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Airborne hyperspectral data for mineral mapping in Southeastern Rajasthan, India

机译:拉贾斯坦邦东南部的矿物测绘的空中高光谱数据

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Geology majorly deals with the structures, features, minerals, rocks, etc. of the planet Earth. Geologists are using the technology of remote sensing for structural interpretation and regional mapping. Ores and minerals identification are also done with the help of remote sensing. This paper is mainly focused on the identification of minerals and mapping with the help of various algorithms such as Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Mixture Tuned Matched Filtering (MTMF) using airborne hyperspectral data. Minerals are identified on the basis of the visible and near-infrared spectral reflectance. Spectral reflectance is having absorption features at different positions and absorption peaks are used for the analysis of imagery. This technique provides surface mineralogical details. SAM algorithm mainly computes the angle between the unknown pixel spectrum and unique pixel spectrum. SFF algorithm matched the continuum removed the spectrum of the imagery pixel from the continuum removed reference spectra. MTMF algorithm detects the abundance of the minerals and removes the erroneous positive. Total 13 endmembers (minerals) were identified in the study area. These minerals are grouped into clay minerals, iron minerals, carbonate minerals, and other minerals. These endmembers are used for the mineral map creation from different algorithms. Algorithms produce the diverse kind of mineral map and these are compared with each other on the basis of the mineralogy and discrimination of mineralized region from settlements. Mineral map produced by MTMF algorithm provides convenient results with better accuracy than other algorithms.
机译:地质主要处理行星地球的结构,特征,矿物质,岩石等。地质学家正在利用遥感技术进行结构解释和区域映射。在遥感的帮助下也完成了矿石和矿物质识别。本文主要集中在诸如光谱角映射器(SAM)等各种算法的帮助下识别矿物质和映射,使用空气过光数据,光谱特征拟合(SAM),光谱特征拟合(SAFF)和混合调谐匹配滤波(MTMF)。基于可见和近红外光谱反射率来识别矿物质。光谱反射率在不同位置处具有吸收特征,并且吸收峰用于图像的分析。该技术提供表面矿物学细节。 SAM算法主要计算未知像素频谱和唯一像素谱之间的角度。 SFF算法匹配,连续体删除了从连续内移除的参考光谱的图像像素的频谱。 MTMF算法检测矿物质的丰富并消除错误的正面。在研究区内确定了13个终点(矿物质)。这些矿物组分为粘土矿物,铁矿物,碳酸盐矿物和其他矿物质。这些终端用来用于来自不同算法的矿物地图。算法产生多样化的矿物地图,这些矿物地图是基于矿化区的矿化区与沉淀区域的矿化区相互比较。 MTMF算法生产的矿物地图提供了方便的结果,比其他算法更好。

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