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Monitoring the Iran Pol-e-Dokhtar flood extent and detecting its induced ground displacement using sentinel 1 imagery techniques

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  • Ali Mehrabi

    (Shahid Bahonar University of Kerman)

Abstract

On 25 March 2019, the Lorestan Province, Iran, suffered a heavy rainstorm. This rainstorm flooded the city of Pol-e-Dokhtar and many villages. To elucidate and monitor the nature of the spatial extent during and after the flood event, and to evaluate flood-induced ground displacement, the time series Sentinel 1 images were analyzed using threshold and SBAS-InSAR techniques. The SAR images were first calibrated, geometrically corrected, and filtered. Then, the threshold method was applied to draw the map of the affected areas. The results showed that flood spatial propagation varies through time. The nature of spatial extent was sinusoidal, so that the flood behavior complied with precipitation periods. Furthermore, the findings of the SBAS-InSAR indicated how an extreme flood can cause ground displacement. Several active movement areas were identified, showing a surface velocity up to −1.1 mm day−1 away from the satellite. The field observations demonstrated that the landslide phenomenon occurred in some of these areas. Therefore, the other identified areas can also be at risk of landslides. Finally, based on the findings, it is evident that SAR data can effectively be used for flood water mapping, flood monitoring, and flood-induced ground displacement.

Suggested Citation

  • Ali Mehrabi, 2021. "Monitoring the Iran Pol-e-Dokhtar flood extent and detecting its induced ground displacement using sentinel 1 imagery techniques," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(3), pages 2603-2617, February.
    • Handle: RePEc:spr:nathaz:v:105:y:2021:i:3:d:10.1007_s11069-020-04414-w
    DOI: 10.1007/s11069-020-04414-w
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    References listed on IDEAS

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    1. Md. Shahinoor Rahman & Liping Di, 2017. "The state of the art of spaceborne remote sensing in flood management," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(2), pages 1223-1248, January.
    2. Yilin Liu & Haijun Huang & Yanxia Liu & Haibo Bi, 2016. "Linking land subsidence over the Yellow River delta, China, to hydrocarbon exploitation using multi-temporal InSAR," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 271-291, October.
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    Cited by:

    1. Zhicheng Wang & Zhiqiang Gao, 2022. "Dynamic monitoring of flood disaster based on remote sensing data cube," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 3123-3138, December.

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