Research on Monitoring Flood Disasters in Poyang Lake by Integrating Optical and Radar Remote Sensing Data
Flood disasters have always been a hot topic in natural disaster research,which are char-acterized by suddenness,frequency,and wide-ranging impacts.The current remote sensing re-search on flood disasters faces challenges such as insufficient monitoring time and low timeliness,making it difficult to effectively monitor their processes.To address this issue,based on optical and radar images,the study initially evaluates the effectiveness of random forests,support vector ma-chines,and minimum distance algorithms in extracting the inundation range of the Poyang lake flood disaster;Then,the highest accuracy random forest algorithm is used to monitor the flood disaster process in Poyang lake area from June to July 2020;Finally,based on the land use type map before the occurrence of flood disasters,the types and areas of land features submerged by flood disasters are analyzed.The results show that:1)The random forest algorithm performs best in extracting flood inundation range,with an overall classification accuracy of 95.50% and a Kappa coefficient of 0.91;2)Integrating optical and radar remote sensing data can effectively monitor flood peak proces-ses.Compared to traditional optical remote sensing monitoring,radar remote sensing sensors are not affected by cloud and rain weather and should be given more attention;3)From June 26 to July 14,2020,the newly submerged area in the Poyang lake area reached 1 367.18 km2,with the main submerged area continually expanding,after which the flood gradually receded.The type of land with the largest inundation area throughout the entire process is farmland,with an inundated area of 246.68 km2.
flood disastersrandom forestremote sensingPoyang lake
万方数据
维普
