Nontronite mineral identification in nilgiri hills of tamil nadu using hyperspectral remote sensing

14th International Conference on Science, Engineering and Technology

自然科学;工业技术

Kumar, M. Vignesh^1 ; Yarakkula, Kiran^1

Centre for Disaster Mitigation and Management, Vellore Institute of Technology, Vellore

Tamil Nadu

632014, India^1

关键词: Atmospheric corrections;    Continuous extraction;    Hyperspectral remote sensing;    Industry requirements;    Mineral identification;    Minimum noise fraction;    Spatial informations;    Spectral angle mappers;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/263/3/032001/pdf
DOI  :  10.1088/1757-899X/263/3/032001

来源: IOP

【 摘 要 】

Hyperspectral Remote sensing is a tool to identify the minerals along with field investigation. Tamil Nadu has abundant minerals like 30% titanium, 52% molybdenum, 59% garnet, 69% dunite, 75% vermiculite and 81% lignite. To enhance the user and industry requirements, mineral extraction is required. To identify the minerals properly, sophisticated tools are required. Hyperspectral remote sensing provides continuous extraction of earth surface information in an accurate manner. Nontronite is an iron-rich mineral mainly available in Nilgiri hills, Tamil Nadu, India. Due to the large number of bands, hyperspectral data require various preprocessing steps such as bad bands removal, destriping, radiance conversion and atmospheric correction. The atmospheric correction is performed using FLAASH method. The spectral data reduction is carried out with minimum noise fraction (MNF) method. The spatial information is reduced using pixel purity index (PPI) with 10000 iterations. The selected end members are compared with spectral libraries like USGS, JPL, and JHU. In the Nontronite mineral gives the probability of 0.85. Finally the classification is accomplished using spectral angle mapper (SAM) method.