Abstract In this study, we processed visible near-infrared (VNIR) and shortwave infrared (SWIR) bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to delineate glauconite-bearing zones in fossiliferous limestones, Quaternarysediments and Paleogene shales in the Lakhpat. Region of the Kachchh Province in India. Glauconitic limestone has subtle absorption features at 2.3 µm when compared to the absorption features of pure limestones that are dominated by the strong absorption feature of calcite at 2.33 µm. Additionally, the spectrum of glauconite-rich limestone also has an absorption feature at about 0.9 µm due to the crystal field effect of Fe2+ present in the glauconite structure and a feeble spectral feature due to the presence of Al-OH bonds at about 2.2 µm. ASTER resampled reflectance spectra of these rocks have been used as the reference to construct different image-enhanced products. We derived index images and Eigen matrix analysis-based principal components (PCs), using ASTER bands, to delineate different rocks in the study area. These index images are derived to enhance broadband absorption features observed in shales, glauconite-bearing and pure limestones, respectively. Principal component images are prepared using the spectral bands defining the broadband absorption features of these rocks. We found that the PC image composite, derived using PC 8, PC 2 and PC 7, is suitable to discriminate basalts, limestones and shales from each other, while an index image colour composite, prepared using three independent index images, is suitable for the identification of lithological contacts between Quaternary sediments, shales and fossiliferous limestones, respectively. In addition, the ASTER resampled rock spectrum of glauconite has a relatively lower spectral gradient in comparison to the gradient observed in the spectrum of fossiliferous limestone within the spectral range of bands 6 and 8. The spectral derivative images are derived for discriminating glauconite-rich zones within the limestone using the contrast in the spectral gradient of limestone and glauconite-rich limestone. The image composite of three spectral derivatives was compiled from the derivative image of bands 4 to 3, bands 5 to 7, and bands 6 to 8 to discriminate glauconite-rich zones from pure fossiliferous limestone. Our study proposes the potential use of broadband reflectance spectroscopy in the mineral mapping of sedimentary provinces.

中文翻译：

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反射光谱引导的宽带光谱导数方法检测印度古吉拉特邦 Kachchh 地区化石石灰岩中富含海绿石的区域

摘要 在这项研究中，我们处理了先进星载热发射和反射辐射计 (ASTER) 数据的可见近红外 (VNIR) 和短波红外 (SWIR) 波段，以描绘 Lakhpat 的含化石石灰岩、第四纪沉积物和古近系页岩中的海绿石带。 . 印度克奇省地区。与纯石灰石的吸收特征主要是方解石在 2.33 µm 处的强吸收特征相比，海青质石灰石在 2.3 µm 处具有细微的吸收特征。此外，由于海绿石结构中存在的 Fe2+ 的晶体场效应，富含海绿石的石灰石的光谱在约 0.9 µm 处也具有吸收特征，由于在约 2.2 µm 处存在 Al-OH 键，因此光谱特征微弱。这些岩石的 ASTER 重采样反射光谱已被用作构建不同图像增强产品的参考。我们使用 ASTER 波段导出索引图像和基于特征矩阵分析的主成分 (PC)，以描绘研究区域内的不同岩石。这些指数图像分别用于增强在页岩、含海绿石和纯石灰岩中观察到的宽带吸收特征。使用定义这些岩石的宽带吸收特征的光谱带准备主成分图像。我们发现使用 PC 8、PC 2 和 PC 7 导出的 PC 图像合成适合区分玄武岩、石灰岩和页岩，而使用三个独立索引图像制备的索引图像彩色合成，分别适用于识别第四纪沉积物、页岩和含化石石灰岩之间的岩性接触。此外，与在 6 和 8 波段光谱范围内的化石石灰岩光谱中观察到的梯度相比，ASTER 重采样的海绿石岩石光谱具有相对较低的光谱梯度。 光谱衍生图像用于区分富含海绿石的区域使用石灰石和富含海绿石的石灰石的光谱梯度对比。三种光谱导数的图像合成由波段 4 至 3、波段 5 至 7 和波段 6 至 8 的衍生图像编译，以区分富含海绿石的区域和纯化石石灰岩。