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.
In order to calculate the serious degree of geological disaster caused by earthquake taken place in Wenchuan county,
Shichuan province, China with magnitude 8.0 on May 12th 2008, a method for extracting the changed vegetation using
remote sensing taken the example of Minjiang basin from Moutuo to Xiao Shawan in Maoxian county, Shichuan
province, China is proposed here. Because the study area has the characteristic of "high vegetation cover" (ratio of
vegetation cover is 88.3% before earthquake takes place), changed vegetation can reflect the serious degree of geological
disaster damage. Flow chart of this method is as following: Firstly, different spatial resolution between two images
acquired before and after earthquake is uniformed and the two images are registered with accuracy less than one pixel;
Then, vegetation changed map is made by extracting the difference area covered by vegetation in two images using
Normalized Difference Vegetation Index (NDVI); Finally, statistics and analysis are performed according to the
vegetation changed map. Results from vegetation changed map show that in the total area of 201.7 km2, vegetation
changed area is 24.4 km2 in which 99.6% is caused by geological disaster with area of 24.3 km2, and the 0.4% left is
caused by the change of farm operations. Therefore, changed vegetation in study area is mainly caused by geological
disaster. According to geological map and high resolution images acquired by airborne remote sensing on May 23rd
2008, for "high fragility and hardness" of limestone, phyllite and quartzose sandstone in study area, the type of
geological disaster is debris flow caused by slacktip.
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