Probabilistic modeling of InSAR-derived land subsidence hazard in New York City for transportation infrastructure damage risk assessments

Abstract

Land subsidence is a growing geohazard that poses a significant threat to critical infrastructure, particularly in urban coastal cities. This study uses Interferometric Synthetic Aperture Radar (InSAR) data from 2016 to 2024 to estimate angular distortion rates to assess infrastructure damage risk in New York City. We applied a probabilistic framework to evaluate multiple “what-if” scenarios and project long-term risks, providing actionable insights for resilience and mitigation planning. Results reveal persistent subsidence in low-elevation and reclaimed zones (∼-5 mm/yr) with localized uplift (∼+1.5 mm/yr), affecting major airports, subway segments, and highways. Fifty-year projections indicate high angular distortion probabilities (0.6–0.8), with economic exposure estimated at ∼$8.20 billion for ∼ 6.1 km of subway lines and ∼$10.54 billion for ∼ 7.8 km of highways exceeding –2 mm/yr. Despite their limited spatial extent, these segments represent a disproportionately large share of total exposure. The findings emphasize the need for continuous monitoring, proactive mitigation, and targeted investment, highlighting the value of integrating geodetic data with probabilistic modeling to address subsidence and climate-related hazards.