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Estimation Method of Inundation Extent Based on Mathematical Morphology

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  • Jianxun Li
  • Kin Keung Lai
  • Paul Safonov

Abstract

Estimation of inundation extent is critical for the flood control system. It helps decision-maker determine the scope of damage to save residents’ lives and property. In this paper, we analyzed the drawbacks of two kinds of methods of inundation estimation, hydrodynamic method and space-filling method, and divided inundation extent into water-body extent and water-invasion extent for the purpose of enhancing estimation accuracy. Based on Mathematical Morphology, an inundation estimation method suitable for flood mapping around natural and artificial lakes was put forward by integrating remote sensing (RS) data and digital elevation model (DEM) data. This method consists of three aspects, including the subdivision of water-body extent, the deduction of water-invasion extent which is viewed as the expansion of water-body extent, and the smoothing the boundaries of water-invasion extent. With subdividing DEM data horizontally into cross sections to build equiangular subsets, the expansion operation was implemented by structuring elements which were established based on set operations and scalar flexibilities. Thus, water-invasion extent was easily described by the structuring elements under given water volume, so that inundation extent was conveniently estimated by spatial data. The experiment results show that the method has the advantages of high accuracy and expressiveness and low time consumption. It had been used to analyze the inundation caused by the water conservancy project named Hanjiang-to-Weihe River Water Transfer Project in China. The method served as decision support for building an efficient emergency response mechanism and helped implement flood disaster forecast and simulation.

Suggested Citation

  • Jianxun Li & Kin Keung Lai & Paul Safonov, 2019. "Estimation Method of Inundation Extent Based on Mathematical Morphology," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-10, October.
  • Handle: RePEc:hin:jnlmpe:7825831
    DOI: 10.1155/2019/7825831
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