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Dynamic monitoring of flood disaster based on remote sensing data cube

Author

Listed:
  • Zhicheng Wang

    (Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences
    Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Zhiqiang Gao

    (Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences
    Chinese Academy of Sciences)

Abstract

High-frequency dynamic monitoring of flood disaster using remote sensing technology is crucial for accurate decision-making of disaster prevention and relief. However, the current trade-off between spatial and temporal resolution of remote sensing sensors limits their application in high-frequency dynamic monitoring of flood disaster. To deal with this challenge, in this study, we presented an approach to conduct high-frequency dynamic monitoring of flood disaster based on remote sensing data cube with high spatial and temporal resolution. The presented approach included two steps: a, removing the cloudy areas in original MODIS data to construct the cloud-free MODIS data cube by using the information provided by GPM rainfall data; b, fusing the cloud-free MODIS data cube and Landsat-8 data by using the spatiotemporal data fusion algorithm to construct the high spatiotemporal resolution (Landsat-like) data cube. The approach was tested by conducting high-frequency dynamic monitoring of flood disaster occurred in Henan Province, PR China. Our study had three main results: (1) the presented cloud removal algorithm in the first step was able to retain flood information and performed well in removing clouds during consecutive rainy days. The differences between cloud-free MODIS data cube and original MODIS data were small and the cloud-free MODIS data cube could be used for constructing high spatiotemporal resolution data cube. (2) Our presented approach could be used to conduct high-frequency dynamic monitoring of flood disaster. (3) Testing results showed that there were two floods occurred in the study area from July 17, 2021, to October 16, 2021; the first flood occurred from July 17, 2021, to September 15, 2021, with maximum affected area of 668.36 km2; the second flood occurred from September 18, 2021, to October 16, 2021, with maximum affected area of 303.88 km2. Our study provides a general approach for high-frequency monitoring of flood disaster.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:nathaz:v:114:y:2022:i:3:d:10.1007_s11069-022-05508-3
    DOI: 10.1007/s11069-022-05508-3
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    References listed on IDEAS

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    1. Joy Sanyal & X. Lu, 2004. "Application of Remote Sensing in Flood Management with Special Reference to Monsoon Asia: A Review," 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. 33(2), pages 283-301, October.
    2. 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.
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