Taking debris flow area as an example, this paper studied retrieval of soil Sodium content and pH by hyperspectral remote sensing, which provided a new method for estimating soil dispersion. Based on preprocessing, the authors extracted four spectral indices, including reflectance(R), inverse reflectance(1/R), inverse-log reflectance(log(1/R)) and band depth(BD), to establish the prediction model for Sodium content and pH using stepwise multiple regression method. Results indicated that reflectance spectra and inverse-log reflectance were the optimum parameters for inverting soil sodium ions content and pH, respectively. Determination coefficients R2 of prediction samples were 0.690 and 0.641 respectively, and R2 of test samples were 0.523 and 0.438, which showed that soil spectra with high spectral resolution had the potential for the rapid prediction of Sodium content and pH, thus, providing reliable detection method for soil dispersion using hyper-spectral technology.
A method for seismogeological hazards extraction using high resolution remote sensing was proposed in the research
taken the epicenter of Wenchuan earthquake-Yingxiu town as the study area. In which, making imagery was built
according to the Digital Elevation Model (DEM) to remove interfering factors. Then, the masked imagery was diced into
several small parts to reduce the large imageries’ inconsistency and they were used as the sources to be classified. After
that, the vector conversion was performed on the classified images to mapping geological hazards. Finally, other
interfering factors such as bare lands, lands covered by few vegetation and buildings on the top altitude were removed
manually. For it can extract geological hazards in a short time, it is of great importance for the decision–makers and
rescuers to know the damaged degree in the disaster area, especially within 72 hours after the earthquake. Therefore, it
will play an important role in decision making, site rescue and hazards response planning.
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