Mineralization Of Iron Ore And The Western Part Of The East Kunlun Establish Remote Sensing Prospecting Model

Western regions of East Kunlun metallogenic belt are rich in minerals,but because of its harsh environment, few people tread, geological survey degree is low. Carrying out field work directly in northwestern plateau regions which are alpine hypoxia and lack of transportation not only consumes a lot of human resources, but also is rarely difficult to carry out large scale and regional work. It's an important way to ensure the sustainable development strategy of China's economy by using new technologies and new methods to strengthen the mineral resources exploration, expand the resources and reserves, satellite remote sensing technology is an indispensable means of this work. With the rapid increase of domestic and foreign data sources and the increasing resolution, remote sensing technology has played a more and more important role in the basic geological and mineral resources surveyThere are diversified iron deposits types in western regions of East Kunlun, mostly skarn-type, sedimentary- type and sedimentary-metamorphic type. Guide by the newest research achievement and the mineralization theory of the geosciences. On the one hand, by analyzing the geological characteristics of the study area, analyze and summarize the metallogenic conditions and distribution rules of iron ore. On the other hand, on the basis of known geological and mineral information, by means of remote sensing image processing and analysis, use multi-spectrum and high- spectrum Satellite remote sensing data source to preliminarily construct remote sensing image processing technology and method system on base of Aster, Worleview-2 and other foreign data with GF-1, 02 C and other domestic high score satellite, which means to farthest extract Indicative information of mineralization and mine-control stratum, geological structure, lithology and alteration in key areas. Go on with the test result, summarize the remote sensing geology factor that control mineral formation and the rule of the mineral deposit preservation. Establish the synthetic mineralization model for remote sensing exploration and predict the advantaged mineral formation area.Remote sensing abnormal information extraction mainly utilize ETM or Aster satellite data by way of spectral angle method, principal component analysis and band ratio method,meanwhile establish of a high score remote sensing geological interpretation signs. On the basis of the above work, use ASD spectrometer indoor to get spectral reflectance curve of typical iron ore and entry ENVI spectral library, summarize the typical rock impact factors. Use spectral index method, maximum likelihood method and spectral angle method(SAM) on ASTER Image which is linked with Intrusive rocks related to mineralization, and compare the respective advantages of the three methods. On the basis of these work, carry out remote sensing prospecting prediction, to supply basic data area for area and survey resources, so as to quickly find the western part of the East Kunlun provide technical support and iron ore prospecting.The analysis shows that the iron ore is mainly distributed in the Proterozoic Jinshuikou group, the small temple group and the Paleozoic Tanjianshan group. The rocks are mainly shallow metamorphic carbonate rocks, clastic rocks, followed by gneiss. Remote sensing image is gray, gray-red color, in which the color is relatively uniform, the stripes are clear, the patch shape grain shape as well as mountain terrain. The Indosinian intrusive rocks show a remarkable specificity for iron mineralization type. There are two major types of iron mineralization related to the type of rock, such as monzonitic granite and syenogranite. The image is dark gray, gray- brown, partial off-white, visible steep mountains, dot shape and banding pattern shape, rough surface, local rounded. The main tectonic lines are N-W and N-WW fault structures, mainly being high angle reverse faults, the image is very eye-catching performance of linear features. Water ancon abnormal segments are often seen, with fault triangles visible. In addition, the spectral reflectance is positively correlated with grain size and mineralization, but with no obvious regularity with alteration, and it is related to the type of alteration. Quantitatively evaluate classification results, the accuracy of monzonitic granite and quartz-syenite in Aster spectral index method is much higher than that in Maximum likelihood and spectral angle classification, while the maximum likelihood method is good for the identification of syenite. From the above analysis, it can be concluded that the spectral index method can improve the classification accuracy of some lithology in the process of lithologic classification.