451-331 Spatial Analysis

620-160 Experimental Design and Data Analysis, 451-208 Computational Methods in Geomatics (or equivalent subjects).

At the conclusion of this subject the student should have an understanding of the role of statistical and geometric techniques of spatial analysis for users of geographic information systems (GIS); an understanding of the computational methods of analysis of spatial relationships; and proficiency in the analysis and evaluation of spatial data.

Content includes spatial data types; spatial data structures; point patterns; measures of dispersion; measures of arrangements; patterns of lines; paths, branching, topology and concepts of distance; patterns of area; coverage, assignment, partitioning, spatial scale and spatial aggregation problems, integration of data from various sources, concepts of space; exploratory spatial data analysis; and spatial autocorrelation.

One 3-hour written examination, plus assignments and practical exercise reports totalling not more than 40 pages. The relative weighting of the assessment components will be provided to students at the beginning of the subject.