Enhancing urban emergency response: A Euclidean distance-based framework for optimizing rescue facility layouts

Abstract

This study presents a Euclidean distance-based framework for optimizing the layout of urban emergency rescue facilities. Traditional precinct-based (Type 1) and dynamic time-based (Type 2) models are compared with the proposed Euclidean distance-based (Type 3) model. The analysis uses geospatial and statistical methods to evaluate accessibility, variability, and fairness across different times of the day. The results indicate that the Euclidean distance-based model enhances rescue response efficiency and maintains a more equitable service distribution relative to traditional models. The study identifies a “threshold effect” in rescue times, emphasizing the critical distance beyond which rescue efficiency declines. By leveraging real-time traffic data and integrating Euclidean distance principles, the proposed framework offers a robust and practical approach for urban planners to improve emergency response capabilities and urban resilience. This research underscores the importance of considering both geometric proximity and dynamic traffic conditions in the strategic placement of rescue facilities, providing valuable insights for future urban emergency management and planning.