Automated Evacuation Routing with ArcGIS Network Analyst

Efficient and adaptive evacuation routing is essential for public safety during disasters such as wildfires, floods, and debris flows. Many traditional evacuation planning methods lack real-time adaptability and fail to account for road closures, congestion levels, and network constraints. This project develops an automated evacuation routing model using ArcGIS Network Analyst, integrating geospatial analysis techniques to generate optimized evacuation routes based on user-defined evacuation zones. A web-based application enables emergency managers to define evacuation zones by drawing a polygon, which triggers the routing model to compute optimal evacuation routes in real time. The model incorporates road closures, restricted access roads, and functional classifications to ensure that only available and suitable roads are used for evacuation. By analyzing residential parcel densities within the evacuation zone, the system assigns congestion penalties to road segments, dynamically influencing optimal route selection. The script automatically identifies exit points at the boundary of the evacuation zones where roads provide safe egress, ensuring logical and efficient evacuation paths. The model was tested using a road network dataset for Santa Barbara County to evaluate its effectiveness in real-world scenarios. This framework is scalable and adaptable, allowing emergency managers to tailor evacuation planning for various disaster scenarios and apply the model to different geographic regions and network datasets. By leveraging network analysis, GIS automation, and interactive web mapping, this project enhances disaster preparedness and response efforts, providing a flexible, real-time evacuation planning tool that supports data-driven decision-making and ensures safer and more efficient evacuations.

Publication Details

Journal
UA Campus Repository (The University of Arizona)
Published
2025-01-01
Primary Topic
Evacuation and Crowd Dynamics
Type
article
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article

Automated Evacuation Routing with ArcGIS Network Analyst

UA Campus Repository (The University of Arizona)
Evacuation and Crowd Dynamics
article

Automated Evacuation Routing with ArcGIS Network Analyst

article en

Abstract

Efficient and adaptive evacuation routing is essential for public safety during disasters such as wildfires, floods, and debris flows. Many traditional evacuation planning methods lack real-time adaptability and fail to account for road closures, congestion levels, and network constraints. This project develops an automated evacuation routing model using ArcGIS Network Analyst, integrating geospatial analysis techniques to generate optimized evacuation routes based on user-defined evacuation zones. A web-based application enables emergency managers to define evacuation zones by drawing a polygon, which triggers the routing model to compute optimal evacuation routes in real time. The model incorporates road closures, restricted access roads, and functional classifications to ensure that only available and suitable roads are used for evacuation. By analyzing residential parcel densities within the evacuation zone, the system assigns congestion penalties to road segments, dynamically influencing optimal route selection. The script automatically identifies exit points at the boundary of the evacuation zones where roads provide safe egress, ensuring logical and efficient evacuation paths. The model was tested using a road network dataset for Santa Barbara County to evaluate its effectiveness in real-world scenarios. This framework is scalable and adaptable, allowing emergency managers to tailor evacuation planning for various disaster scenarios and apply the model to different geographic regions and network datasets. By leveraging network analysis, GIS automation, and interactive web mapping, this project enhances disaster preparedness and response efforts, providing a flexible, real-time evacuation planning tool that supports data-driven decision-making and ensures safer and more efficient evacuations.

UA Campus Repository (The University of Arizona)
Climate action
Openalex Percentile: Top 44%
Evacuation and Crowd Dynamics
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Automated Evacuation Routing with ArcGIS Network Analyst · UA Campus Repository (The University of Arizona) (2025) | TGRS Research Map | TGRS