Remote sensing is an important means of monitoring the extent of flood inundation and understanding the evolution of flood disasters.However,optical images often have many deficiencies during floods,and all-weather SAR images have slightly lower accuracy in extracting water bodies.A flood inundation range extraction model based on Sentinel-2 optical images and Sen-tinel-1 radar image data was constructed to extract the flood inundation range quickly and accurately.An adaptive threshold seg-mentation algorithm,the Otsu algorithm,was used to extract the water body range of two types of data and the proposed model,and an application analysis was conducted using Baoding City,Hebei Province as an example.The results showed that Sentinel-2 im-ages with less cloud cover had the best water extraction effect,with an overall accuracy(OA)of 95.6%.After introducing some available Sentinel-2 data,the OA of the constructed model reached95.0%,OA and Kappa coefficient were increased by1.2%and 2.4%respectively compared to using Sentinel-1 data alone.This model is installed on the Google Earth Engine platform and can achieve fast,accurate,and low-cost continuous output of the spatial range of surface water bodies.Clouds and mist do not limit it and have higher extraction accuracy than Sentinel-1 images alone.In the case of severe cloud coverage leading to a lack of Sentinel-2 data,this model can be used as an alternative method for extracting flood inundation areas.
维普
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