Spatial Data Analysis GISE 5208D

Course description:

The course provides an introduction to the spatial analysis related to both of raster data and vector data. This includes interpolation methods and techniques. The course covers the functions that are used for the analysis of vicinity, neighborhood, and overlay. The course also provides an introduction to geostatistical analysis. All are presented with emphasis on the potential applications of the functions and processes.

Course Aims:

  • Provide students with background to spatial analysis.
  • Enable students to filter maps; weighting linear combination of maps. Constraint mapping and suitability analysis, weighting of evidence, standardization; trade-off and exclusion.
  • Assist in site selection with Boolean and continuously classified data.

Course outcomes:

Upon completion of this course, the student should be able to: 
  •  Understand the basic properties of spatial data. 
  •  Understand the main types of spatial data, the main geometrical frameworks which can be used in analyzing 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.