UCL
Department of Geography
University College London
[Educational Aims and Objectives of the Course] [Course workload and assessment] [Timetable 2015-16] [Reading List] [How to run the practicals elsewhere]
To enable the students to:
- Understand the nature of remote sensing data and how they are acquired
- Understand different types of remote sensing instruments and their missions
- Understand basic image representation and processing
- Understand how Earth Observation data can be combined with other sources of data and data techniques (e.g. GIS)
- Understand how EO data can be used in environmental science (particularly via classification and monitoring)
- Develop practical skills in these areas, which may be useful in planning of dissertations
- Develop links with the second year course on Geographic Information Systems Science and with othet courses as appropriate (e.g. hydrology, environmental systems)
- Lay the foundations for the third year course on Earth Observation
| Component | Hours |
|---|---|
| Lectures | 8 |
| Private Reading | 80 |
| Supervised Laboratory Work (Computing) | 24 |
| Independent Laboratory Work (Computing) | 20 |
| Required Written Work | 10 |
| TOTAL | 142 |
Usual range 100-150 for 1/2 course unit
- 100% Assessed Practical (3500 words) - submission date standard 2nd year submission date i.e. Fri 22th March 2019 (12 noon).
N.B.
- Penalties for late submission and over length WILL be applied
- Different arrangements for JYA/Socrates (make sure you inform the lecturers if this affects you)
Lectures in Pearson G07
Computing in Pearson Building, UNIX Computer lab, Pearson 110a
- Jensen, John R. (2006) Remote Sensing of the Environment: an Earth Resources Perspective, Hall and Prentice, New Jersey, 2nd ed.
- Jensen, John R. (1995, 2004) Introductory Digital Image Processing: A Remote Sensing Perspective (Prentice Hall Series in Geographic Information Science)
- Jones, H. G and Vaughan, R. A. (2010) Remote Sensing of Vegetation, OUP, Oxford.
- Lillesand, T., Kiefer, R. and Chipman, J. (2004) Remote Sensing and Image Interpretation. John