Abstract
This paper proposes a method of combining and visualizing multiple lithological indices derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and topographical information derived from digital elevation model (DEM) data in a single color image that can be easily interpreted from a geological point of view. For the purposes of mapping silicate rocks, carbonate rocks, and clay minerals in hydrothermal alteration zones, two new indices derived from ASTER thermal infrared emissivity data were developed to identify silicate rocks, and existing indices were adopted to indicate the distribution of carbonate rocks and the species and amounts of clay mineral. In addition, another new method was developed to visualize the topography from DEM data. The lithological indices and topographical information were integrated using the hue–saturation–value (HSV) color model. The resultant integrated image was evaluated by field survey and through comparison with the results of previous studies in the Cuprite and Goldfield areas, Nevada, USA. It was confirmed that the proposed method can be used to visualize geological information and that the resulting images can easily be interpreted from a geological point of view.
Highlights
In geological remote sensing, surface materials such as rocks and minerals are characterized and/or discriminated based on their spectral features, which are captured by a multi- or hyperspectral sensor mounted on an aircraft or spacecraft (e.g., [1,2,3,4])
All of the lithological indices and topographical information were combined to generate a single image that clearly exhibits the distribution of silicate rocks, carbonate rocks, and hydrothermal alteration zones, as well as the topography, using the HSV color model
The proposed method consists of three parts: a technique to combine multiple indices using the HSV color model, the derivation of appropriate spectral indices to discriminate among different lithologies, and a method of visualizing the topography derived from digital elevation model (DEM) data
Summary
Surface materials such as rocks and minerals are characterized and/or discriminated based on their spectral features, which are captured by a multi- or hyperspectral sensor mounted on an aircraft or spacecraft (e.g., [1,2,3,4]). The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a multispectral imaging sensor on NASA’s Terra spacecraft and has already imaged almost all land areas worldwide except for those in the polar regions. ASTER has three optical subsystems: the visible and near-infrared (VNIR), shortwave-infrared (SWIR), and thermal infrared (TIR) radiometers, as described in Table 1 [5]. The VNIR and SWIR bands were designed to capture the diagnostic absorption features of clay, carbonate, and iron oxide minerals, as well as vegetation, whereas the TIR band was designed to measure the surface temperature and detect the emissivity patterns of silicate rocks. The band ratio technique (e.g., [6]) has been widely used to enhance spectral patterns because of its simple calculation. The spectral angle mapper (SAM) [7], spectral indices [8], and conventional classification methods such as supervised classification (e.g., [9]) are popularly used to map the distributions of different rocks and minerals
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