This thesis examines links between environmental conditions and the socio-economic and demographic determinants of Chronic Obstructive Pulmonary Disease (COPD) in Christchurch, New Zealand. COPD is a progressive condition characterised by reduction in lung function and limited mobility. Tobacco smoking and exposure to air pollution are considered the main causal factors. COPD is the fifth leading cause of mortality globally, and is projected to become the third by 2030. Geographic Information Systems serves a vital role in furthering understanding of the spatial patterns of the condition, and the prevalence of associated variables across space. The aim of this thesis is to engage GIS tools to assess the spatial and temporal patterns of COPD hospitalisation events in relation to air pollution distribution, based on land-use regression modelling, and associated socio-economic variables. To test for the effects of these socio-economic variables, census data was included relating to deprivation levels, and percentages of Maori/Pacific Islanders, smokers and elderly of the population at meshblock and area unit levels. Temporal analysis sought to find correlation between monitored particulate matter, hospitalisation rates and the temperature and wind speed patterns that may affect this. Geographic Weighted Regression (GWR) models found that higher hospitalisation rates were spatially correlated with meshblocks containing high predicted air pollution and deprivation. Maori/Pacific Islander and smoking percentages were moderately associated with hospitalisation event distribution. Temporally, it was found that hospitalisation events occur most predominately in periods of high pollution, lower temperatures and still wind conditions. This thesis is the first research to include spatial and temporal techniques to explore COPD hospitalisation patterns in Australasia.