Characteristic Analysis of Flood Monitoring in Wuhan City Based on GF-1 Remote Sensing Data

Severe flooding and river embankment dam collapse in Wuhan City was caused by heavy rainfall from June 30 to July 6, 2016. In this study, GF-1 WFV images before and after the floods were used to analyze the spectral characteristics of water bodies during the flooding period and to compare the suitability of this data for extracting various types of information about the water bodies using NDWI thresholds and object-oriented classification. An optimal algorithm was adopted for monitoring the flood disaster. The results showed that the object-oriented classification method was superior to the NDWI threshold method for extracting the results of different types of urban water bodies during the flood season. The flood submergence area caused by flooding of rivers and river embankments was effectively identified from GF-1 WFV images using object-oriented classification methods. The results provide a reference for the application of GF-1 image analysis to monitor urban flood disasters.