基于SAR纹理和LightGBM的洪水淹没地区遥感应急监测

Emergency monitoring of remote sensing for flood inundation region based on SAR texture and LightGBM

针对洪涝灾害期间淹水范围监测精准和时效的高要求,本文提出了一种基于SAR(synthetic aperture radar)纹理信息和LightGBM算法的水体提取方法.与SDWI(sentinel-1 dual-polarized water index)水体指数法、SVM(support vector machines)、RF(random forest)和GBDT(gradient boosting decision tree)算法对比表明,在河道、湖泊和洪水淹没区三类重点监测区域,该方法提取精度均达98%以上,总体精度优于其他方法.同时,该方法的运行效率较其他方法提升20~100倍,极大地提高了洪涝灾害期间淹水应急监测的时效性.

In response to the need for high timeliness and accuracy monitoring for inundation region during flood disaster,a new extraction method of water areas based on SAR texture and LightGBM was proposed.Compared with other methods,such as the SDWI water index,SVM,RF and GBDT methods,it shows that the accuracy of water extraction of river,lake and flooded area is beyond 98%and higher than other methods.Meanwhile,the operating efficiency of the proposed method is 20~100 times higher than other methods,which greatly improves the timeliness of inundation emergency monitoring during flood disaster.