Postgraduate Course: Further Spatial Analysis (PGGE11085)
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 | This course explores further methods for the analysis of geographical data. Building on ideas from the introductory module, this course begins by examining fuzzy and probabilistic models for representing uncertainty in geographical data. Various methods for interpolating point data to create surfaces are then considered, including kriging which is introduced through a discussion of geostatistical concepts such as variograms and isotropy. Methods for the detection of clustering within point data sets are then studied, with particular reference to the problem of finding 'hotpots'. Methods are illustrated through real-world use cases. The latter part of the course uses a combination of guest speakers and student seminars to explore more advanced methods such as areal interpolation, geographically weighted regression and microsimulation. Students undertake their own investigation of one specific method and present their findings in a seminar in the final week of the course. |
| Course description |
Draft Syllabus:
Week 1
Lecture: Fuzzy and probabilistic models of uncertainty
Practical: Map Comparison Toolkit
Week 2
Lecture: Clustering in geographical data
Practical: Hotspot mapping using Crimestat
Week 3
Lecture: Spatial Interpolation
Practical: Interpolation using Geostatistical Analyst
Week 4
Lecture: Geographically weighted regression
Practical: GWR
Week 5
Student seminar presentations
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
It is RECOMMENDED that students have passed
Introduction To Spatial Analysis (PGGE11091)
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | It is RECOMMENDED that students have passed Introduction to Spatial Analysis (PGGE11091) |
Course Delivery Information
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| Academic year 2014/15, Available to all students (SV1)
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Quota: None |
| Course Start |
Block 4 (Sem 2) |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 12,
Seminar/Tutorial Hours 12,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
74 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Clustering Practical (40%) deadline week 9
Interpolation Practical (40%) deadline week 10
Oral Seminar Presentation (20%) deadline week 10 |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
By the end of this module, students should have achieved and demonstrated, or be able to achieve and demonstrate, the ability to:
- Be familiar with each of the methods introduced in the lectures for the analysis of spatial data and understand when it is appropriate to use each;
- Be able to carry out some of these methods using GIS;
- Understand the concepts and principles on which the methods are based, and be aware of their assumptions, value and limitations;
- Have awareness of the application areas where the methods are used;
- Locate, read and summarise relevant literature, from both traditional and electronic media, to extend their understanding of the lecture material
- Independently research a further method of spatial analysis not covered in the taught lectures;
- 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 their own learning through reading and the preparation of assignments, and reflect upon their learning experience.
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Reading List
Recommended basic or preparatory reading:
Bailey, T.C. and Gatrell, A.C. (1995). Interactive spatial data analysis.
Birkin, M., Clarke, G., Clarke, M. and Wilson, A. (1995) Intelligent GIS: Location Decisions and Strategic Planning. Geoinformation International, Cambridge.
Bonham-Carter, G. (1994) Geographic information systems for geoscientists: modelling with GIS. Pergamon, Oxford, 398pp.
Clarke, G and Stillwell, (2004) Applied GIS and Spatial Analysis. Wiley.
Burrough, P.A and McDonnell, R.A (1998) Principles of geographical information systems. Clarendon Press, Oxford. For geostatistics, errors and fuzzy sets, read chapters 5, 6 and 8-11.
Chainey, S and Radcliffe, J (2000) GIS and Crime Mapping. Wiley.
Crimestat III User Manual http://www.icpsr.umich.edu/CrimeStat/
Fischer, M. Scholten, H.J and Unwin, D. (1996) Spatial analytical perspectives on GIS. Taylor and Francis, London.
Fotheringham, S. Brunsdon, C and Charlton, M (2000) Quantitative Geography: perspectives on spatial data analysis. Sage.
Fotheringham, S. Brunsdon, C and Charlton, M (2002) Geographically weighted regression: the analysis of spatially varying relationships. Wiley.
Haining, R. (2003) Spatial Data Analysis: Theory and Practice. CUP.
Lam, N.S. (1983) Spatial interpolation methods: a review. American Cartographer 10: 129-49.
Map Comparison Toolkit 3.0 (2006) http://www.riks.nl/mck/
Longley, P.A. and Batty, M. (eds.) (2003) Advanced Spatial Analysis - The CASA book of GIS. ESRI Press, Redlands. California.
Longley, P.A., Goodchild, M. F., Maguire, D.J. and Rhind, D. W. (eds.) (1999) Geographical Information Systems (Vol 1: Principles and Techniques, Vol 2 Management and Applications). Wiley.
Longley, P.A., Goodchild, M. F., Maguire, D.J. and Rhind, D. W. (eds.) (2005) Geographical Information Systems: Principles, Techniques, Management and Application (abridged edition). Wiley.
O'Sullivan, D. and D. J. Unwin (2003 or 2010) Geographic Information Analysis. Wiley, New York.
Openshaw, S. (1991) Developing appropriate spatial analysis methods for GIS. In Maguire, D. J., Goodchild, M. F. and Rhind, D. W. (Eds.) GIS: Principles and Applications, Vol. 1, Chapter 25, pp. 389-402. Longman.
Visser H and T. de Nijs, 2006. The Map Comparison Kit. Environmental Modeling & Software 21, 346-358.
Webster, R and Oliver, M.A (1990) Statistical methods in soil and land resources survey. Oxford, OUP. 316p.
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Additional Information
| Course URL |
http://www.geos.ed.ac.uk/ |
| Graduate Attributes and Skills |
Not entered |
| Keywords | PGGE11085 exploratory spatial data analysis; spatial interpolation; GIS |
Contacts
| Course organiser | Dr Neil Stuart
Tel: (0131 6)50 2549
Email: N.Stuart@ed.ac.uk |
Course secretary | Miss Lynne Mcgillivray
Tel: (0131 6)50 2543
Email: Lynne.McGillivray@ed.ac.uk |
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