Remote Sensing and Geographic Information Systems have improved considerably over the past decade and geography has become very much richer in digital information. The requirement to build complex applications and simulations has become more urgent with the need to plan for a changing climate, to feed an increasing population and to provide pinpoint marketing analysis for business. Further, spatial data is becoming increasingly easier to access and is being utilised by a wider range of government and research agencies. This course explores a toolbox of conceptual approaches and methods to model and analyse a range of highly complex, often non-deterministic problems. It provides a true enabling technology for the natural sciences and a rich source of computational and representational challenges for the computer sciences. The course exposes students to a range of biophysical and social problems.

Note: Graduate students attend joint classes with undergraduate students but are assessed separately.

On satisfying the requirements of this course, students will have the knowledge and skills to:

Regular attendance and participation in class work is required. Any students who fail to participate in practical sessions on a regular basis but nonetheless submit practical work may be invited to demonstrate that it is their own work. Assessment will be based on:

• Critical review of journal paper or project seminar, expected to show conceptual understanding and a degree of discovery learning (10%; LO 1, 2, 4, 5)
• Research plan (5%; LO 1, 5)
• Research paper (35%; LO 1, 3, 5, 6)
• Lab work (20%; LO 1, 2, 3, 4, 6)
• Exam (30%; LO 1, 2, 3, 4)

65 hours contact comprising 26 hours of lectures, 22 hours of practicals and two days in the field (equivalent to three practicals)

Bachelor degree; general science knowledge.

with GEOG6509 or SRES6509

Chang, K., 2008, Introduction to Geographic Information Systems (fourth ed.), McGraw.