Postgraduate Course: Earth Observation, Platforms, Sensors and Analytical Methods (PGGE11315)
Course Outline
| School | School of Geosciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course will provide the very latest and the next generation of passive and active sensing for environmental monitoring and spatial sampling, with an emphasis on the use of analytical methods for a broad range of scientific applications. This will be done via application-based learning and hands on computer practicals, in a strongly supported classroom and lab environment. |
| Course description |
The course provides an overview of how remote sensing systems operate, the advantages and disadvantages of a full range of EO methods (LiDAR, RADAR, multispectral and hyperspectral) and platforms (field-based, UAV, airborne and space-based). The course examines the range of ways in which EO systems are used across various applications with a focus on the use of small UAV platforms and their flight control systems: inertial management units (IMU); GPS, and flight aspect and position logging systems. The H&S and regulatory framework for operation of UAV. You will also learn about the additional challenges of using miniature imaging system and radiometers on UAVs and the post processing and analysis of high spatial resolution (sub decimetre) imagery acquired using these sensors. The course also, introduces the principles of field spectroscopy and hyperspectral EO and techniques for the collection and analysis of hyperspectral data across a range of scientific disciplines
Consideration is given to issues of data quality, accuracy, validation and reliability, when assessing the value remotely sensed data. Further familiarising you with some of the key elements of data handling, future methods remote sensing.
The course will consist of 11 four-hour sessions combining lecture/tutorial and practical sessions. The typical format will be a 1-1.5hour lecture followed by practical sessions, and followed by student led discussion/reading. This is not a rigid structure and will vary slightly from week to week. Formative and summative feedback will be provided throughout the course.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2026/27, Not available to visiting students (SS1)
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Quota: 40 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 11,
Supervised Practical/Workshop/Studio Hours 33,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
152 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
100% CW«br /»
Assessment 1: Image analysis/classification (ML) using chosen passive dataset from options 2000 words (40% of CW) «br /»
Assessment 2: Critical seminar (in groups) of chosen passive/active topic 20 minute seminar run as mini symposium in week 5 (20% of CW) , «br /»
Assessment 3: LiDAR practical intersecting with radar from chosen data set options 2000 words (40% of CW) |
| Feedback |
Formative feedback is given verbally, and in writing, throughout the course. Summative written feedback is given in all submissions. A Q&A session is run throughout the course for students to gain active real time feedback in class time and during practicals. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Have an advanced understanding of both passive and active (including LiDAR and RADAR) data streams, their relevance and the advantages and disadvantages of each.
- Understand the acquisition, processing and analytical methods of multi-platform passive and active data.
- Have extensive practical skills and a range of advanced analytical EO techniques and understand the advantages and disadvantages of each of these.
- Locate, read and summarise relevant literature, from both traditional and electronic media, to extend your understanding of the topic.
- Develop reasoned arguments, firmly grounded in the available literature.
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Reading List
Anderson, K. and Gaston, K. (2013) Lightweight unmanned aerial vehicles will revolutionize spatial ecology. Frontiers in Ecology and the Environment 11: 138-146.
Agisoft PhotoScan User Manual Professional Edition, Version 1.1 « www.agisoft.com/pdf/photoscan-pro_1_1_en.pdf »
Berni, J. Zarco-Tejada, P., Suárez, L. and Fereres, E. (2009) Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle. IEEE Transaction on Geosciences and Remote Sensing. 47, 3, 722 - 738.
Colomina, I and Molina, P. (2014) Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing 92, 79-97.
Hardin. P. and Jensen, R. (2011). Unmanned Aerial Vehicles in Environmental Remote Sensing: Challenges and Opportunities, GIScience & Remote Sensing, 48:1, 99-111.
James. M. and Robson, S. (2014) Mitigating systematic error in topographic models derived from UAV and ground-based image networks. Earth Surf. Process. Landforms 39, 1413-1420
Kuenzer, C. and Dech, S. (eds) (2012) Thermal Infrared remote sensing: sensors, methods and applications. Springer DOI 10.1007/978-94-007-6639-6. Particularly Chapters 1 and 4.
Lillesand, T.M., Kiefer, R.W. and Chipman, J.W. (2004). Remote sensing and image interpretation. Wiley, New York, 4th edition or later in particular Chapters 2 (section on digital images), 3, 4 and 8.
Milton, E.J., 1987. Principles of field spectroscopy. International Journal of Remote Sensing, 8, 1807-1827.
Milton, E.J., Schaepman, M., Anderson, K., Kneubuhler, M. and Fox, N. (2009). Progress in field spectroscopy. Remote Sensing of Environment, 113, S92-S109.
Schaepman-Strub, G., Schaepman, M.E., Painter, T.H., Dangel, S. and Martonchik, J.V. (2006). Reflectance quantities in optical remote sensing-definitions and case studies. Remote Sensing of Environment, 103, 27-4
I.H. Woodhouse, Introduction to Microwave Remote Sensing. (Taylor and Francis, CRC Press, 2005) (Radar chapters only)
I.H. Woodhouse, Thirteen Short Chapters on Remote Sensing. (Currently only available as an eBook from Amazon, 2013)
W. Wagner, A. Ullrich, V. Ducic, T. Melzer, N. Studnicka (2006) Gaussian decomposition and calibration of a novel small-footprint full-waveform digitising airborne laser scanner, ISPRS Journal of Photogrammetry & Remote Sensing 60:100 112.
Clément Mallet , Frédéric Bretar (2009) Full-waveform topographic lidar: State-of-the-art,
ISPRS Journal of Photogrammetry and Remote Sensing 64, 116t. |
Additional Information
| Graduate Attributes and Skills |
This course will provide the students with a range of highly marketable skills and introduce them to technologies sought after by employers. These technical skills relate closely to the employment opportunities identified by our Industrial External Examiner, professional bodies and graduate feedback. The students also gain skills in logical thinking, project work, organisation and report-writing. |
| Keywords | Passive earth observation,active earth observation,LiDAR,RADAR,machine learning,UAV,aircraft |
Contacts
| Course organiser | Prof Caroline Nichol
Tel: (0131 6)50 7729
Email: Caroline.Nichol@ed.ac.uk |
Course secretary | Ms Felicity Smail
Tel:
Email: Felicity.Smail@ed.ac.uk |
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