Abstract
Hapkeās bidirectional reflectance function based on the theory of radiative transfer has been implemented for modeling the spectra derived from Chandrayaan-1 hyperspectral images. The parameter study was done to study the behavior and influence of each parameter like grain size, porosity, iron fraction which represents the degree of space weathering and phase function was critically assessed. The model was then tested against the four standard lunar mixtures which constitutes of major lunar minerals from RELAB, and it was observed that the artificially created model spectra were successful in reproducing the overall trend in the resultant spectra. Finally, the nine representative spectra derived from hyperspectral image of the Chandrayaan-1 HySI sensor covering part of Mare Vaporum were modeled. The mass fraction of the surface minerals along with the associated Hapke parameter was predicted.
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Acknowledgements
āThe author is thankful for the financial assistance received from DoS (Department of Space, ISRO/SSPO/Ch-1/2016-17, August 17, 2016). This work is a part of the ISRO project under Chandrayaan-1 AO (Announcement of Opportunity) program. The research is based (partially or to a significant extent) on the results obtained from the Chandrayaan-1, first lunar mission of the ISRO, archived at the Indian Space Science Data Center (ISSDC).ā
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Mohammed Zeeshan, R., Sayyad Shafiyoddin, B. (2020). Implementation of the Bidirectional Reflectance Function for Modeling the Spectra Derived from Hyperspectral Images. In: Reddy, V., Prasad, V., Wang, J., Reddy, K. (eds) Soft Computing and Signal Processing. ICSCSP 2019. Advances in Intelligent Systems and Computing, vol 1118. Springer, Singapore. https://doi.org/10.1007/978-981-15-2475-2_45
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