, numerical and problem solving skills as applied to remote sensing.
•Critically evaluate and review research literature in the field of remote sensing, across a range of application areas.
•Recognise and apply the pathways from remote sensing data acquisition to application, producing data products of value to end-users.
•Use of image processing software to interpret and analyse remote sensing.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 20 | 1:00 | 20:00 | lecture materials |
| Guided Independent Study | Assessment preparation and completion | 1 | 10:00 | 10:00 | Coursework submission |
| Scheduled Learning And Teaching Activities | Practical | 4 | 3:00 | 12:00 | 4 computer-based practicals |
| Guided Independent Study | Directed research and reading | 1 | 20:00 | 20:00 | Lecture follow up |
| Guided Independent Study | Independent study | 1 | 38:00 | 38:00 | Reading-reflective learning |
| Total | 100:00 |
Teaching Rationale And Relationship
Specialist knowledge of sensor types, data acquisition and processing and applications is primarily taught through lectures, supported by practicals developing image processing skills in applied contexts. Development of skills in critical review of remote sensing literature and identification of appropriate processing methodologies will be assisted by a seminar and independent short essay.
Alternative will be offered to students who are unable to be present in person.
Reading Lists
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Written Examination | 90 | 2 | A | 70 | In person exam |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Computer assessment | 2 | M | 15 | 2 Online assessed quizzes via Canvas |
| Report | 2 | M | 15 | 600-word short essay on critical review questions via Canvas |
Formative Assessments
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Computer assessment | 2 | M | 2 Online quizzes via Canvas of the first two practicals. |
Assessment Rationale And Relationship
A formal written examination will be used to assess understanding of lectured theoretical concepts and principles, reviewing development, application as well as image processing methodologies and data analysis, accounting for the majority of summative module assessment (70%).
Progress will be assessed via online Canvas quizzes for the last two practicals (15%). Students will be asked to evaluate two remote sensing publications in a short essay (15%), that way improving critical review skills. The first two practicals will include online Canvas quizzes, for supporting their understanding, but those will not be formally assessed.
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CEG2709's Timetable
Past Exam Papers
- Exam Papers Online : www.ncl.ac.uk/exam.papers/
- CEG2709's past Exam Papers
General Notes
N/A
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The information contained within the Module Catalogue relates to the 2024 academic year.
In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described.
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