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DRPS : Course Catalogue : School of Geosciences : Postgraduate Courses (School of GeoSciences)

Postgraduate Course: Introduction To Spatial Analysis (PGGE11091)

Course Outline
SchoolSchool of Geosciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThe course provides an introduction to some of the fundamental concepts and concerns of spatial analysis, which are taught through lectures and practical work.

The main topics covered include: a background to spatial analysis in Geography; a short discussion of what is special about spatial data; spatial autocorrelation; modifiable areal unit problem; basic geometrical frameworks for describing and analysing phenomena in space; distance metrics; gridded space; overlay analysis; suitability analysis; Boolean and continuous classification; networks; shortest path through a network; errors and uncertainty in geographical data.

Examples will be drawn from various domains of physical and human geography including urban geography, the geography of transport and urban planning.
Course description Week 1
Lecture: Brief history of spatial analysis in geography. What is special about spatial data? Spatial Autocorrelation. Modifiable Areal Unit problem. Concepts of space and distance: 'absolute' and 'relative' space; continuous and discrete spaces.

Week 2
Lecture: A typology of spatial analytical methods based on point, line, polygon and gridded types of data. Transformations. Map Algebra.
Practical: Cost surfaces and routing by cost minimisation. Example of planning a cycle route.

Week 3
Lecture: Sieve mapping; weighted linear combination of maps. Constraint mapping and suitability analysis; weighting of evidence; standardisation; trade-off and exclusion. Site selection with Boolean and continuously classified data.

Week 4
Lecture: Network analysis and routing problems. Form and function in networks; Murray's law. Introducing topology and graph theory; network connectivity; shortest path through a network
Practical: Network Analysis using ArcGIS.

Week 5
Error and uncertainty in spatial data. Accuracy and precision for spatial data. Sources of error. Error propagation. Representing and handling error. Fuzzy tolerances and fuzzy objects.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2015/16, Available to all students (SV1) Quota:  40
Course Start Block 1 (Sem 1)
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 )
Assessment (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Additional Information (Assessment) 50% practical project (due week 6)
50% examination (one hour; answer one essay question from a choice of four)
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)Introduction To Spatial Analysis1:00
Learning Outcomes
By the end of this module, students should have achieved and demonstrated, or be able to achieve and demonstrate, the ability to:
* Understand the basic properties of spatial data that sometimes require it to be analysed differently to non-spatial data
* Understand the main types of spatial data, the main geometrical frameworks which can be used in analysing spatial data plus their main assumptions and limitations
* Be familiar with the more common methods used in the statistical analysis of spatial data which are applicable to point, line and areal data and understand the assumptions involved in their use
* Implement some of these techniques in practice in a GIS context
* Understand the basic concepts, elements and methods taught in the module and be aware of their assumptions, implications, value and limitations
* Have awareness of the application areas where these methods are used
* Locate, read and summarise relevant literature, from both traditional and electronic media, to extend their understanding of the topics included
* 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.
Reading List
References (* recommended textbooks)
Anselin, L. (1989) What is special about spatial data? NCGIA Technical Paper, 89-4. Also in pp. 63-77 of Griffith, D.A. (1990) Statistics, Past, Present and Future. Ann Arbor Institute of Mathematical Geographers.
* Bailey, T. C. and Gatrell, A. C. (1995) Interactive Spatial Data Analysis. Longman, London.
Batty, M. and Longley, P. (1996) Spatial Analysis: Modelling in GIS Environments. GeoInformation International, Cambridge.
Berry, J. K. (1987) Fundamental operations in computer assisted map analysis. IJGIS, 1, 2, 119-136.
Berry, J. K. (1988) Computer assisted map analysis: Potential and pitfalls. Photogrammetric Engineering and Remote Sensing, 53, 10, 1405-1410.
Birkin, M., Clarke, G., Clarke, M. and Wilson, A. (1995) Intelligent GIS: Location Decisions and Strategic Planning. Geoinformation International.
*Burrough, P.A and McDonnell, R.A (1998) Principles of geographical information systems. Clarendon Press, Oxford.
Carver, S (1991) Integrating multicriteria evaluation and GIS. IJGIS 5, 321-39.
*Chrisman, N. (1997) Exploring geographic information systems. Wiley.
*DeMers, M.N. (2002). GIS modelling in raster. New York, Wiley.
* deSmith, Longley P.A. and Goodchild M.F. (2011) Geospatial Analysis - a comprehensive guide.
Eastman, J.R. (2005) Multicriteria evaluation and GIS. Chapter 35 in GIS - principles, techniques, management and applications, Longley, P.A. M.F. Goodchild, D.W. Rhind, and D.J. Maguire (eds). Wiley.
Fischer, M. Scholten, H.J and Unwin, D. (1996) Spatial analytical perspectives on GIS. Taylor and Francis, London.
Fotheringham, A. S. and Rogerson, P. (1994) GIS and Spatial Analytical Problems. IJGIS 7 (1), 3-20.
Fotheringham, A. S. and Rogerson, P. (1994) Spatial Analysis and GIS. Taylor & Francis, London.
Gatrell, A. C. (1991) Concepts of space and geographical data. In Maguire, D. J., Goodchild, M. F. and Rhind, D. W. (Eds.) Geographical Information Systems: Principles and Applications, Vol. 1, Chapter 9, pp. 119-134. Longman, Harlow.
Getis, A. and Boots, B. (1978) Models of Spatial Processes: An Approach to the Study of Point, Line and Area Patterns. Cambridge University Press.
Goodchild, M. (1987) A spatial analytical perspective on GIS. International Journal of Geographical Information Systems, 1, 327-334.
Goodchild, M. F., Gopal, S. (1989) Accuracy of Spatial Databases. Taylor & Francis. London.
Haining, R. (2003) Spatial Data Analysis: Theory and Practice. Cambridge University Press.
Heuvelink, G.M. (1998) Error propagation in environmental modelling with GIS. Taylor and Francis, London.
*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. and Rhind, D. (2005) Geographic Information Systems and Science. (2nd edition) Wiley. Chaps 14 and 15
*Longley, P.A., Goodchild, M. F., Maguire, D.J. and Rhind, D. W. (eds.) (1999) Geographical Information Systems (2 Vols) (2nd edition).
Section C on 'Spatial Analysis' in Vol 1 is recommended reading.
*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.
*Maguire, D. J., Goodchild, M. F. and Rhind, D. W. (Eds.) (1991) Geographical Information Systems: Principles and Applications (2 Vols.). Longman. Volume 1 may be still online at
(a) Chrisman, N. The error component of geographic data. Ch. 12.;
(b) Gatrell, A. C. Concepts of space and geographical data. Ch. 9;
(c) Openshaw, S. Developing appropriate spatial analysis. Ch 25;
(d) Tomlin, C. D. Cartographic modelling. Ch. 23;
Mennis J, Hultgren T (2006) Intelligent dasymetric mapping and its application to areal interpolation. Cartography and Geographic Information Science, 33, 179-194
*O'Sullivan, D. and D. J. Unwin (1st edn. 2003 or 2nd edn. 2010) Geographic Information Analysis. Wiley, New York
Openshaw, S. and Taylor, P. (1981) The modifiable areal unit problem. Concepts and Techniques in Modern Geography (CATMOG), 38. Geo Abstracts, Norwich, England. Download pdf from
Tomlin, C. D. (1990) Geographical Information Systems and Cartographic Modelling. Prentice-Hall, New Jersey.
Unwin, D. J. (1981) Introductory Spatial Analysis. Methuen, London.
Zhang, J and Goodchild, M.F. (2002) Uncertainty in Geographic Information. London, Taylor & Francis.
Additional Information
Course URL
Graduate Attributes and Skills Not entered
Additional Class Delivery Information Practical Session 16:00-18:00 in room 1.26 Geography, Drummond Street
KeywordsPGGE11091 Spatial analysis,spatial data,spatial autocorrelation,network spaces,GIS
Course organiserDr Neil Stuart
Tel: (0131 6)50 2549
Course secretaryMr Edwin Cruden
Tel: (0131 6)50 2543
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