Articles | Volume 26, issue 10
https://doi.org/10.5194/nhess-26-5299-2026
https://doi.org/10.5194/nhess-26-5299-2026
Research article
 | 
28 Oct 2026
Research article |  | 28 Oct 2026

Large-scale flood monitoring based on time-series Sentinel-1 images and Z-score

Runmei Xing, Fengyuan Lu, and Jun Zhao

Cited articles

Alvarez-Vanhard, E., Corpetti, T., and Houet, T.: UAV and satellite synergies for optical remote sensing applications: a literature review, Sci. Remote Sensing, 3, 100019, https://doi.org/10.1016/j.srs.2021.100019, 2021. 
Amitrano, D., Di Martino, G., Di Simone, A., and Imperatore, P.: Flood detection with SAR: a review of techniques and datasets, Remote Sens., 16, 656, https://doi.org/10.3390/rs16040656, 2024. 
Anusha, N. and Bharathi, B.: Flood detection and flood mapping using multi-temporal synthetic aperture radar and optical data, The Egyptian Journal of Remote Sensing and Space Science, 23, 207–219, https://doi.org/10.1016/j.ejrs.2019.01.001, 2020. 
Barredo, J. I.: Major flood disasters in Europe: 1950–2005, Nat. Hazards, 42, 125–148, https://doi.org/10.1007/s11069-006-9065-2, 2007. 
Borrelli, P., Robinson, D. A., Panagos, P., Lugato, E., Yang, J. E., Alewell, C., Wuepper, D., Montanarella, L., and Ballabio, C.: Land use and climate change impacts on global soil erosion by water (2015–2070), P. Natl. Acad. Sci. USA, 117, 21994–22001, https://doi.org/10.1073/pnas.2001403117, 2020. 
Download
Short summary
This study introduces a method for monitoring floods using Synthetic Aperture Radar. The approach analyzes how radar signals interact with different land surfaces. It finds vegetation growth affects signal consistency in natural landscapes, while rainfall changes signal reflection in cities. Using statistical analysis, the method creates flood probability maps. Combining different radar signal types improves identification of flooded areas in both natural and urban environments.
Share
Altmetrics
Final-revised paper
Preprint