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The course provides an introduction to remote sensing (RS) and environmental modelling, with the aim of enabling the student to make practical use of RS data for topics such as land cover mapping and use those data in a practical situation. The course is very practical in nature and assumes no prior understanding RS, modelling, or the computing required to process data. A range of RS activities are covered: measurement from space sensors; understanding the properties of the data; basic image processing; and using the data in environmental science. Computer based practicals are an integral part of the course and extend the lecture material. There is an extended environmental science practical exercise encouraging links between this and other courses.

The course aims to enable the student to:
1. Understand the nature of RS data and how they are acquired.
2. Have some knowledge of the different types of RS instruments.
3. Understand basic image representation and processing.
4. Understand how RS data can be combined with other sources of data and data techniques (eg GIS)
5. Develop practical skills in these areas that may be used in a dissertation.


Lecture topics covered: basics of an RS system; different types of instruments; different domains of information; the properties of radiation; image representation; image processing; environmental modelling; introduction to extended practical. Lectures in the first half of term are supported by practicals where the students apply the understanding gained in the lectures to topics such as mapping forest changes in Brazil.
see: https://geog0027-environmental-remote-sensing.readthedocs.io

Most of the second half of the course will be taken up with an extended practical (linking satellite observations of urban area to a simple land use change model). The write-up on this will form the entire assessment. Practical exercises will use a combination of IDL/ENVI and R programming on Unix workstations or your own computer.
see: https://geog0027-coursework.readthedocs.io Computer practical exercises will form a large portion of the course to provide back up to your learning from the lectures. You will also undertake an extended practical for coursework involving extracting information from remote sensing data and using it to calibrate an environmental model.

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