A comprehensive understanding of urban development is critical for moving towards the goal of sustainability. Despite a collection of urban sustainability indicator (USI) conceptual frameworks proposed and explored in practical urban sustainability assessment, establishing an integrated, well-quantified, spatially characterized USI model is still a challenging task. Therefore, based on a manuscript-style format this thesis develops a subjectively weighted integrated USI model and then applies it to the city of Saskatoon, SK, Canada, as a case study, based on quantifying a hierarchical index system. In addition, urban environmental sustainability is spatiotemporally investigated for an improved understanding of Urban Heat Island (UHI) effect. Results show that the proposed integrated USI model improved urban sustainability measurement by overcoming the shortages in existing USI models. Geospatial statistics demonstrated disparity in urban sustainability across residential neighbourhoods for Saskatoon in 2006 based on the significant clusters and outliers. It also found that population increases can possibly improve intellectual and economic well-being and promote urbanization, but may cause environmental degradation and lead to a decline in overall urban sustainability. This research also demonstrates that satellite imagery can be used to study environmental sustainability at different spatiotemporal scales. This research reveals that both urban water and green spaces had significant cooling effects on the surrounding urban LST within specific ranges. Urban surface temperature can be estimated based on a multiple linear regression model with sustainable traveling mode index and land use information as input variables. The overall significance of this research has three folds. First, it lays a preliminary theoretical foundation for a comprehensive understanding of urban sustainability based on a well-quantified integrated USI model. Second, it is relatively original with respect to improving urban sustainability measurements through the incorporation of subjective information into objective data. Third, this research has explored spatiotemporal analysis to detect urban sustainability patterns based on compiling multiple data sources using geospatial techniques. The proposed USI model is highly suitable for comparison analysis at different spatial scales as well as continuously tracking the dynamic changes. Therefore, this research can be a good practice of applying the spatiotemporal philosophy to urban geographical problems.