Study On The Extraction Of Mineral Information In Geermu Of Qinghai Province Based On Multi-source Remote Sensing Data

Rocks and minerals are the products of geological processes. Mineral is the basicunit of rock. The mineral is a simple substance or compounds formed by geologicalprocesses. Different minerals or the combinations of them compose various types ofrocks of different nature. The minerals contain different chemical compositions andhave certain internal structures. As the external conditions change, the compositionsand structures also make some changes that may lead to the formations of newminerals. Rock is the assemblage of one or more kinds of minerals aggregating with acertain texture and structure. It is widely distributed in the earth's crust and is therecord of the history of geological developments.Through the study of rocks and minerals, both the exploration and theunderstanding of crust development, changes as well as the laws of movements can beachieved so that bring about important inferences for prospecting and geologicalstudies. Minerals host in the rocks, along with geological processes and show certainregularity of the dependency of the type of rocks on the types of the minerals.Launching the geological study of the rock and mineral information can providegeological data and material for exploring, probing, and mining the mineral resourceswhich shows the economic significance and practical value of the rock and mineralresearch work in the mineral prediction and development.Remote sensing in geology is a technique that comprehensively applies modernremote sensing techniques to study the geological rules as well as carry out geologicalsurvey and resources exploration. It focuses on the geological information obtainedfrom the air from a macro perspective and takes the reactions of a variety of geologicbodies of electromagnetic radiation as a fundamental basis. This technique iscombined with a variety of other integrated applications of geological data so that itcan be used to analyze, to judge, and to identify certain areas of geological situation.In recent years, with the development of multi-spectral and hyper-spectral remotesensing technology as well as the improvement of spectral resolution, the applicationsof remote sensing technology have good prospects of development in several fieldssuch like the identification of rocks and minerals, the identification of minerals andmapping and so on.Associated analysis of spectral features of rocks and minerals together with theirmaterialization properties is the basis of the identification and extraction of rocks andminerals via the means of remote sensing. The research in this area can be generally divided into two aspects: one is to take the characteristic spectra of rocks and mineralsas a starting point and carry out relevance analysis by taking the chemicalcomposition of rocks and minerals, the crystal structure or some other physical andchemical knowledge into consideration to extract the rock and mineral information;another is to put emphasis on the physical model and extract the information of rocksand minerals with the knowledge of spectra of them. Currently, remote sensingtechnology in the identification of information of rocks and minerals as well as thegeological mapping are mainly dependent on the spectral characteristics of the surfacefeatures. It directly makes use of the spectral characteristics of the rocks and mineralsto identify them and extracts their information quantitatively or semi-quantitatively.Excessive reliance on the spectral information of rocks and minerals often results inthe overlook of the relationship between the chemical composition of minerals andmineral or the mineral and the rocks. The influence on the characteristics of objectspectrum that is caused by the atmospheric radiation and the influence on the singlewaveform caused by the spectral shift or the mutation that is brought about by themixed spectrum may result in the repeated introductions of the spectral characteristicsand may lead to greater interference of the results of rock and mineral informationextraction.Based on remote sensing technology, this paper combines itself with geologicalresearch methods to extract the information of rocks and minerals within Wutumeirenin the area of Golmud in Qinghai Province. The study can be divided into two steps:First, in geological background of this region that mentioned above, the author adoptsthe methods of image enhancement based on the gray level and texture features of theremote sensing images and expand the differences in the gray level and texturefeatures between various lithological characters in order to give prominence to theinformation of the surface features. This makes it easy for the visual interpretation andestablishment of the regions of interest. Besides, this paper uses the method ofsupervised classification to classify the images to meet the purpose of distinguishingdifferent lithological characteristics. Moreover, it also separates the regions ofdifferent classifications.From the analysis of the spectral characteristics viewed by the techniques ofremote sensing, the author establishes the mathematical and physical models of therelationships between the oxides in the minerals and the characteristics of thespectrum. Via using the chemical computing method of Norm Mineral Calculation(CIPW) for the rocks, according to the method of spectral information–oxide–mineral–rock, this paper carries out the identification of the rocks and mineralsin the certain region as well as the extraction of the information of the rocks andminerals quantitatively or semi-quantitatively.This research carries out investigation from the angle that is quite different fromthe ones taken in the previous studies and provides a new way of thinking about the identification of the information of rocks, the content of the mineral content and thechemical composition, etc.The main research results and innovations of this research are as following:1.The investigation of the method of the integration of image enhancementbased on different remote sensing data of multiple sources.Taking the ASTER data and QucikBird-2data as the data sources, this paperrealize the target of the integration of multi-spectral images and high resolutionimages and gets the images with the good qualities of both the two kinds of images sothat it improves the spatial resolution of multispectral images. The experiments showthat the HIS wavelet fusion method can improve the resolution; at the meanwhile, itcan also achieved good results in the quantitative evaluations of the maximum entropyas well as the maintenance of spectral features.When applied to the establishment of the regions of interest and the classificationof images, the enhanced images can solve the problems of the low quality ofinterpretation and classification, the coarseness of the texture that are caused by theinsufficient spectral resolution of the high-resolution images. This in turn brings aboutthe improvement of the quality of the integrated image and the precision of thecomprehensive analysis. The classification based on these images is better than othersbased on the images without the integration.2.The classification methods based on the LS-SVM classification techniqueswith high-resolution multi-spectral image.Using least squares support vector machine (LS-SVM) classification techniques,based on merged high-resolution multi-spectral image, texture, shape and spectralinformation of image with the relevance of lithology were extracted. Spectral andtexture of image were treated as the main feature information in the process ofselecting. Based on JM distance and conversion of classification degree, the optimalfeature space was selected. Feature space was compressed in factor analysis totransform the dimensionality reduction so that feature information achieved optimaleffect. Training the known samples, establishing classification model and evaluatingthe accuracy of the model followed. Finally, the study area was dealt with lithologypartition and classification post-processing by the model. The results showed that:LS-SVM classification model with the texture and other information were moreconducive to lithology discrimination; the LS-SVM classification method performedwell in the remote sensing images lithology identification.3.Support vector machine regression method improves the accuracy ofquantitative retrieval of oxide weight percent.The retrieval of the mineral oxide is not a simple linear problem. Aftercontrasting the regression effect between some linear regression algorithms andsupport vector machine regression algorithm, support vector machine regressionmodel was proposed and improved in terms of kernel function. The improved regression model improved retrieval accuracy of the oxide. The experiments show thatthe retrieval result of the method is more accurate and its application effect is better inthe case of the same number of samples.4.The CIPW rock chemistry calculation method is introduced into quantitativeidentification of remote sensing geological mineral and put forward a″rock andmineral spectral information-oxide-mineral-rock″method of extracting rock andmineral information.The CIPW rock chemical analysis method is introduced into the remote sensinggeological work, regarding each pixel of remote sensing images as a rock sample.Based on typical rock and diagnostic spectral characteristics of the mineral, aspectral mathematical physics model of oxide in the mineral and the spectralcharacteristics of mineral were established. The chemical composition of each pixelwas calculated. Then proceed to the CIPW Standard mineral calculation to get thestandard mineral quantitative information.At last, calculating according to the rock and mineral spectral information-oxide-mineral-rock research idea, we will get quantitative and semi-quantitative rockand mineral information in this area.5.According to the theory of geological diagenesis, lithology identification ruleswere established to extract lithology information.Minerals and mineral assemblages according to certain rules exist in the rock. Itreflects the uniform formation conditions. They combine according to a certaingeological effect. Due to different causes of formation and the changes of externalconditions, the mineral which rocks contain will change. From the geochemical pointof view, the chemical elements contained in different rocks in the same stratum isdiverse and the content of each element is very uneven, resulting in the contents ofoxide and mineral are also different. From the petrological point of view, differentlithology must be formed by a wide range and variety of combinations of minerals.Based on geological theory, the delineated lithology classification is seen as abenchmark. Based on the content of oxide in different rocks and the difference ofmineral content, the lithology identification rules is established. According to theprinciple of layer stripping identification, the lithology in the study area can beclassified.