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The special topography of mountain terrain will induce the retrieval distortion in same species and surface spectral
lines. In order to improve the research accuracy of topographic surface characteristic, many researchers have focused on
topographic correction. Topographic correction methods can be statistical-empirical model or physical model, in which
the methods based on the digital elevation model data are most popular. Restricted by spatial resolution, previous model
mostly corrected topographic effect based on Landsat TM image, whose spatial resolution is 30 meter that can be easily
achieved from internet or calculated from digital map. Some researchers have also done topographic correction based on
high spatial resolution images, such as Quickbird and Ikonos, but there is little correlative research on the topographic
correction of CBERS-02B image. In this study, liao-ning mountain terrain was taken as the objective. The digital
elevation model data was interpolated to 2.36 meter by 15 meter original digital elevation model one meter by one meter.
The C correction, SCS+C correction, Minnaert correction and Ekstrand-r were executed to correct the topographic effect.
Then the corrected results were achieved and compared. The images corrected with C correction, SCS+C correction,
Minnaert correction and Ekstrand-r were compared, and the scatter diagrams between image digital number and cosine of
solar incidence angel with respect to surface normal were shown. The mean value, standard variance, slope of scatter
diagram, and separation factor were statistically calculated. The analysed result shows that the shadow is weakened in
corrected images than the original images, and the three-dimensional affect is removed. The absolute slope of fitting lines
in scatter diagram is minished. Minnaert correction method has the most effective result. These demonstrate that the
former correction methods can be successfully adapted to CBERS-02B images. The DEM data can be interpolated step
by step to get the corresponding spatial resolution approximately for the condition that high spatial resolution elevation
data is hard to get.
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