Advanced Spatial Analysis, Statistics, and Modelling
explores the theory and application of advanced methods of spatial statistics and analysis. Widely-used and emerging spatial analysis tools are applied to real-world spatial problems, including epidemiology, transportation, infrastructure, conservation, crime analysis, and climatology. Students will identify appropriate spatial analysis methods depending on the subject and type of spatial data, as well as build descriptive and predictive spatial models to investigate spatial patterns and processes. Lab sessions address common spatial techniques using mainstream GIS software.
Prerequisites & course information
LH: 3 PR: GEOG 3260 (or equivalent, with permission of instructor and the Head of Department), GEOG 3222 (or equivalent, with permission of instructor and the Head of Department), Mathematics 2050 (or equivalent, with permission of instructor and the Head of Department), Computer Science 1001 (or equivalent, with permission of instructor and the Head of Department)
Sources
- Course catalogue ↗2026-2027