基于多源遥感数据的水体信息提取研究

卫星遥感技术已被广泛应用到水体信息提取中,但目前基于遥感技术的水体信息提取多采用单一的遥感数据源,而没有充分利用多源数据的信息复合优势,因此,提取结果经常受天气气候或空间分辨率限制。本文研究了不同尺度、不同平台的多种遥感数据源的水体信息提取方法。首先,基于波谱间关系决策树分类算法对Landsat ETM+图像进行水体提取,利用其分辨率优势较准确地提取出水体范围;其次,在Radarsat SAR图像上利用阈值法粗提取水体信息后,结合DEM剔除阴影得到水体信息;最后,利用灾前Landsat ETM+图像水体信息提取结果和灾中Radarsat SAR图像水体信息提取结果,进行差值处理,得到洪水淹没范围。研究结果可以为洪水灾害监测与评估提供信息依据。

The Research on Water Information Extraction Based on Multisource Remote Sensing Data

Satellite remote sensing technology has been widely used to extract water-body information. However,nowadays a single kind of remotely sensed data is usually used to extract water-body information,but the advantage of the combination of multi-source datum information is ignored. Consequently,the accuracy of water information extraction is often limited to the climate or spatial resolution. In this paper,a new method based on multi-scale and multi-platform remotely sensed data is explored to extract water-body information. The main research includes several steps as follows： first,decision tree classification algorithms based on relationships between spectrum are used to extract the accurate size of water-body on Landsat ETM ＋ image due to its high spatial resolution; second,the method of threshold value is used to extract water-body information on Radarsat SAR image crudely,then more accurate water-body information is obtained by eliminating the shadow influence combined with DEM; finally,the flood extent is obtained by using differential technique of the water-body information extracted from the Landsat ETM ＋ image before flood disaster and Radarsat SAR image during flood disaster. The new method explored in this paper can provide information support for flood disaster monitoring and evaluation.