Students gain proven knowledge and understanding with respect to the field of spatial analysis. They are in a position to use the knowledge and understanding acquired in order to solve problems. They are in a position to disseminate information, ideas, problems and solutions to expert as well as non-expert audience.
YES Search, analysis and synthesis of data and information by using necessary technologies.
YES Adaptation to new situations.
YES Decision making
YES Autonomous work
NO Team work
NO Working within an international context.
YES Interdisciplinary work
NO Producing new research ideas.
NO Project planning and management.
NO Respecting diversity and multicultural aspects.
YES Respecting the natural environment
NO Showing social, professional and ethical responsibility as well as sensitivity to sex issues.
YES Applying criticism and self-criticism
YES Promoting free, creative and deductive thinking.
The course focuses on studying phenomena that have spatial dimensions. A brief review of the basic statistical concepts and methods is done. An analysis of the fundamental problems related to spatial data is also included. Advanced analysis and modeling methods are presented. The content of the course is in specific:
1. Introduction in descriptive statistics
2. Linear regression – correlation
3. Factor analysis – principal components analysis
4. Classification and grouping of spatial data
5. Spatial indexes for specializations
6. Local correlation and spatial autocorrelation
7. Pattern analysis (clustering – dispersion)
8. Fundamental problems (MAUP, Ecological fallacy etc)
9. Geographically Weighted Regression
10. Interpolation (points, lines, areas)
11. Geovisualization as an analytical method
12. Urban spatial metrics
13. Cellular Automata
Written examination at the end of the semester.
Pedion Areos, 383 34, Volos
+30 24210 74452-55
+30 24210 74380
g-prd@prd.uth.gr