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Unit information: Spatial Modelling 2 in 2016/17

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Unit name Spatial Modelling 2
Unit code GEOG25010
Credit points 20
Level of study I/5
Teaching block(s) Teaching Block 4 (weeks 1-24)
Unit director Professor. Richard Harris
Open unit status Not open
Pre-requisites

All units in Year 1 Geography programme

Co-requisites

A,B or C Geography Units

School/department School of Geographical Sciences
Faculty Faculty of Science

Description

The unit explores the principles of geographical information science and geographical data analysis focusing on the use of ArcGIS and of R to teach principles of scientific computing, principles of geographical information science, mapping data, using regression to explain what we see on a map, point pattern analysis and spatial regression analysis. A key aim of the unit is to provide quantitative research training suitable for dissertational work, developing skills in computing programming, geographical data handling, mapping and analysis, and in the presentation and interpretation of statistical information.

Intended learning outcomes

On completion of this Unit students should be able to:

Have good knowledge of the foundational principles of geographical information science and of geographical data analysis, with the ability to:

Use command-line programming and scripting to input, manipulate, analyse and visualise data in R;

Undertake statistical analysis to analyse data-sets and interpret the results within a geographical context;

Know the differences between spatial and non-spatial forms of analysis and how to apply them; and

Use GIS to load, display and query geographical databases.

The following transferable skills are developed in this Unit:

  • numeracy
  • computer literacy
  • problem solving
  • analytical skills

Teaching details

A combination of lectures and directed practical work.

Assessment Details

Open-book unseen examination testing knowledge on how to use R, 2 hours, to be held in January. (50%)

Short and essay question examination (not open-book) testing understanding of GIS, regression and spatial data analysis, 1 or 1.5 hours (to be confirmed), to be held in May/June. (50%)

Reading and References

Harris, R. and Jarvis, C. (2011). Statistics for Geography and Environmental Science. London: Prentice Hall.

Lloyd, C.D. (2010). Spatial Data Analysis: an Introduction for GIS Users. Oxford: Oxford University Press.

Venable, W.N., Smith, D.M. & R Development Core Team (2002–). An Introduction to R, Bristol: Network Theory Limited. Available for free at: http://cran.r-project.org/

SUPPLEMENTARY:

Longley, P.A., Goodchild, M.F., Maguire, D.J. & Rhind, D.W. (2011). Geographic Information Systems & Science. New York: Wiley.

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