Modelling solar radiation data at a high spatiotemporal resolution for an urban environment can inform many different applications related to climate action, such as urban agriculture, forest, building, and renewable energy studies. However, the complexity of urban form, vastness of city-wide coverage, and general dearth of climatological information pose unique challenges doing so. To address some climate action goals related to reducing building emissions in the City of Victoria, British Columbia, Canada, applied geomatics and climatology were used to model solar radiation data suitable for informing renewable energy feasibility studies, including photovoltaic system sizing, costing, carbon offsets, and financial payback. The research presents a comprehensive review of solar radiation attenuates, as well as methods of accounting for them, specifically in urban environments. A novel methodology is derived from the review and integrates existing models, data, and tools – those typically available to a local government. Using Light Detection and Ranging (LiDAR), a solar climatology, Esri’s ArcGIS Solar Analyst tool, and Python scripting, daily insolation (kWh/m2) maps are produced for the city of Victoria. Particular attention is paid to the derivation of daily diffuse fraction from atmospheric clearness indices, as well as LiDAR classification and generation of a Digital Surface Model (DSM). Novel and significant improvements in computation time are realized through parallel processing. Model results exhibit strong correlation with empirical data and support the use of Solar Analyst for urban solar assessments when great care is taken to accurately and consistently represent model inputs and outputs integrated in a methodological approach. / Graduate