With the development of Hyperspectra and the method of rock-mineral information extraction, several cores were
analyzed based on analytical spectral devices (ASD) and rock-mineral information extraction in Wushan-cooper deposit
area. Aiming at the low accuracy of mineral identification with hyperspectral data, the present study established regional
spectra library on the basis of the study area geological background, section noise filtering and fast Fourier transform
processing methods. Using the rapid quantificational identification model, the rock-mineral alternation information was
extracted to build core profile and 3D model to discuss the deep mineralization evaluation.
Combing with the regional metallogenic background, the alteration information indicated that the ore mineral was related
with multiple alteration assemblages and there may be rock mass in deep space. The Cu element contents and ore
mineral were closely related with the skarnization, silicification and chloritization. It also suggested that the deposit was
skarn type in less than 1000 m depth, which was affected by the sandstone. Meanwhile, in more than 1000 m depth, the
deposit was controlled by composite minerallzation types, which was associated with the previous geology and mineral
deposits studies. In summary,this study supported a two stage mineralization model for the Wushan-copper deposit
area,namely,the first stage of synsedimentary hydrothermal exhalative stage and the second stage of magmatichydrothermal
ore-forming stage.
Image segmentation is the basis of object-based information extraction from remote sensing imagery. Image
segmentation based on multiple features, multi-scale, and spatial context is one current research focus. The scale
parameters selected in the segmentation severely impact on the average size of segments obtained by multi-scale
segmentation method, such as the Fractal Network Evolution Approach (FNEA) employed in the eCognition software. It
is important for the FNEA method to select an appropriate scale parameter that causes no neither over- nor undersegmentation.
A method for scale parameter selection and segments refinement is proposed in this paper by modifying a
method proposed by Johnson. In a test on two images, the segmentation maps obtained using the proposed method
contain less under-segmentation and over-segmentation than that generated by the Johnson’s method. It was
demonstrated that the proposed method is effective in scale parameter selection and segment refinement for multi-scale
segmentation algorithms, such as the FNEA method.
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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