Quantifying the impact of Typhoon Phanfone on Philippine port activity using automatic identification system data - Madhavi Pundit; Immanuel Sin; Paolo Magnata; R. Duncan McIntosh; Priscille Villanueva (Asian Development Bank (ADB), 2025)
The automatic identification system (AIS) is a short-range coastal tracking system used to identify ships and their speed and location worldwide. This case study leverages high frequency AIS data to analyze the impact of typhoons on port activity in the Philippines. Maritime transport plays a pivotal role in facilitating trade and transportation of goods and passengers in an archipelago like the Philippines. The Philippines typically encounters 20 tropical cyclones each year, with significant impacts on port operations and economic activity. We study Typhoon Phanfone (known in the Philippines as Typhoon Ursula) that hit the Philippines in December 2019. Disruptions in maritime activity based on daily ship traffic were measured using AIS data over a 2-year period for the Philippines and its top trade partners. A Bayesian structural time series model was employed to build a counterfactual for quantifying the impact of Typhoon Phanfone on specific Philippine ports. This analytical framework that harnesses the potential of AIS data provides policymakers and stakeholders with a tool for near real-time impact assessment that informs planning regarding port operations, scheduling, and resource allocation, and can feed into medium-term disaster risk management decisions.
Keywords: C11; C32; C55; Q54; 330; AIS data; daily ship traffic; Bayesian structural time series model