Predictive Prospecting Using Remote Sensing in a Mountainous Terrestrial Volcanic Area, in Western Bangongco–Nujiang Mineralization Belt, Tibet

Abstract

The Bangongco–Nujiang metallogenic belt of Tibet is a main suture zone in the Qinghai–Tibet Plateau, which is known as an important porphyry–epithermal–skarn Cu-polymetallic mineralization zone in China. The western part of the Bangongco–Nujiang metallogenic belt exposes several medium high-silica terrestrial alkaline volcanic rocks with strong alteration influenced by collision orogeny. Some research has shown that clues to mineralization such as malachite and gossan are found on the surface. However, volcanic rock areas with varied topography place a huge burden on geological investigation, and the existing research on predicting mineralization is relatively scarce. This paper describes the extraction of alteration mineral information based on medium spatial resolution and hyperspectral resolution images, establishing a spectral library of alteration minerals in this area. By analyzing radar data, digital elevation, and synthesis results of different spectral bands, we combine remote sensing with geographic information technology to establish crater markers. The extraction results from multisource and chemical exploration data are superimposed onto the analysis of mineralization characteristics and geological conditions so as to establish the mineralization signatures for terrestrial volcanic rock areas. Eighteen mineralization prospect areas were identified, which can provide technical support for future mineralization research in this belt.

A No-Reference Quality Assessment Method for Hyperspectral Sharpened Images via Benford’s Law

“…Although the proposed method is tested by using three different HS datasets, there still may be potential limitations: (1) The input images (i.e., HR-MS and LR-HS images) used when generating fusion results are simulated from the HS dataset itself. The effectiveness of the proposed method is uncertain about heterogeneous or multi-platform HS data.…”

“…With the rapid development of imaging sensor technology in recent years, more and more airborne and satellite hyperspectral sensors have been able to capture hyperspectral (HS) images. Due to the rich spectral information, HS images have a wide range of applications in remote sensing, such as geological monitoring [1][2][3], object tracking [4], atmospheric monitoring [5][6][7], etc. Because of the trade-off issue in HS images acquisition, where high spectral resolution comes at the cost of low spatial resolution, the practical application of HS data has been greatly limited.…”

Prospecting Prediction for the Yulong Metallogenic Belt in Tibet Based on Remote Sensing Alteration Information and Structural Interpretation

“…In recent years, satellite remote sensing technology, with its advantages of a short cycle, low cost, low risk and green environmental protection, has played an important role in the extraction of altered mineral information in hydrothermal deposits. At present, Landsat-8 OLI, ASTER and other multispectral data have been widely used in the extraction of altered mineral information, which then provides an important reference for the delineation of potential areas for prospecting [2][3][4]. However, due to the restrictions in spectral resolution, the extraction accuracy of the precise alteration type needs to be further improved.…”