Work place: Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India
E-mail: kiran.dasari@manipal.edu
Website: https://orcid.org/0009-0000-6451-1342
Research Interests:
Biography
KIRAN DASARI, Ph.D., received his Bachelor of Technology (B.Tech) degree in Electronics and Communication Engineering from the Institute of Aeronautical Engineering, JNT University Hyderabad in 2010, Master of Technology (M.Tech) degree in Embedded Systems from Padmasri BV Raju Institute of Technology, JNT University Hyderabad in 2012. He received a Doctor of Philosophy (Ph.D.) in Electronics and Communication Engineering from the National Institute of Technology, Warangal, India, in 2021. He has 12 years of teaching and research experience at various institutes. Presently working in Manipal Institute of Technology, a constituent unit of Manipal Academy of Higher Education, Manipal, Karnataka, India. He is a Co-Principal Investigator for an ISRO-sponsored CHANDRAYAAN-2. DFSAR project. He received several best paper awards at International Conferences. His areas of interest are Microwave Imaging, Remote Sensing, Earth Observation, Planetary Remote Sensing, SAR Polarimetry, Microstrip Antennas, Robotics, Embedded Systems, Machine Learning, and IOT, etc. He has been a member of the IEEE Geoscience and Remote Sensing Society since 2018 and the IEICE, Japan. He is a reviewer for various peer-reviewed journals such as IEEE Access, Remote Sensing Applications: Society and Environment, International Journal of Microwave and Wireless Technologies, Advanced Electromagnetics, Engineering, Technology & Applied Science Research (ETASR), etc., and various International Conferences.
By Saritha Mulkala Anjaneyulu Lokam Kiran Dasari Prasanna Chandrika Chenuboyina
DOI: https://doi.org/10.5815/ijwmt.2026.05.17, Pub. Date: 8 Oct. 2026
Information about the mineral makeup and whether the surface has water-related compounds can be obtained from the lunar surface’s spectral reflectance. The Chandrayaan-2 Imaging Infrared Spectrometer (IIRS) and Chandrayaan 1 Moon Mineralogy Mapper (M³) are hyperspectral instruments that can capture detailed spectral signatures across a wide range of wavelengths, from visible to infrared. This lets scientists’ study lunar materials in great detail. This paper presents a systematic methodology for analyzing and interpreting the hyperspectral data from Indian lunar missions to derive significant reflectance data. The workflow includes converting measured radiance to reflectance, applying photometric adjustments, removing thermal radiation contributions using the Planck-based model, and getting spectra from certain pixels in selected lunar areas. To study two sites, IIRS images were taken from the following two craters: Gardner crater and Glauber crater. Glauber Crater’s images facilitated a direct comparison between the two missions. From the spectrum produced, the presence of iron-based lunar rocks like olivine and pyroxene can be identified. The absorption dip observed in Gardner crater within the 3 µm band proves the presence of hydroxyl or water on the surface. On the other hand, Glauber Crater lacks an absorption dip, indicating it is dry. The spectra obtained from IIRS and data are similar in spectral shape over the same area, indicating that both instruments independently confirm the absence of hydration for characterizing the lunar surface composition. With these findings, we gain insight into the Moon’s mineral content and composition, variations in mineral properties from one area to another, and the presence of water signatures that depend on topography. The thermally corrected IIRS spectrum of Gardner crater reveals a characteristic absorption feature at 3 µm centred at 2.918 µm with band depth of 0.072 and FWHM of 0.194 µm, suggesting that there is surface OH/O on Gardner crater as has been detected before by IIRS hydration features at similar latitudes of the Moon. On the other hand, the spectra from both IIRS and M³ at Glauber crater reveal only an increase in the slope of the spectrum without showing any 3 µm hydration absorption feature. The IIRS reflectance ranges from 0.025 to 0.200 while the M³ reflectance ranges from 0.015 to 0.038. This is expected due to variations in calibration of the two sensors; however, in this case it shows consistency in the fact that there is no surface hydration.
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