Mapping Maritime Shocks: AIS Data Uncovers Typhoon Phanfone’s Impact on Philippine Trade

The ADB study uses high-frequency Automatic Identification System (AIS) data to measure how Typhoon Phanfone disrupted Philippine port activity, revealing major declines in ship traffic at key ports like Cebu and Iloilo. It demonstrates that real-time maritime data can revolutionize disaster assessment and strengthen climate resilience in Asia’s coastal economies.

The Asian Development Bank (ADB), in collaboration with its Economic Research and Development Impact Department and Sectors Department 1, has unveiled a groundbreaking study, supported by the Japan Fund for Prosperous and Resilient Asia and the Pacific. The study represents an innovative fusion of economics, data science, and climate resilience research. It uses high-frequency Automatic Identification System (AIS) data to evaluate the real-time disruptions caused by Typhoon Phanfone (Ursula), which devastated the Philippines in December 2019. Conducted by ADB economists Madhavi Pundit and Priscille Villanueva, along with maritime expert R. Duncan McIntosh and consultants Immanuel Sin and Paolo Magnata, the research offers a pioneering framework for rapid, data-driven disaster assessment.

Ports at the Frontline of Climate Disruption

Maritime transport underpins over 80% of global trade, and in an archipelagic country like the Philippines, ports serve as the nation’s lifelines. But their coastal locations make them extremely vulnerable to typhoons. Typhoon Phanfone alone displaced 3.4 million people, stranded nearly 24,000 passengers, and inflicted infrastructure losses of about ₱5.7 billion ($98 million). The storm halted shipping operations, immobilized over 150 vessels, and disrupted supply chains. Traditionally, the Philippines depends on post-disaster needs assessments to quantify damages, a process that can take months. The ADB researchers argue that AIS data can revolutionize this approach by offering near–real-time insights into maritime activity, enabling authorities to assess economic impacts and recovery needs within days rather than months.

Turning Ship Signals into Economic Insights

The AIS, a coastal tracking system mandated by the International Maritime Organization, continuously transmits a vessel’s identity, speed, and location. The ADB study drew from the United Nations Global Platform (UNGP) and IHS Markit databases, covering vessel movements from January 2019 to December 2020. Additional datasets from the World Port Index and International Best Track Archive for Climate Stewardship (IBTrACS) provided detailed port coordinates and the storm’s trajectory. Researchers standardized 1,450 distinct port areas across the Philippines and its top trade partners using a distance-based mapping method. They then measured daily unique ship counts at each port to determine maritime activity before, during, and after the typhoon. To quantify disruptions, the team employed a Bayesian Structural Time Series (BSTS) model, a powerful statistical tool that constructs a synthetic “counterfactual,” estimating what port activity would have looked like had the storm not occurred.

Uncovering the Typhoon’s Hidden Economic Footprint

The BSTS analysis revealed clear patterns of disruption. Major ports in the Visayas, particularly Cebu, Iloilo, and Isabel, suffered severe declines in maritime traffic. Cebu’s daily ship count plunged by 35%, from an expected average of 27 vessels to just 17, while Iloilo registered a 14% decline and Isabel a dramatic 47% drop. These effects were statistically significant, confirming the destructive impact of Typhoon Phanfone on regional trade flows. By contrast, Batangas, Bacolod, and Capiz ports showed no significant change, highlighting the uneven nature of the typhoon’s impact. Interestingly, Manila Port, situated outside the storm’s path, recorded a modest 10% increase in vessel arrivals, likely due to rerouted traffic from affected areas. This adaptive shift in shipping patterns demonstrates the inherent flexibility of maritime logistics networks. The researchers also observed temporary surges in traffic at certain ports following the storm, which they linked to humanitarian relief operations, a sign of how ports transform into critical logistics hubs during recovery efforts.

Building Resilience Through Data and Foresight

The ADB study concludes that AIS data can transform disaster management by allowing policymakers to monitor port activity and supply chain disruptions almost in real time. The authors recommend improving the precision of port boundary definitions and expanding the model to include indicators such as cargo tonnage, vessel dwell time, and frequency of port calls for more comprehensive assessments. They also urge replicating the methodology for other typhoons to strengthen its robustness and establish a scalable framework for Asia and the Pacific. The implications extend far beyond the Philippines: with climate change expected to intensify storms across the region, such data-driven monitoring systems could become essential tools for protecting economic lifelines.

Ultimately, this research situates itself at the crossroads of technology, economics, and resilience. It demonstrates that by harnessing digital vessel data and advanced statistical modeling, nations can anticipate disruptions, direct relief operations efficiently, and design infrastructure investments that withstand future climate shocks. For a country facing an average of twenty typhoons a year, the ability to translate data into actionable insight marks a crucial step toward sustainable recovery. The ADB’s study transforms how we understand disaster impacts, shifting from reactive assessments to proactive resilience, where data becomes the first line of defense against the storms of the future.