Postgraduate Course: Hyperspectral Remote Sensing (PGGE11040)
Course Outline
| School | School of Geosciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | The course aims to provide an introduction to hyperspectral remote sensing methods, systems for the collection of data at high spectral resolution and unique approaches and algorithms to the processing of such data. The case is made for the greater use of hyperspectral reflectance data. Taking a bottom-up approach the course will first visit spectral signatures and their collection at the Earth=s surface using instruments and techniques of field spectroscopy, and hyperspectral imaging instruments. Practical exercises will be undertaken in support of these techniques. |
| Course description |
- Week 1
Lectures:
1. Introduction to course, and the case for hyperspectral;
2. Introduction to practicals/assessments
Practical: set seminar assessment
- Week 2
Lectures:
1. An introduction to field spectroscopy
2. The analysis of field hyperspectral data
Practical: The analysis of 3D hyperspectral data
- Week 3
Lectures:
1. Hyperspectral imaging sensors
2. Applications of hyperspectral remote sensing (I)
Practical: The analysis of 3D hyperspectral data
-Week 4
Lecture: Applications of hyperspectral remote sensing (II)
Presentations
- Week 5
Presentations
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
Course Delivery Information
|
| Academic year 2014/15, Available to all students (SV1)
|
Quota: None |
| Course Start |
Block 3 (Sem 2) |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 24,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
74 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Practical assessment 60% due week 3 of block 3
Seminar assessment 40% due week 1 of block 4 |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
By the end of this course, students should have achieved and demonstrated the ability to
- know the basic principles of field spectroscopy and techniques for the collection and analysis of hyperspectral ground-truth data.
- identify the most important attributes for airborne and hyperspectral sensors, and evaluate their characteristics and potential performance.
- identify why calibration is critical and have knowledge of approaches taken to the atmospheric correction of hyperspectral data.
- appreciate how data extraction techniques and hyperspectral algorithms work.
- know the potential application areas for hyperspectral analysis.
- 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.
- plan and write assignments, within the specified parameters and to a professional standard.
- take responsibility for your own learning through reading and the preparation of assignments, and reflect upon your learning experience.
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Reading List
Reading List (more extensive list appears on course handbook)
General remote sensing texts, plus
- Liang, S. (2004) Quantitative remote sensing of land surfaces. Wiley. New Jersey
- Van der Meer, F.D., de Jong, S.M. (2001) Imaging spectroscopy; basic principles and prospective applications. Kluwer. 403 pp.
- Curran, P.J. (1994) Imaging spectrometry. Progress in Physical Geography, 18: 247-266
- Goetz, A.F.H., Curtiss, B. (1996) Hyperspectral imaging of the earth: remote analytical chemistry in an uncontrolled environment. Field Analytical Chemistry and Technology, 1: 67-76
- Asrar, G. (ed.) Theory and Applications of Optical Remote Sensing, Chapter 10, John Wiley and Sons, New York, NY, pp 429-472
- Chang, Ch-L. () Hyperspectral imaging: Techniques for spectral detection and classification. Kluwer Academic, New York. 370pp.
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Contacts
| Course organiser | Dr Alasdair Macarthur
Tel: (0131 6)50 5926
Email: Alasdair.MacArthur@ed.ac.uk |
Course secretary | Miss Lynne Mcgillivray
Tel: (0131 6)50 2543
Email: Lynne.McGillivray@ed.ac.uk |
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