河流精确提取在水资源调查、利用、变化检测及大型水利设施建设评估等方面具有非常重要的意义。通常的河流信息提取方法受影像中云、冰雪、山体阴影、大型湖泊等的干扰较大,大范围的适用性有限。以Landsat卫星遥感数据为数据源,在归一化差异水指数(NDWI)计算的基础上,首次提出采用高斯归一化水体指数(GNDWI)提取河流水体的模型,使得指数能够更大程度上保证河流提取的连续性,并通过DEM的辅助实现了其他干扰信息的去除。通过对伊犁河试验区河流信息提取的实验结果表明,该方法除了能够实现对复杂多样的河流水体信息进行自动提取外,还可有效去除阴影等信息的混淆,并能够达到较高的河流提取精度。

The accurate extraction of rivers is important for survey of water resources, time series change detection on water usage, assessment of large-scale water conservancy facilities, and so on. The general methods of river extraction are difficult to be applied widely because of the disruption by clouds, snow, shadow of mountains, and lakes in remotely sensed images. In this paper, we propose a new index calculation model for river extraction, which is based on an improved water index, named Gaussian normalized difference water index (GNDWI). The model can remove the interference factors effectively by the aid of a DEM. The experiment for the extraction of Ili River from Landsat images show that the new model can automatically and rapidly extract the river in very complex environments. Furthermore, shadows and other useless information can also be effectively removed with a high accuracy.