Urban wind simulations are essential for assessing pedestrian comfort, pollutant dispersion, and microclimate design, yet high-fidelity CFD remains computationally expensive. This thesis investigates the potential of a Swin-Transformer-based surrogate model to approximate steady-state 2D results for 100 m × 100 m tiles under a single inflow direction. A dataset of 690 urban tiles was extracted from the 3DBAG and simulated in Ansys Fluent at 0.5 m resolution across five inflow speeds (5–15 m/s) and five types of building layouts. Velocity fields were rasterized to 1 m grids. The surrogate architecture preserves the original Swin backbone, evaluated with three loss variants: original RMSE, buffer weighting, and a divergence penalty. Encoding wind as xy-component consistently outperformed magnitude-only training. Errors scaled linearly with inflow speed and were highest in Mixed and Attached urban forms. Architectural resolution was the dominant factor influencing accuracy since it introduced visible artifacts, while the buffer and divergence losses offered only marginal improvements. Limitations remain near building facades, where sharp gradients are smoothed by the patch-based architecture. Nonetheless, the surrogate offers potential for rapid wind flow estimation suitable for early-stage design or preliminary analysis.

The Earth's surface is a complex landscape that is essential for a wide range of applications, from urban planning to environmental monitoring. Digital models of the Earth's surface are generated through mathematical calculations using elevation data collected from various sources and the Digital Terrain Model (DTM) which captures the bare earth's surface topography in 2.5D. The creation of DTM is an approximation of terrain in unsample locations, by using x-y coordinates and one z value. Traditionally, terrain interpolation uses deterministic or geo-statistical methods to calculate elevation. This research would use random forest regression as an alternative method and to compare the results against traditional interpolation. Comparing different locations against traditional interpolation yields similar results overall. Feature importance, within the the points that are closest to the sampled ICESat-2 data point are more significant than other features used in Random Forest model. The correlation between these datasets and the spatial relationship established would impact on the results of the elevation. The improvement overall of using traditional interpolation compared to random forest regression is limited depending on the location and using model trained with local datasets. For model trained on other geographical locations, which shows similar differences.

This thesis presents the development of a real-time daylight analysis tool for architectural and urban development using the Unreal Game Engine. The tool offers architects and urban planners a fast and precise way of analysing outdoor daylight conditions in their designs. The Unreal Game Engine provides real-time visualisation and analysis of daylight conditions, which makes it an effective tool for real-time decision-making during the design process. The study compares the light values and the process of extracting these values in Unreal with the validated light model Radiance used in Honeybee & Ladybug in the visual scripting program Grasshopper for Rhino. The thesis compares the values of Unreal & Honeybee/ladybug based on outdoor illuminance values, calculation time and ease of use. The comparison demonstrates the potential of Unreal as a valuable daylight analysis tool, with measurements showing a Mean Absolute Error of 9.78% between Honeybee and Unreal. In terms of computational time, the Unreal application requires only 0.6ms to execute and recalculate the daylight analysis, whereas the complete Honeybee script took an average of 93 minutes to calculate daylight values, and a new angle calculation took approximately 645 seconds. Furthermore, unlike Honeybee, which is sensitive to the complexity of urban or complex geometries and requires challenging adjustments, the Unreal application effortlessly accommodates complex geometry without the need for extensive modification.
The thesis concludes that the tool provides a robust and efficient method for analysing daylight conditions in architectural and urban design. The tool's ease of use and real-time visualisation capabilities make it an essential addition to the design workflow. Finally, the thesis presents the tool as a proof of concept for a geospatial urban development platform with built-in geospatial analysis. The research has demonstrated the potential of real-time simulation and analysis using the Unreal Game Engine as a powerful tool for architects and urban planners.