Syllabus academic year 2010/2011
(Created 2010-07-25.)
Credits: 7,5. Grading scale: TH. Cycle: A (Second Cycle). Main field: Technology. Language of instruction: The course might be given in English. EXTN75 overlaps following cours/es: GISN01. Optional for: L4gi. Course coordinator: Ola Hall,, Department of Physical Geography. Prerequisites: L: EXTF80/EXTA45 Geographic Information Technology and FMS032 Matematical Statistics, Basic Course; LTH: EXTF01 Geographical Information Systems for Landscape Studies and FMS032 Mathematical Statistics, Basic Course; Science: NGEA12 Geographical Information Systems and NGEA07 Theory and Methods of Physical Geography. The course might be cancelled if the number of applicants is less than 16. The number of participants is limited to 60 Selection criteria: Number of credits. Assessment: Assessment takes the form of a written examination. Approved on all exercises and participation on all compulsory activities. Home page:

The course aims to equip students with fundamental theoretical knowledge and practical skills in the methods of spatial analysis.

Knowledge and understanding
For a passing grade the student must

• explain correlations (relationships) within and between geographical data sets

• interpret, discuss, and apply regression methods using geographic data

• explain and apply geostatistics

• explain scaling issues affecting spatial analysis and geographic data at depth

• generally describe analysis approaches for very large data sets (data mining)

• explain the foundations of the theory behind spatial decision support systems.

Skills and abilities
For a passing grade the student must

• independently analyse and intepret the results from regression models, and

• understand and apply particular spatial analytical methods to geographic data.

Judgement and approach
For a passing grade the student must

• to be able to independently relate to both spatial and conventional statistical measures and methods,

• critically appreciate the nature of geographic data and analytical techniques

• assess the reliability of analyses conducted with different methods.

The course consists of 5 modules:

• regression and other basic methods in statistical modelling

• geostatistics

• scaling issues

• analysis of very large data sets (data mining)

• spatial decison support systems.

Course compendium from the department.