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This course provides an introduction to a range of statistical techniques used in the analysis of spatial data. A comprehensive lab programme uses a variety of software packages to explore visualisation, exploratory spatial data analysis, spatial autocorrelation, point pattern analysis, spatial statistics and the modifiable areal unit problem (MAUP).
Nau mai ki GISC404-STAT450 - welcome to GISC404-STAT450. This course provides an introduction to a range of statistical techniques used in the analysis of spatial data. It will cover the basic concepts and techniques of spatial data analysis (SDA) and provide a wide range of applications examples from various fields such as geology, demographics, epidemiology and environmental sciences. A comprehensive lab programme uses a variety of software packages (including ArcGIS, Geoda, geoR) to explore and analyse spatial data using the techniques taught in the course.
After completing this course, you are expected to be able to:Know the range of statistical techniques used in the analysis of spatial dataUnderstand issues in analysing spatial dataApply basic statistical and spatial analysis methods to simple research questionsBe confident in utilising a range of software packages for analysing spatial dataExplore, describe and model spatial dataAdequately present spatial analytical research
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Critically competent in a core academic discipline of their award
Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
Biculturally competent and confident
Students will be aware of and understand the nature of biculturalism in Aotearoa New Zealand, and its relevance to their area of study and/or their degree.
Globally aware
Students will comprehend the influence of global conditions on their discipline and will be competent in engaging with global and multi-cultural contexts.
Subject to the approval of the Programme Director. RP: GEOG205 or GISC422, GEOG323
GEOG205 or GISC422, GEOG323
12 hrs lectures (6 x 2 hour lectures)9 hrs labs (3 x 3 hour labs)129 hrs self-study and project work (lab reporting, article reviews, take home assignment)
Ioannis Delikostidis and Elena Moltchanova
There are no prescribed books for this course however all of the topics covered in the course are included in the four texts listed below. Please refer to these books when sourcing reading material for each topic in addition to the ‘Selected Reading’ lists provided. • O’Sullivan, D. & Unwin, D. (2014). Geographic Information Analysis (2nd ed). London: John Wiley.• Grekousis, G. (2020). Spatial analysis methods and practice: describe - explore - explain through GIS (Ebook). Cambridge University Press.• Illian, J., Penttinen, A., Stoyan, H. & Stoyan D. (2008). Statistical Analysis and Modelling of Spatial Point Patterns. Wiley• Bivand R., Pebesma E. & Gomez-Rubio V. (2008). Applied Spatial Data Analysis with R (Use R). Springer
Learn - for all online course materials See the Masters in GIS website for further information
Domestic fee $1,084.00
International Postgraduate fees
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see School of Earth and Environment .