Long-Span Bridge Inspection Prioritization
Long-span bridge assessment prioritization. Bridges in orange should be some of the first to be inspected, whereas bridges in yellow are of medium priority, and bridges in green are the lowest prioirity.
NASA-sponsored scientists have developed a way to assist long-span bridge inspectors prioritize which bridges should be inspected before others. This research contributes to a comprehensive global risk assessment framework for long-span bridges by evaluatiing their vulnerability to slow-moving geo-hazards, such as land subsidence and landslides. By integrating spaceborne monitoring capabilities—specifically Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR)—with traditional in-situ Structural Health Monitoring (SHM) sensors, the study demonstrates a significant reduction in the epistemic uncertainty surrounding structural integrity. This integrated data can be used directly by infrastructure asset managers and civil engineers to continuously refine risk registers, accurately monitor deformation over time, and prioritize maintenance schedules. Ultimately, utilizing this combined satellite and ground-based data empowers decision-makers to proactively identify high-risk structures, optimize resource allocation, and enhance the long-term safety and resilience of critical transportation networks.
This visualization has been cropped for vertical displays.
Print resolution map of the United States and all the long-span bridges measured in this study.
Bridge type legend
Credits
Please give credit for this item to:
NASA's Scientific Visualization Studio
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Visualizer
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Alex Kekesi
(ADNET Systems, Inc.)
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Alex Kekesi
(ADNET Systems, Inc.)
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Scientists
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Dominika Malinowski
( University of Bath)
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Giorgia Giardina
(Delft University of Technology, Netherlands)
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Dominika Malinowski
( University of Bath)
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Producer
- Grace Weikert (eMITS)
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Technical support
- Laurence Schuler (ADNET Systems, Inc.)
- Ian Jones (ADNET Systems, Inc.)
Related papers
https://www.nature.com/articles/s41467-025-64260-x
Datasets used
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MT-InSAR (Multi-Tempoeral Interferometric Synthetic Aperture Radar) [Sentinel-1: C-SAR]
ID: 1287 -
Land Subsidence (Potential Global Subsidence Map)
ID: 1288 -
Global Landslide Model (Global Landslide Hazard Assessment for Situational Awareness (LHASA))
ID: 1001https://pmm.nasa.gov/applications/global-landslide-modelThe global Landslide Hazard Assessment for Situational Awareness (LHASA) model is developed to provide situational awareness of landslide hazards for a wide range of users. Precipitation is
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Release date
This page was originally published on Monday, June 29, 2026.
This page was last updated on Friday, June 26, 2026 at 8:01 AM EDT.