Integrating Spectral Anomalies And Texture Feature From SAR Image To Extract Mineral Information

Mineralization information of remote sensing is the basic foundation of mineral resourcesexploration, the remote sensing data and corresponding analyzing methods will influencethe result of extracting mineralization information. Traditional remote sensing applicationson mineral exploration are quantitative interpretation and spectral analysis based onmulti-spectral data, while the development of radar remote sensing technique providesbroader prospect for geological and mineral applications. The study area locates in themiddle of Qilian Mountain, on which various deposits distribute, sophisticated geologicalconditions, and the basic remote sensing investigation is lacked; but the researches onmineral deposits are very ripe, so these foundations are very beneficial to detailed analysisof spectral and radar texture, polarization information. This paper selects ASTER andRadarsat-2remote sensing data, using the advantages of spectral and texture information,functioning as professional knowledge, to researching mineral exploration on plateau areasof high altitude. These are all meaningful to figure out mineral deposits types,mineralization conditions, and put forward fit remote sensing methods.(1)Mineralization information extraction based on spectral anomalies. ASTER V-SWIRbands are good sources of mineral alteration extraction, thus ferric and hydroxyl alterationmapping are applied according to diagnose features; while lithological identificationrelated to Cu-Pb-Zn is applied thermal bands by taking advantage of lithological spectral;the content of silicon dioxide is calculated by “K-value” method of Shuichi Miyatake toobtain the basic and ultra-basic lithology mapping results.(2)Mineralization information extraction based on texture feature. Radarsat-2which holdsmulti-polarization imaging model, high spatial resolution and abundant structureinformation is prospective for geologic application. The differences of terrain scatteringcharacteristics are basic to extract brightness and texture features. Gray statisticalcharacteristic such as medium and variance are gained from multi-polarization Radarsat-2,and the Gray-Level Co-occurrence Matrices are used to extract several texture featuressuch as Angular second moment, comparativeness, coloration, entropy. Finally thegabbro, granite, medium to basic volcanic rocks are identified according to respectiverules.(3)Integration of mineralization information from optical and radar data. With the resultsabove, EBF model is applied on the mineralization information to evaluate the mineralalteration and lithological mapping as evidences, to obtain integrated anomaly. Mineralization information extraction is well applied in the Yushigou area and the result isvery good. Remote sensing methods are properly applied from spectral analysis to textureextraction, which increase the ability of lithological mapping and mineral alterationmapping. Multi-sources are compensating the disadvantages of single-source and lowspatial/spectral resolution. Remote sensing features are exaggerated by combining bothoptical and radar data, improving the efficiency of mineralization information extraction,as well as the development of geologic remote sensing.