Articles | Volume 30, issue 7
https://doi.org/10.5194/hess-30-2183-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-2183-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Apr 2026
Research article |
| 17 Apr 2026
| 17 Apr 2026
Community-scale urban flood monitoring through fusion of time-lapse imagery, terrestrial lidar, and remote sensing data
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, USA
Sophie Dorosin
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, USA
José A. Constantine
Department of Geosciences, Williams College, Williamstown, Massachusetts 01267, USA
Claire C. Masteller
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, USA
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Short summary
Frequent, low-intensity urban pluvial flooding is notoriously difficult to detect and monitor. This study introduces a novel, low-cost approach using computer vision to integrate time-lapse photos with lidar data to estimate water levels and flood extents. Applied to two case study flood events and validated against a two-dimensional flood model, this method shows how community-centered, adaptable monitoring systems can capture spatiotemporal flood dynamics often missed by traditional methods.
Frequent, low-intensity urban pluvial flooding is notoriously difficult to detect and monitor....
