Urban Simulation as a Data-Driven Decision-Making Tool: Analyzing the Spatial Performance of Badr City in Egypt Using SLEUTH Model

Traditional urban planning approaches have recently witnessed many struggles in anticipating the impact of policy shifts, economic changes and social dynamics on the performance of cities. In this context, a data-driven decision-making approach is considered as a critical method in shaping urban policies that manage cities' spatial performance. The paper investigates utilizing SLEUTH simulation model as a tool for data-driven decision making in the field of urban management. The study applied SLEUTH model on Badr city in Egypt as a case study for New Egyptian cities, where many of them faced challenges in achieving the desired rates of urban development through the past years. The study is structured into two main parts, the theoretical framework that investigates the significance of data driven decision making approach and the use of computational tools in the field of urban planning and the empirical part that details the methods used in the research including input data and calibration stages for two SLEUTH modeling scenarios: Scenario A: which utilized basic input data for the model to act as a baseline simulation, and scenario B where policy related factors are integrated such as the proximity to the New Administrative Capital and the establishment of Light Rail Transit Stations within the city. The results showed significant differences between the two scenarios, which highlighted the importance of integrating policy related factors in urban simulation models for more reliable results. The study concluded that incorporating updated computational and simulation tools has a significant effect on enhancing the process of setting management strategies for the modern dynamic urban contexts and highlighted the importance of adopting adaptive urban planning frameworks that respond to the evolving spatial performance of cities.