Work place: Department of Electronics and Communication Engineering, National Institute of Technology Warangal, Warangal, 506004, Telangana, India
E-mail: anjan@nitw.ac.in
Website: https://orcid.org/0000-0001-7709-4365
Research Interests:
Biography
ANJANEYULU LOKAM was born in 1967 in India. He received the B.Tech. (ECE), M.Tech. degree, and Ph.D. degrees from the National Institute of Technology (NIT), Warangal, India, in 1989, 1991, and 2010, respectively. He was the Project Officer at the Institute of Armament Technology, Pune, India, for five years since 1991, and was involved in the design of surface-borne and air-borne radar systems for clutter measurement applications. He worked as a Staff Scientist at Helios Systems in Chennai, India, for two years and was involved in developing radio-wave propagation assessment software modules for ship-borne radars. He has been with the Department of Electronics and Communication Engineering, NIT, Warangal, India, since 1997. His areas of interest include computer networks, electromagnetic field theory, microwave and radar engineering, microwave remote sensing, radar polarimetry, hybrid polarimetry, and neural networks and fuzzy logic systems. He has completed several R&D defense projects and has 50 papers to his credit in national and international conferences and journals. He is a Fellow of the Institution of Engineers, a Life Member of ISTE, and a member of the IEEE Antennas and Propagation Society and the IEEE Signal Processing Society since 2010. He is a Principal Investigator for an ISRO sponsored CHANDRAYAAN-2(AO-2) project-2023.
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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