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Satellite Radar Used to Map Subsidence Damage Risk Across New York City Transport Network
A study published in the International Journal of Applied Earth Observation and Geoinformation in early 2026 has used InSAR-derived ground movement measurements to build a probabilistic model of subsidence-related damage risk for transportation infrastructure across New York City. The research, which combined satellite radar displacement data with asset location mapping and geotechnical records, represents one of the most detailed applications to date of satellite geodesy to the question of infrastructure risk quantification at a city scale, and offers a template for how other major urban centres might approach the same problem.
The study drew on displacement measurements extracted from synthetic aperture radar imagery to map rates of ground settlement across the metropolitan area. These measurements were then combined with data on the location, type, and structural characteristics of transport infrastructure including roads, bridges, and subway infrastructure to generate probabilistic estimates of damage risk under different subsidence scenarios. The approach moves beyond simply identifying where the ground is sinking to quantifying what the measured rates of movement are likely to mean for specific categories of built asset over defined time horizons.
The findings add to a growing body of research on subsidence in major cities. A broad review of sinking cities published in a sustainability journal in early 2026 found that subsidence threatens more than 1.6 billion people globally, with several rapidly urbanising cities recording rates exceeding 100 millimetres per year. In the United States, earlier research had established that all 28 of the most populous cities are experiencing measurable subsidence, much of it driven by groundwater extraction, and that more than 29,000 buildings in those cities sit within areas assessed as high or very high damage risk zones.
What the New York study adds is methodological specificity. By using InSAR data as the input for a probabilistic damage model rather than simply as a descriptive tool, the research demonstrates how satellite-derived displacement measurements can be translated directly into risk metrics that are useful to infrastructure managers, city planners, and the insurance and finance sectors. This translation, from physical observation to financial and operational consequence, is a step that much previous satellite monitoring work has stopped short of taking.
The wider significance of the research lies in its scalability. The same methodology, combining publicly available SAR data with asset registries and geotechnical parameters, can in principle be applied to any city or infrastructure network where the underlying data exists. As satellite revisit frequencies increase and processing pipelines become more accessible, the barrier to replicating this kind of analysis across diverse geographies continues to fall.