A GIS-, and Web-based DDS for Post-Disaster Recovery of Transportation Systems

Abstract: Recent advancements in information technology, along with the availability of big data and cloud computing, have greatly enhanced our ability to collect and analyze data across various aspects of life. This capability is particularly valuable for optimizing decision-making processes in chaotic situations, such as urban recovery following disasters. The transportation network is one of the critical sectors that can leverage these innovations for swift and effective disaster recovery. Decision-makers in this essential field can develop a comprehensive framework that integrates big data from multiple sources to create a valuable decision-making tool. However, despite ongoing research, there is still a notable lack of integrated decision-making tool specifically designed to restore transportation systems after disasters. This study addresses this gap by developing a comprehensive framework to support decision-making in the planning and reconstruction of urban transportation networks post-disaster. The proposed Decision Support System (DSS) framework incorporates Geospatial Information Systems (GIS), cloud computing, and advanced data analysis techniques. The outcomes of this research will enhance decision-making by facilitating real-time and continuous monitoring of conditions and changes over time. By providing timely insights into the state of transportation systems, the DSS will significantly expedite the recovery process, ensuring that urban areas can swiftly regain their functionality and resilience in the aftermath of a disaster.