摘要: Spectral remote sensing technique is usually used to monitor flood and waterlogging disaster. Although spectral remote sensing
data have many advantages for ground information observation, such as real time and high spatial resolution, they are often interfered by
clouds, haze and rain. As a result, it is very difficult to retrieve ground information from spectral remote sensing data under those
conditions. Compared with spectral remote sensing technique, passive microwave remote sensing technique has obvious superiority in
most weather conditions. However, the main drawback of passive microwave remote sensing is the extreme low spatial resolution.
Considering the wide application of the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) data, an AMSR-E
data unmixing method was proposed in this paper based on Bellerby′s algorithm. By utilizing the surface type classification results with
high spatial resolution, the proposed unmixing method can obtain the component brightness temperature and corresponding spatial
position distribution, which effectively improve the spatial resolution of passive microwave remote sensing data. Through researching the
AMSR-E unmixed data of Yongji County, Jilin Provinc, Northeast China after the worst flood and waterlogging disaster occurred on July
28, 2010, the experimental results demonstrated that the AMSR-E unmixed data could effectively evaluate the flood and waterlogging
disaster.