ABSTRACT Spaceborne data with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Short Wave Infrared (SWIR) bands have been used worldwide in discriminating different clay minerals. However, due to wide bandwidth of ASTER sensors, it is difficult to distinguish between pure and impure variety of talc mineral. The present study highlights the efficacy of airborne hyperspectral data Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) for spectral analysis in talc mineral in the Jahazpur Belt of Bhilwara district in Rajasthan, India. Due to its better spectral and spatial resolution, AVIRIS-NG is found to be extremely useful in identifying talc mineral in SWIR region. Talc is characterized by doublet shaped spectral pattern in AVIRIS-NG image with strong absorption dips at 2289.75 nm and 2314.80 nm which could not be picked up in ASTER image. Spectral matching of talc pixels is verified with the field spectra of samples and available spectral library of United States Geological Survey, Jet Propulsion Laboratory, and International Geological Correlation Programme. Variation in reflectance percentage of different talc pixels is attributed to variation in chemical composition of talc. However, a large number of mixed pixels with spectral pattern of both talc and kaolinite minerals have been identified in AVIRIS-NG image which are found to be an impure variety of talc. Whole-pixel to sub-pixel classification techniques with Spectral Angle Mapper, Spectral Feature Fitting, Mixture Tuned Matched Filtering, and Linear Spectral Unmixing (LSU) techniques have been applied for talc abundance mapping in Jahazpur area. LSU is found to be the most useful and accurate technique in classifying spectrally pure to impure variety of talc.

中文翻译：

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使用AVIRIS-NG数据绘制印度拉贾斯坦邦贾哈兹布尔带滑石和矿物丰度的光谱特征

摘要 具有先进星载热发射和反射辐射计 (ASTER) 短波红外 (SWIR) 波段的星载数据已在全球范围内用于区分不同的粘土矿物。然而，由于ASTER传感器的带宽很宽，很难区分纯滑石矿物和不纯滑石矿物。本研究强调了机载高光谱数据机载可见光/红外成像光谱仪 - 下一代 (AVIRIS-NG) 在印度拉贾斯坦邦 Bhilwara 区 Jahazpur 带滑石矿物光谱分析中的功效。由于其更好的光谱和空间分辨率，AVIRIS-NG 被发现在识别 SWIR 区域的滑石矿物方面非常有用。滑石的特点是 AVIRIS-NG 图像中的双峰形光谱图案，在 2289.75 nm 和 2314 处具有强吸收下降。80 nm 在 ASTER 图像中无法拾取。滑石像素的光谱匹配通过样品的现场光谱和美国地质调查局、喷气推进实验室和国际地质相关计划的可用光谱库进行验证。不同滑石像素的反射率百分比变化归因于滑石化学成分的变化。然而，在 AVIRIS-NG 图像中发现了大量具有滑石和高岭石矿物光谱图案的混合像素，这些像素被发现是一种不纯的滑石。具有光谱角度映射器、光谱特征拟合、混合调谐匹配滤波和线性光谱分离 (LSU) 技术的全像素到亚像素分类技术已应用于 Jahazpur 地区的滑石丰度映射。