Identifying and analyzing barriers to ship-based evacuation planning using AIS data
研究利用船舶自动识别系统（AIS）数据改进沿海社区疏散规划，识别出政府限制、培训教育和文化敏感性是主要障碍，为孟加拉湾难民营地提供战略框架。
Coastal communities face distinct challenges in disaster response and crisis management, shaped by their unique geographical and demographic characteristics. This study departs from traditional emergency evacuation ideas by highlighting the use of Automatic Identification System (AIS) ship tracking data to improve evacuation planning for coastal populations. There remains a limited understanding of the barriers hindering humanitarian organizations (HOs) from fully integrating this technology into coastal community planning. This is evident in the scarce literature on the subject, with only one study exploring the feasibility of evacuation planning using AIS data. To examine the barriers to the adoption of AIS-based evacuation planning, Leavitt’s Diamond model was used as a conceptual framework. A mixed-method approach was employed to identify and analyze these barriers. Bhasan Char, a small island in the Bay of Bengal, serves as the research context for this study. The island is vulnerable to weather events, posing safety risks to its population of approximately 30,000 Rohingya refugees who fled from Myanmar. The study uniquely identifies governmental restrictions, training and education, and cultural sensitivity as primary drivers, emphasizing their critical role in shaping effective evacuation efforts. For instance, reforms to governmental restrictions are particularly pivotal, as they profoundly influence systemic challenges, including lack of coordination, policy ambiguity, absence of standard operating procedures, resource allocation inefficiencies, and emergency response limitations. By focusing on these primary drivers, this research provides a strategic framework for enhancing the effectiveness of evacuation planning efforts using AIS technology.