Study on Alteration Information Extraction by Using Assimilation of Multi-Sensor Spectral Data

Some alterations of similar spectral reflectances cannot be distinguished accurately for their lower spectral resolution when the traditional methods, such as, band ratio and principal component analysis are used to extract alteration information from Landsat ETM multi-spectral data. In this paper, the band1~band7 of MODIS whose wave lengths are among 10~500nm, together with ETM’s multi-spectral bands, whose spatial resolutions are 30m, are chosen in the execution of data assimilation. After the third order wavelet transformation, the low-frequency component of ETM data are replaced by the MODIS data subsequently, then the inverse wavelet transform is in progress. The result of data assimilation consists of not only ETM’s spatial information but also MODIS’ spectral information. At last, four bands of assimilation results are selected to process PCA transform, as a result, two types of alteration in the study area are extracted accurately according to their components.