Daytime surface temperatures of the Moon derived from high-resolution IIRS on-board Chandrayaan-2

Daytime surface temperatures of the Moon derived from high-resolution IIRS on-board Chandrayaan-2 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Daytime surface temperatures of the Moon derived from high-resolution IIRS on-board Chandrayaan-2 Subhadyouti Bose, Denesh Karunakaran, Tvisha Kapadia, Neha Panwar, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6816265/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The Imaging Infra-Red Spectrometer (IIRS) on-board Chandrayaan-2 has been mapping the lunar surface since 2019 with high spatial (80 m/pixel) and spectral resolutions (20–25 nm). IIRS’s spectral range from 0.7 to 5 µm allows it to differentiate between the reflected as well as the thermal components. In this study, we have derived surface temperatures from sixteen IIRS strips, sourced from different parts of the lunar surface by inverting the Planck’s equation. Thereafter, for the first time, we have compared IIRS-derived temperatures with those retrieved from a lunar thermal model and Diviner. The results show that the temperature estimates from IIRS data are in good agreement with the thermal model and the Diviner data over a specific latitude range of ± 60° and time window of 09:30 − 14:00 hours local lunar time. The minimum and maximum mean absolute differences obtained for the temperature estimates by IIRS and the thermal model are 0.69 K and 23.9 K, respectively, for our suggested time and latitudinal range. These results demonstrate the robustness and reliability of the high-resolution IIRS-derived surface temperatures. Further, using the temperatures obtained from IIRS data, we investigated a part of the floor of the Schrödinger Basin comprising of a volcanic vent and found compositional diversity pointing towards the most recent and previously undetected episode of magmatic activity in the region. The findings were validated using Clementine-UVVIS multispectral data and crater chronology studies using Lunar Reconnaissance Orbiter – Narrow Angle Camera (LRO-NAC) data. This study, thus, highlights the importance of using high-resolution surface temperatures from IIRS to unravel such hitherto unknown aspects of lunar geology. Planetary Science Planetary Geology Moon Moon surface Schrödinger Basin Infrared observations Instrumentation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. Introduction Satellite-based observations of the lunar thermal environment began with Clementine, followed with Diviner Lunar Radiometer Experiment (DLRE) on-board the Lunar Reconnaissance Orbiter (LRO) mission. The Diviner instrument measures the lunar surface irradiance using a nine-channel radiometer that operates between a wavelength range from the visible to near-infrared (0.3 µm, VNIR) up to the far infrared (400 µm, FIR) ( Paige et al., 2010 ). Diviner was followed by two separate four-channel microwave radiometers (MRM) on-board Chang’E-1 (Fa and Jin, 2010 ), and Chang’E-2 missions (Gong and Jin, 2012 ). The spatial resolution of the Chang’E-1 MRM sensor is ~ 35 to 50 km/pixel, from 200 km above the lunar surface (Zheng et al., 2012) , while the brightness temperature (T B ) maps produced from CE-1 and CE-2 are binned at a spatial resolution of ~ 15 km/pixel and ~ 6 km/pixel, respectively (Zheng et al., 2019) . On the other hand, Diviner senses the surface irradiance at a spatial resolution of ~ 240 to ~ 320 m/pixel at the equator. Diviner is successful in mapping the global daytime and nighttime surface temperatures of the Moon after its injection into the lunar orbit in 2009 (Williams et al., 2017 ). The Indian Space Research Organization (ISRO) launched its second mission to the Moon on 22 July 2019, which carried one of the most advanced imaging spectrometers, Imaging Infra-Red Spectrometer (IIRS), along with seven other instruments. IIRS is the first lunar spectrometer that can operate in the extended wavelength range of ~ 0.7 µm to ~ 5 µm. In addition, the spatial resolution of IIRS is 80 m/pixel, which is attained from a nearly constant altitude of ~ 100 km on a polar circular orbit. Prior to IIRS, the Moon Mineralogy Mapper (M 3 ) sensor, sent on-board Chandrayaan-1, operated in the range of 430 to 3,000 nm. M 3 was designed to capture hyperspectral images at a resolution of ~ 140–280 m/pixel from 100–200 km above the lunar surface. However, in the case of IIRS, in addition to being useful to properly capture the 3-µm OH/H 2 O feature (extending from ~ 2.8 to ~ 3.5 µm), the enhanced spectral coverage also provides an opportunity to investigate the thermally affected component of the electromagnetic spectrum, which ideally begins after ~ 2.5 µm and becomes significant beyond ~ 3 µm. Verma et al., ( 2022 ) have removed the thermal component from IIRS data (between 2 to 3.5 µm, the “shorter wavelength”) by estimating the thermal emissions in the range of 4 to 5 µm. Moreover, the wavelength range between 3.5 to 5 µm (the “longer wavelength”) may also be used to study the thermophysical properties of the lunar surface. Additionally, Ojha et al., ( 2024 ) have estimated surface temperatures from a part of a single IIRS strip and compared them with Diviner. The motivation to conduct this study stems from the fact that, to date, the global surface temperatures of the Moon are available only at a highest spatial resolution of ~ 240 to ~ 320 m/pixel from the Diviner instrument onboard LRO. Now, we have IIRS data available at a higher spatial resolution of ~ 80 m/pixel. Hence, we aimed to test whether IIRS data, which has thermal bands between 4.5 to 5 microns, could be used to derive reliable surface temperature estimates for the Moon. For this purpose, we have used multiple IIRS images, data derived from a thermal model ( Hayne et al., 2017 ), and corresponding Diviner data spanning different latitudes, times of acquisition, and terrain types to obtain a robust and reliable correlation between the temperature values. Further, in this study, we seek to demonstrate the application of IIRS-derived surface temperatures in resolving a candidate problem related to lunar geology. 2. Study areas Eighteen IIRS images, acquired between ~ 08:00 and ~ 16:30 hours local time, have been analysed in this work, with the image extents stretching between the latitudes of ~ 67° N up to ~ 73° S, thereby covering a wide range of latitudes across the lunar surface (Fig. 1 ; Table S1). A few of these images largely represent the lunar maria (Oceanus Procellarum, Mare Serenitatis, Mare Tranquillitatis, Mare Fecunditatis, Mare Crisium, as well as parts of Mare Moscoviense). One of the 16 images stretches from ~ 44° N to ~ 44° S and includes an area that passes through highlands to the north of Mare Crisium, as well as the highlands to the south of Mare Fecunditatis. The particularly large extent of the image allows us to study temperature variations across a wide range of latitudes as well as different types of surfaces. The justification behind selecting these images is to showcase the variation of surface temperatures as a function of terrain types, latitudes, and times of data acquisition. Results derived and discussions pertaining to these images have been presented in Section 4 . 3. Data and methods 3.1 Chandrayaan-2 IIRS data and thermal model Calibrated IIRS Level-1 (CODMAC Level 3, NASA PDS L1B) radiance data have been used in this study (Table S1). Each IIRS pixel is radiometrically corrected, band-separated, dark corrected, and provides band-to-band registered surface radiance (SI unit: W/(m 2 Sr µm)). Additionally, each of the IIRS images were manually seleno-referenced to their actual Ground Control Points by performing a rigorous image-to-image seleno-referencing with LRO-WAC as the reference image. Individual seleno-referenced IIRS products were then re-verified using a global LRO-WAC mosaic. The IIRS images selected in this study were captured at different local times of a lunar day. This was done to check the various temperature trends across different lunar local times. These sixteen images cover different latitude zones on the lunar surface (Fig. 1 ), thereby exhibiting the influence of latitude on surface temperatures. In addition, we have used two more images from a polar region to demonstrate the scientific application of the IIRS-derived temperatures. The radiance pixels from all the images were converted to surface temperatures by inverting the Planck blackbody function (Eqs. 1 & 2) and by assuming a constant emissivity value of 0.95 for all the images. \(\:{B}_{\lambda\:}\left(T\right)=\frac{{2hc}^{2}}{{\lambda\:}^{5}}\frac{1}{{e}^{\frac{hc}{\lambda\:kT}}-1}\) (1) , where, h is the Planck’s constant, c is the speed of light, k is the Boltzmann constant and T is temperature. $$\:T=\frac{hc}{\lambda\:kln\left(\epsilon\:\pi\:\frac{{2hc}^{2}}{{I\lambda\:}^{5}}+1\right)}$$ \(\:I=\epsilon\:\pi\:\frac{{2hc}^{2}}{{\lambda\:}^{5}}\frac{1}{{e}^{\frac{hc}{\lambda\:kT}}-1}\) (2) , \(\:I\simeq\:\epsilon\:\pi\:{B}_{\lambda\:}\left(T\right)\forall\:\lambda\:>4.5\mu\:m\) ; ε and T are constant for a given pixel. Further, these derived surface temperatures from the IIRS data were compared with the temperature values derived from a standard lunar thermal model (Hayne et al., 2017 ). For the sake of completeness, we have provided the comparisons with Diviner data in the supplementary material (Sections S2 and S3). 3.2 Clementine UVVIS and LRO-NAC data We have used 5-band Clementine UVVIS (200 m/pixel) and high-resolution LRO-NAC (0.5 m/pixel) data to validate the results from the IIRS-derived surface temperatures to decipher possible mineralogical variations and estimate the age of the selected site, i.e., a pyroclastic deposit on the floor of the Schrödinger Basin. A colour-ratio map was then generated from the UVVIS reflectance data (with band centres at 415, 750, 900, 950, and 1,000 nm), which was prepared using the following colour-combination – red: \(\:\left(\frac{750}{415}\right)\) nm, green: \(\:\left(\frac{750}{950}\right)\) nm, and blue: \(\:\left(\frac{415}{750}\right)\) , as described in McEwen et al., ( 1994 ). The LRO-NAC images were used to obtain age estimates based on crater chronology ( Michael and Neukum, 2010 ) of the vent in order to determine the period of major emplacements and resurfacings. Accordingly, crater size-frequency distribution (CSFD) measurements have been used to reveal the age of the vent. Sufficient care was taken to avoid the count areas with significant slopes (< 7°), which further act in minimizing the chances of errors in the estimation of surface ages. A cumulative resurfacing correction has been applied to account for the errors induced due to erosion mantling of smaller craters and other resurfacing processes ( Michael and Neukum, 2010 ) . 4. Results and discussion 4.1 Analysis of surface temperatures derived from IIRS and the thermal model Our analysis of the IIRS dataset (images obtained between the lunar local times of ~ 08:00 and ~ 16:30 hours) reveals that the mean temperature differences (obtained by subtracting the IIRS temperature means from the corresponding model-derived temperature means for each image) are the highest towards the early morning (prior to ~ 09:30 hours) as well as later in the day (after ~ 14:00 hours) on the Moon (Fig. 2 ). Based on this analysis, we were able to identify a block of time during which the mean differences between IIRS and model-derived temperature data were comparatively less. The mean difference varied between 0.69 K – 23.9 K between ~ 09:30 and ~ 14:00 hours on the lunar surface. Therefore, the local lunar times of ~ 09:30 to ~ 14:00 hours represent the optimum time range during which the temperatures estimated from IIRS would be the most reliable and comparable to the corresponding model-derived temperature data. During these local timings, the Sun remains at a sufficient angle above the lunar surface (< 40 ο ) (Williams et al., 2017 ), which allows IIRS to accumulate sufficient thermally emitted signal in the spectral range of 4.5 to 5 µm. Beyond these times, a large deviation between IIRS and model-derived temperatures is recorded, due to non-optimum solar illuminationconditions. Similar discrepancies are observed when we compared the IIRS-derived temperatures with the temperatures derived from Diviner (Fig. S1). To analyse the differences between the model-derived and observed temperatures, we used 9 IIRS images such that they were acquired within our proposed time frame. The temperatures estimated from IIRS were compared with the model using two different criteria – (i) at every 10° latitude we compared IIRS-derived mean temperature against the model-derived temperature across an entire lunar day, and (ii) at a fixed local time (IIRS image acquisition time) and over latitude bins of 1° (± 0.5°), we plotted IIRS data pixels from within that bin. From the population of pixels of an entire IIRS image, we have selected a small sample of pixels (~ 80,000 to ~ 100,000) within a ± 0.5° latitudinal range around each specific latitude and then calculated the mean for that range. For every corresponding latitudinal bin of IIRS, temperatures were also estimated from the thermal model at every 0.5° latitude, which have been plotted over the IIRS temperature pixels (Figs. S1 to S4). To better describe the goodness of fit between the temperatures obtained from IIRS and the thermal model, pixels sampled from IIRS images along with their mean (dashed red line) were plotted across the different latitudes and were overlaid by the values retrieved from the thermal model at latitudinal intervals of 0.5° (solid yellow line). The estimated temperatures fell within the 2σ bounds as shown in Fig. S1 (d-f), Fig. S2 (f-j), Fig. S3 (c-d), and Fig. S4 (n-z) by the light red band, which ensured the statistical significance of this data. This comparison allowed us to analyse the temperature variations observed in real time from IIRS caused by differences in latitude, lunar local time, topography, and solar incidence angle at a higher spatial resolution. Table 1 Table showing mean temperature values obtained from the modeled data as well as the observed IIRS data and their absolute differences in K, with respect to different local times and latitudes. Group number Image IDs Local acquisition time Latitudes (± 0.5° bins) IIRS mean temperature (K) Model mean temperature (K) Absolute difference [IIRS-Model] (K) 1 CH2_IIR_NCI_20210706T0928053245 09:28 20 358.32 354.19 4.13 10 361.4 359.51 1.89 0 363.8 360.64 3.16 2 CH2_IIR_NCI_20231119T1021387279 CH2_IIR_NCI_20211130T1106576194 10:21 to 11:06 40 344.12 352.45 8.33 30 352.36 366.15 13.79 20 351.97 375.27 23.3 10 358.7 380.36 21.66 0 358.05 381.95 23.9 3 CH2_IIR_NCI_20211231T1149584496 11:49 40 345.61 359.37 13.76 30 358.44 373.05 14.61 4 CH2_IIR_NCI_20210610T1302166936 CH2_IIR_NCI_20191206T1305147603 CH2_IIR_NCI_20191210T1310531966 CH2_IIR_NCI_20240122T1333597453 CH2_IIR_NCI_20210126T1349194455 13:02 to 13:49 60 311.57 303.58 7.99 50 324.49 331.17 6.68 40 342.33 351.2 8.87 30 356.37 365.21 8.84 20 367.89 374.61 6.72 10 379.09 379.78 0.69 0 380.18 381.61 1.43 -10 370.08 379.97 9.89 -20 362.77 374.99 12.22 -30 353.71 365.82 12.11 -40 337.28 352.09 14.81 -50 327.83 332.42 4.59 -60 301.98 305.32 3.34 As shown in Table 1 , four separate groups (Groups 1 to 4) were created, which consists of the nine IIRS images that were acquired at a specific local time (between ~ 09:30 to ~ 14:00 hours). These groups have been created on the basis of local time such that images acquired within a period of one hour could be compared with each other as well as with the model. By analysing the data from all the four groups, we found the temperature differences between the model and the observed dataset to be in line with the expected trends for the lunar surface. However, at a few latitudes (in Group 2, between 0° to 20° and Group 4, between − 10° and − 30°), some anomalous differences have been noted that can be identified from the figures (Figs. S2 and S4). In these cases, the mean of the modeled temperature exceeds the 2σ range of the sampled pixels, which could be attributed to local topography, solar incidence angles, regolith properties, unusual albedo/emissivity properties of the crater walls/floors, and anisotropic thermal emissions from rough, sunlit surfaces (Paige et al., 2010) . We have also shown for each group (Fig. 3 (a-d)) the temperature range (maximum and minimum) obtained from each IIRS data as per the data shown in Table 1 (in blue), 2σ bound (in green), ‘X’ (in red) signifying the model-derived temperature, with the actual latitude range created according to 1° bin (in yellow) for every 10° latitude as per each IIRS image extent. The absolute differences obtained between the thermal model and IIRS data between the latitudes of ± 60° (Group-4) have been shown in Fig. 4 . 4.2 Application of the IIRS-derived surface temperatures: A case-study from the Schrödinger Basin To describe the utility of the surface temperatures derived from IIRS, we performed a case-study on a volcanic deposit that is located around a vent on the floor of the ~ 326-km-wide Schrödinger Basin. The importance of such a study on the floor of the Schrödinger Basin can be underscored by the following reasons – it is the best-preserved impact basin of its size on the Moon ( Kramer et al., 2013 ; Wilhelms et al., 1987 ); the location of Schrödinger at the eastern edge of the oldest and the largest impact basin on the Moon - the South Pole-Aitken (SPA) Basin, provides an exciting opportunity to study the possibility of the presence of ejecta from SPA being found in and around Schrödinger itself and, the fact that a vent located on the floor of the basin could have acted as a large source of volatiles as well as harbour a large pyroclastic deposit, thus highlighting the immense potential of Schrödinger Basin being an interesting location for a near-future human exploration base. An investigation that focuses on the thermal aspects of the floor of the basin would likely add impetus to the ongoing studies of the scientifically important Schrödinger Basin and the nearby Permanently Shadowed Regions (PSRs) located near the Lunar South Pole. We investigated the surface temperatures obtained from around a vent (75.33° S, 139.22° E) inside the ~ 326-km-diameter Schrödinger Basin (Fig. 5 ). Surrounding the vent is a large mafic deposit encompassing an area of ~ 795 km 2 , which is the focus of our study. A longitudinal fracture passing through the centre of the vent appears to dissect the vent into two symmetric parts. A 3-D rendering created using LRO-NAC DTM (5 m/pixel) shows the elevated nature of the vent (Fig. 6 ). In this case-study, we have used two IIRS images that overlap each other near the vent, allowing us to investigate the thermal characteristics of the surface around the vent. These two IIRS images were acquired at 08:27 and 10:25 hours local time from a polar region. We selected the image obtained at 08:27 hours despite it lying beyond the recommended timeframe as well as latitude range (Section 4.1 ) because we wanted to study the relative temperature difference between the two images. Also, the Schrödinger Basin is one of the limited regions where a sufficient overlap among two IIRS images was available. In order to investigate possible temperature variations, the overlapping part between the two images were extracted and temperature differences were obtained (Fig. 7 (a-c)). A temperature asymmetry around the vent is quite evident in the overlapping part wherein the south-eastern part shows considerably lower temperatures as compared to the north-western part (Fig. 7 (a, b)), suggesting the possibility of the occurrence of two distinct units. Also, the temperature differences around the vent were found to be non-uniform (Fig. 7 (c)). A marked variation exists between the north-western and the south-eastern side. In order to quantify this variation, two subsets, Subset-1 and Subset-2, were created on either side of the vent (Fig. 7 (c)). Subset-1 showed an average temperature variation (i.e., the difference between the maximum and minimum temperatures) of ~ 50 K, whereas the Subset-2 experienced an average temperature difference of ~ 62 K, during approximately two hours of difference in data acquisition time. This further strengthens the proposition that there could be two distinct units around the vent. Subsequently, to delineate the entire extent of the volcanic deposit, we merged the two temperature images, assuming them to be acquired during similar time of a lunar day. This resulted in the generation of a temperature map of the study area, using which we were able to identify the boundaries of the two units (Fig. 8 ). The relatively warmer unit is named as Unit-1, while the other unit is named as Unit-2 (Fig. 8 ). The average surface temperature for Unit-1 is ~ 305 K, whereas the average for Unit-2 is ~ 277 K. Possible reasons for this could be due to variation in material composition, physical properties, and topography. Delineation of the effect of these parameters warrants a further investigation. We studied the mineralogical composition of the Units-1 and − 2 using Clementine UVVIS data. A colour-ratio map (Fig. 9 ) generated using the band-combinations of McEwen et al., ( 1994 ) indicate a difference in the surface composition of the area around the vent. The Unit-1 predominantly shows red-orange tones which are suggestive of the presence of low-Ti mafic soils in the region. In contrast, the Unit-2 primarily shows a bluish tone, indicating the presence of higher-Ti mafic soils. In order to estimate the emplacement history of the region, crater counting has been carried out for the Units 1 and 2. The results reveal an age of \(\:{3.6}_{-0.08}^{0.05}\) Ga for the Unit-1 by fitting the curve for crater diameter (D) range 500 m < D < 2000 m (Fig. 10 ). Volcanic resurfacing has been observed in the Unit-1 at 1.8 ± 0.2 Ga by fitting the curve for crater diameter range 250 m < D < 500 m. On the other hand, Unit-2 exhibits a crater chronology-derived age of \(\:{3.7}_{-0.01}^{0.06}\) Ga by fitting the curve for crater diameter range 500 m < D < 1000 m. Similar to Unit-1, a volcanic resurfacing also occurred in Unit-2 at 2.5 ± 0.4 Ga, which was interpreted by fitting the curve for crater diameter range 250 m < D < 500 m. Hence, three different episodes of volcanic activity have been observed around the vent. Although the statistical significance of the difference in ages between Units 1 and 2 is 1.56σ, the compositional study indicates that these are two distinct units with different mineralogy. Therefore, it is quite likely that they were emplaced during separate volcanic eruptions. The older ages for Unit-1 are consistent with the results from Kring et al., ( 2021 ). However, the younger episodes at ~ 1.8 Ga and ~ 2.5 Ga in Units-1 & -2, respectively, have been reported herein for the first time. Thus, the units deciphered on the basis of IIRS-derived temperature maps exhibit different compositions and they were emplaced during timeframes. It is important to note that the ~ 1.8 Ga resurfacing found in Unit-1 is the youngest reported volcanic activity in the Schrödinger Basin. The physical properties of the regolith could also be playing a role in the temperature variation of the region. These physical properties can be influenced by the compositional differences and the age of the unit. It is also possible that the topography could affect the derived temperatures. However, the slope of the entire region around the vent is gradual (< 7°), indicating a lack of significant topography around it (Fig. 11 ). Hence, the local topography does not seem to be playing a major role in this region, as evident in the temperature difference image in (Fig. 7 (c)). Therefore, the observed temperature differences could likely be due to the existence of two distinct types of surfaces on the opposite sides of the vent. 5. Conclusions A detailed analysis of the surface temperatures derived from IIRS radiance data has been carried out in this study. Sixteen IIRS images have been used to understand how surface temperatures vary across different latitudes, terrains, and local time. The IIRS images studied in this work showed the expected latitudinal variations - decreasing temperatures with increasing latitude amongst all the images. In order to compare and validate the results obtained from IIRS data, we have used the lunar thermal model implemented by Hayne et al., ( 2017 ) and at every 10° latitude we compared IIRS-derived mean temperature against the model-derived temperature across an entire lunar day as well as at a fixed local time (IIRS image acquisition time) and over latitude bins of 1° (± 0.5). In addition to the thermal model, we have also used Diviner data to test and validate the temperatures obtained from IIRS. Our analyses of the IIRS-derived temperatures reveal the following information: (1) IIRS data captured between ~ 09:30 and ~ 14:00 hours local time can be reliably used to estimate lunar surface temperatures between the latitudes of ± 60° across the lunar surface, and (2) the temperature differences obtained from IIRS, the thermal model and Diviner data point towards the expected trends across the lunar surface. We checked data from the three datasets over maria and highlands while keeping the latitudes and times of acquisition as constant and found that the mean differences tend to vary more across the highlands as compared to the mare. When we fixed the surface types as well as the time of data acquisition and varied the latitudes, we found the differences to increase as a function of latitude. Additionally, it was found that the temperatures retrieved from the thermal model fit the IIRS-derived temperatures across different latitudes as well as local time. Absolute errors calculated between the model and IIRS varied between ~ 0.7 K and ~ 24 K. Further, using two more IIRS images, we conducted a case study on the floor of the Schrödinger Basin which includes a volcanic vent, known as Schrödinger G. Based on our analysis, we were able to identify two distinctly different units within the same deposit. In order to validate the finding, we have used multispectral Clementine-UVVIS data to generate a colour-ratio map (Fig. 9 ). Further, we found that these two units experienced late-stage volcanic activity. Unit-1 experienced volcanic resurfacing at ~ 1.8 Ga, whereas the Unit-2 had volcanic resurfacing at ~ 2.5 Ga (Fig. 10 ). Hence, IIRS data was instrumental in bringing out the differences in the volcanic units, using which we were able to discern the geological diversity of the region. Thus, in a nut-shell, the results obtained in this study bring out the potential of using IIRS data for estimating the day time surface temperatures across the lunar surface at a high spatial resolution and highlight its usefulness in deciphering the geological diversity. Also, for the first time, a comparison between a thermal model and IIRS data has been shown in this study, which strengthens the reliability and robustness of the IIRS data within the suggested time frame. We propose that the surface temperatures measured by IIRS could be used to further understand the lunar thermal environment at a high spatial resolution. Declarations Acknowledgments We thank the Department of Space, Government of India, for providing financial support for this work. We acknowledge the use of data from Chandrayaan-2, the second lunar mission of the Indian Space Research Organization (ISRO), archived at the Indian Space Science Data Centre (ISSDC), publicly available at ISSDC Pradan (https://pradan.issdc.gov.in/ch2/). We also gratefully acknowledge the LRO-Diviner science team, the LRO-WAC, and LRO-NAC teams for providing publicly accessible data. Annu Kumari is gratefully acknowledged for help in seleno-referencing the IIRS dataset. We are thankful to Prof. Anil Bhardwaj, Director, PRL, and Prof. Varun Sheel, Chairman, PSDN, for their constant support to carry out this work. Shri A. S. 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Paige, D.A., Siegler, M.A., Zhang, J.A., Hayne, P.O., Foote, E.J., Bennett, K.A., Vasavada, A.R., Greenhagen, B.T., Schofield, J.T., McCleese, D.J., Foote, M.C., DeJong, E., Bills, B.G., Hartford, W., Murray, B.C., Allen, C.C., Snook, K., Soderblom, L.A., Calcutt, S., Taylor, F.W., Bowles, N.E., Bandfield, J.L., Elphic, R., Ghent, R., Glotch, T.D., Wyatt, M.B., Lucey, P.G., 2010. Diviner Lunar Radiometer Observations of Cold Traps in the Moon’s South Polar Region. Science 330, 479–482. https://doi.org/10.1126/science.1187726 Ren, H., Nie, J., Dong, J., Liu, R., Fa, W., Hu, L., Fan, W., 2021. Lunar Surface Temperature and Emissivity Retrieval From Diviner Lunar Radiometer Experiment Sensor. Earth Space Sci. 8, e2020EA001436. https://doi.org/10.1029/2020EA001436 Vasavada, A., 1999. Near-Surface Temperatures on Mercury and the Moon and the Stability of Polar Ice Deposits. Icarus 141, 179–193. https://doi.org/10.1006/icar.1999.6175 Verma, P.A., Chauhan, M., Chauhan, P., 2022. Lunar surface temperature estimation and thermal emission correction using Chandrayaan-2 imaging infrared spectrometer data for H 2 O & OH detection using 3 μm hydration feature. Icarus 383, 115075. https://doi.org/10.1016/j.icarus.2022.115075 Williams, J.-P., Paige, D.A., Greenhagen, B.T., Sefton-Nash, E., 2017. The global surface temperatures of the Moon as measured by the Diviner Lunar Radiometer Experiment. Icarus 283, 300–325. https://doi.org/10.1016/j.icarus.2016.08.012 Wilhelms, D., McCauley, J., Trask, N., 1987. The geologic history of the Moon (Professional Paper), 1348. U.S. Geological Survey, Washington D.C. Additional Declarations The authors declare no competing interests. Supplementary Files SupportingInformation.docx Supplementary information for the manuscript Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6816265","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":466565273,"identity":"9c036425-c9cc-4fc4-bc06-c121c1376892","order_by":0,"name":"Subhadyouti Bose","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABNUlEQVRIie2RMUvEMBSAEwJx6enacmL+Qkuh4G9x6SHo0jh3OEundKl7Bbn+hXPp3BKoS9C1oENBEIdD6tbBA9Me6OH1UDfBfJAHebyPl/cCgELxJ9GwDPnnHffRlweh8DeK6BT4Q6UHsj4OKiShZd2ChwMShei58QOyu3NRNK+z86O9SCqtn31VzOrs1IrBk22KHB8mgltMuz02LrMbmnAYwljcbyi65+ga4JO57mJ7xHIXywwaZSUNpYIg21BI4jnGm1TStMb2kgUuJgsHLa9Kmm5RQOU5465LWAH0CBmSXTRH7mpK51sUU7ycjPfNbpYJky/vZvFsIy5zei2VYmAWEtHSWPjdxjhvWrkxEgmraacBnd3xom79zYeteq3+Ql9L8T7mw/UfoGbtEnxTrFAoFP+Id63+dfZ3GZeqAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-1574-4550","institution":"Physical Research Laboratory","correspondingAuthor":true,"prefix":"","firstName":"Subhadyouti","middleName":"","lastName":"Bose","suffix":""},{"id":466565274,"identity":"561838d3-48bd-48ff-af21-2b727bfa7219","order_by":1,"name":"Denesh Karunakaran","email":"","orcid":"","institution":"Department of Civil, Environmental and Geo-Engineering, University of Minnesota, Minneapolis","correspondingAuthor":false,"prefix":"","firstName":"Denesh","middleName":"","lastName":"Karunakaran","suffix":""},{"id":466565275,"identity":"0527360b-0dc7-4a54-a670-2c353a9a5772","order_by":2,"name":"Tvisha Kapadia","email":"","orcid":"","institution":"Physical Research Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Tvisha","middleName":"","lastName":"Kapadia","suffix":""},{"id":466565276,"identity":"d4264698-4124-4768-95d0-1d175a7f0f60","order_by":3,"name":"Neha Panwar","email":"","orcid":"","institution":"Physical Research Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Neha","middleName":"","lastName":"Panwar","suffix":""},{"id":466565277,"identity":"6f2e8b5b-566e-4704-bce0-3754eaf33748","order_by":4,"name":"Arpeet Chandane","email":"","orcid":"","institution":"Physical Research Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Arpeet","middleName":"","lastName":"Chandane","suffix":""},{"id":466565278,"identity":"72c5f756-c95e-4188-938e-108e789906ce","order_by":5,"name":"Neeraj Srivastava","email":"","orcid":"","institution":"Physical Research Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Neeraj","middleName":"","lastName":"Srivastava","suffix":""}],"badges":[],"createdAt":"2025-06-04 04:47:07","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6816265/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6816265/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84197657,"identity":"ec66c5ce-dd27-4f1b-bc8f-cbcb8669bcaa","added_by":"auto","created_at":"2025-06-09 08:01:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1432714,"visible":true,"origin":"","legend":"\u003cp\u003eSurface temperature images derived from the sixteen IIRS strips used in this study have been overlaid on an LRO-WAC global mosaic. In addition, we have taken two images from a high-latitude region to demonstrate the scientific application of the IIRS-derived temperatures. Details about the images shown here are tabulated in Table S1.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/00237a51f2a87318259fa580.png"},{"id":84197659,"identity":"2dd84881-7c42-49b5-b0ff-b87e7bb9438a","added_by":"auto","created_at":"2025-06-09 08:01:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":171523,"visible":true,"origin":"","legend":"\u003cp\u003eA\u003cstrong\u003e \u003c/strong\u003eplot showing the absolute differences between the mean temperatures obtained from IIRS and the thermal model, which was run as per the acquisition times of IIRS. A time block extending from ~09:30 hours up to ~14:00 hours, during which the calculated absolute mean differences are relatively smaller, is shown in blue.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/71354feba8f6b1330a035b05.png"},{"id":84198708,"identity":"31c603b7-aa18-4fa3-8fab-8d84b16ded1f","added_by":"auto","created_at":"2025-06-09 08:09:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":265777,"visible":true,"origin":"","legend":"\u003cp\u003ePlots showing the temperature range (maximum and minimum) obtained from each IIRS data as per the data shown in Table 1 (in blue), 2σ bound (in green), ‘X’ (in red) signifies the model-derived temperature, with the actual latitude range created according to 1° bin (in yellow) for every 10° latitude as\u003cem\u003e \u003c/em\u003eper each IIRS image extent. (a) presents the data for Group-1, (b) for Group-2, (c) for Group-3, and (d) for Group-4.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/f978a50a5f62b5cac27dec8c.png"},{"id":84197662,"identity":"d66e9f0a-4abd-4681-98a2-9bc27dffd8c2","added_by":"auto","created_at":"2025-06-09 08:01:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":264573,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of IIRS and model-derived temperatures for Group-4 (latitudes 60 to -60 at 13:02 to 13:49 hours local lunar time). The green line indicates the model-derived temperature, while the blue line indicates the IIRS-derived temperatures obtained at a coordinated time for both the datasets. The absolute errors obtained from Group 4 have been shown with a red dotted line.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/005cdbd9d9f2e39de265a8e4.png"},{"id":84198712,"identity":"907da24d-2780-4b9a-aaa1-c0042d2683a6","added_by":"auto","created_at":"2025-06-09 08:09:12","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":546639,"visible":true,"origin":"","legend":"\u003cp\u003eLRO-WAC mosaic showing the Schrödinger Basin with respect to its location near the Lunar South Pole (left) and the superposition of LOLA-DEM over the LRO-WAC subset showing the volcanic vent, Schrödinger G (yellow circle), that has been investigated in this study (right).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/30afdae4264e1482486e3c82.png"},{"id":84197669,"identity":"846c8e8f-aae9-4bba-9e21-19f5b591de28","added_by":"auto","created_at":"2025-06-09 08:01:12","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":239982,"visible":true,"origin":"","legend":"\u003cp\u003eA 3-D rendering of the volcanic vent created using LRO-NAC DTM. Unit of elevation is in meters.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/643958609ef27819e885746d.png"},{"id":84197675,"identity":"83ddb0ad-3926-471b-91c4-44dc33ca66d4","added_by":"auto","created_at":"2025-06-09 08:01:12","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":448886,"visible":true,"origin":"","legend":"\u003cp\u003eIIRS-derived temperature image of a part of the mafic deposit around the volcanic vent inside the Schrödinger Basin, corresponding to the overlapping portion of the data acquired at 08:27 hours (a) and at 10:25 hours (b). The temperature difference of (a) and (b) is shown in (c). The two boxes shown in (c) refer to the Subsets 1 and 2 which have been used for determining the representative average temperature differences around the vent. The background image is from LRO-WAC.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/6355a569c67cebd2c4449435.png"},{"id":84197663,"identity":"2715e8c5-d3fc-4ebd-9596-b9214dba3930","added_by":"auto","created_at":"2025-06-09 08:01:12","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":875094,"visible":true,"origin":"","legend":"\u003cp\u003eA temperature image mosaic generated from IIRS strips (CH2_IIR_NCI_20221226T1010382905 and CH2_IIR_NCI_20221226T0812414905) show the extent of the two distinct units around the vent outlined on the basis of temperature variations.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/e8eee5dc693a4cce7446f41a.png"},{"id":84197677,"identity":"11721d16-1777-41f3-8f74-a44b72a40da5","added_by":"auto","created_at":"2025-06-09 08:01:12","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":582285,"visible":true,"origin":"","legend":"\u003cp\u003eA\u003cstrong\u003e \u003c/strong\u003ecolour-ratio map generated using multispectral images from Clementine UVVIS data for the area surrounding the vent at Schrödinger G. A clear distinction between the two units is visible, indicating compositional variation between them.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/b5cef5202d55d4555de85a2b.png"},{"id":84199565,"identity":"9e6052cc-ec3d-47d7-8023-bd058db3bec0","added_by":"auto","created_at":"2025-06-09 08:17:12","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":190994,"visible":true,"origin":"","legend":"\u003cp\u003eFits from CSFD indicate multiple volcanic episodes around the vent at Schrödinger G. Resurfacing events at 1.8 ± 0.2 Ga and 2.5 ± 0.4 Ga have also been found in Units 1 and 2, respectively.\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/f3076ed290c24c1a211dd7eb.png"},{"id":84197672,"identity":"d506a97b-3c23-4644-a7a8-be4fc31f4a23","added_by":"auto","created_at":"2025-06-09 08:01:12","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":480132,"visible":true,"origin":"","legend":"\u003cp\u003eA\u003cstrong\u003e \u003c/strong\u003eslope map generated using LRO-LOLA elevation data for the area surrounding the pyroclastic vent at Schrödinger G.\u003c/p\u003e","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/c8afccc171a4c06f274fb07c.png"},{"id":84201674,"identity":"d34cf46b-60a1-4a6b-ab95-d0c3b8487481","added_by":"auto","created_at":"2025-06-09 08:33:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6505849,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/cfcf6161-af5b-4ee2-a798-c2738124503f.pdf"},{"id":84197667,"identity":"9cea2d6a-2569-41e9-ba84-3df9b19208aa","added_by":"auto","created_at":"2025-06-09 08:01:12","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8510276,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary information for the manuscript\u003c/p\u003e","description":"","filename":"SupportingInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-6816265/v1/c025fd6e72971ba25c324180.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eDaytime surface temperatures of the Moon derived from high-resolution IIRS on-board Chandrayaan-2\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSatellite-based observations of the lunar thermal environment began with Clementine, followed with Diviner Lunar Radiometer Experiment (DLRE) on-board the Lunar Reconnaissance Orbiter (LRO) mission. The Diviner instrument measures the lunar surface irradiance using a nine-channel radiometer that operates between a wavelength range from the visible to near-infrared (0.3 \u0026micro;m, VNIR) up to the far infrared (400 \u0026micro;m, FIR) (\u003cb\u003ePaige et al., 2010\u003c/b\u003e). Diviner was followed by two separate four-channel microwave radiometers (MRM) on-board Chang\u0026rsquo;E-1 (Fa and Jin, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and Chang\u0026rsquo;E-2 missions (Gong and Jin, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The spatial resolution of the Chang\u0026rsquo;E-1 MRM sensor is ~\u0026thinsp;35 to 50 km/pixel, from 200 km above the lunar surface \u003cb\u003e(Zheng et al., 2012)\u003c/b\u003e, while the brightness temperature (T\u003csub\u003eB\u003c/sub\u003e) maps produced from CE-1 and CE-2 are binned at a spatial resolution of ~\u0026thinsp;15 km/pixel and ~\u0026thinsp;6 km/pixel, respectively \u003cb\u003e(Zheng et al., 2019)\u003c/b\u003e. On the other hand, Diviner senses the surface irradiance at a spatial resolution of ~\u0026thinsp;240 to ~\u0026thinsp;320 m/pixel at the equator. Diviner is successful in mapping the global daytime and nighttime surface temperatures of the Moon after its injection into the lunar orbit in 2009 (Williams et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Indian Space Research Organization (ISRO) launched its second mission to the Moon on 22 July 2019, which carried one of the most advanced imaging spectrometers, Imaging Infra-Red Spectrometer (IIRS), along with seven other instruments. IIRS is the first lunar spectrometer that can operate in the extended wavelength range of ~\u0026thinsp;0.7 \u0026micro;m to ~\u0026thinsp;5 \u0026micro;m. In addition, the spatial resolution of IIRS is 80 m/pixel, which is attained from a nearly constant altitude of ~\u0026thinsp;100 km on a polar circular orbit. Prior to IIRS, the Moon Mineralogy Mapper (M\u003csup\u003e3\u003c/sup\u003e) sensor, sent on-board Chandrayaan-1, operated in the range of 430 to 3,000 nm. M\u003csup\u003e3\u003c/sup\u003e was designed to capture hyperspectral images at a resolution of ~\u0026thinsp;140\u0026ndash;280 m/pixel from 100\u0026ndash;200 km above the lunar surface. However, in the case of IIRS, in addition to being useful to properly capture the 3-\u0026micro;m OH/H\u003csub\u003e2\u003c/sub\u003eO feature (extending from ~\u0026thinsp;2.8 to ~\u0026thinsp;3.5 \u0026micro;m), the enhanced spectral coverage also provides an opportunity to investigate the thermally affected component of the electromagnetic spectrum, which ideally begins after ~\u0026thinsp;2.5 \u0026micro;m and becomes significant beyond ~\u0026thinsp;3 \u0026micro;m. Verma et al., (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) have removed the thermal component from IIRS data (between 2 to 3.5 \u0026micro;m, the \u0026ldquo;shorter wavelength\u0026rdquo;) by estimating the thermal emissions in the range of 4 to 5 \u0026micro;m. Moreover, the wavelength range between 3.5 to 5 \u0026micro;m (the \u0026ldquo;longer wavelength\u0026rdquo;) may also be used to study the thermophysical properties of the lunar surface. Additionally, Ojha et al., (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) have estimated surface temperatures from a part of a single IIRS strip and compared them with Diviner.\u003c/p\u003e \u003cp\u003eThe motivation to conduct this study stems from the fact that, to date, the global surface temperatures of the Moon are available only at a highest spatial resolution of ~\u0026thinsp;240 to ~\u0026thinsp;320 m/pixel from the Diviner instrument onboard LRO. Now, we have IIRS data available at a higher spatial resolution of ~\u0026thinsp;80 m/pixel. Hence, we aimed to test whether IIRS data, which has thermal bands between 4.5 to 5 microns, could be used to derive reliable surface temperature estimates for the Moon. For this purpose, we have used multiple IIRS images, data derived from a thermal model \u003cb\u003e(\u003c/b\u003eHayne et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and corresponding Diviner data spanning different latitudes, times of acquisition, and terrain types to obtain a robust and reliable correlation between the temperature values. Further, in this study, we seek to demonstrate the application of IIRS-derived surface temperatures in resolving a candidate problem related to lunar geology.\u003c/p\u003e"},{"header":"2. Study areas","content":"\u003cp\u003eEighteen IIRS images, acquired between ~\u0026thinsp;08:00 and ~\u0026thinsp;16:30 hours local time, have been analysed in this work, with the image extents stretching between the latitudes of ~\u0026thinsp;67\u0026deg; N up to ~\u0026thinsp;73\u0026deg; S, thereby covering a wide range of latitudes across the lunar surface (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Table S1). A few of these images largely represent the lunar maria (Oceanus Procellarum, Mare Serenitatis, Mare Tranquillitatis, Mare Fecunditatis, Mare Crisium, as well as parts of Mare Moscoviense). One of the 16 images stretches from ~\u0026thinsp;44\u0026deg; N to ~\u0026thinsp;44\u0026deg; S and includes an area that passes through highlands to the north of Mare Crisium, as well as the highlands to the south of Mare Fecunditatis. The particularly large extent of the image allows us to study temperature variations across a wide range of latitudes as well as different types of surfaces. The justification behind selecting these images is to showcase the variation of surface temperatures as a function of terrain types, latitudes, and times of data acquisition. Results derived and discussions pertaining to these images have been presented in Section \u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3. Data and methods","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Chandrayaan-2 IIRS data and thermal model\u003c/h2\u003e \u003cp\u003eCalibrated IIRS Level-1 (CODMAC Level 3, NASA PDS L1B) radiance data have been used in this study (Table S1). Each IIRS pixel is radiometrically corrected, band-separated, dark corrected, and provides band-to-band registered surface radiance (SI unit: W/(m\u003csup\u003e2\u003c/sup\u003e Sr \u0026micro;m)). Additionally, each of the IIRS images were manually seleno-referenced to their actual Ground Control Points by performing a rigorous image-to-image seleno-referencing with LRO-WAC as the reference image. Individual seleno-referenced IIRS products were then re-verified using a global LRO-WAC mosaic. The IIRS images selected in this study were captured at different local times of a lunar day. This was done to check the various temperature trends across different lunar local times. These sixteen images cover different latitude zones on the lunar surface (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), thereby exhibiting the influence of latitude on surface temperatures. In addition, we have used two more images from a polar region to demonstrate the scientific application of the IIRS-derived temperatures. The radiance pixels from all the images were converted to surface temperatures by inverting the Planck blackbody function (Eqs.\u0026nbsp;1 \u0026amp; 2) and by assuming a constant emissivity value of 0.95 for all the images.\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:{B}_{\\lambda\\:}\\left(T\\right)=\\frac{{2hc}^{2}}{{\\lambda\\:}^{5}}\\frac{1}{{e}^{\\frac{hc}{\\lambda\\:kT}}-1}\\)\u003c/span\u003e \u003c/span\u003e \u003cb\u003e(1)\u003c/b\u003e,\u003c/p\u003e \u003cp\u003ewhere, \u003cem\u003eh\u003c/em\u003e is the Planck\u0026rsquo;s constant, \u003cem\u003ec\u003c/em\u003e is the speed of light, \u003cem\u003ek\u003c/em\u003e is the Boltzmann constant and \u003cem\u003eT\u003c/em\u003e is temperature.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:T=\\frac{hc}{\\lambda\\:kln\\left(\\epsilon\\:\\pi\\:\\frac{{2hc}^{2}}{{I\\lambda\\:}^{5}}+1\\right)}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:I=\\epsilon\\:\\pi\\:\\frac{{2hc}^{2}}{{\\lambda\\:}^{5}}\\frac{1}{{e}^{\\frac{hc}{\\lambda\\:kT}}-1}\\)\u003c/span\u003e \u003c/span\u003e \u003cb\u003e(2)\u003c/b\u003e,\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:I\\simeq\\:\\epsilon\\:\\pi\\:{B}_{\\lambda\\:}\\left(T\\right)\\forall\\:\\lambda\\:\u0026gt;4.5\\mu\\:m\\)\u003c/span\u003e \u003c/span\u003e; ε and T are constant for a given pixel.\u003c/p\u003e \u003cp\u003eFurther, these derived surface temperatures from the IIRS data were compared with the temperature values derived from a standard lunar thermal model (Hayne et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). For the sake of completeness, we have provided the comparisons with Diviner data in the supplementary material (Sections S2 and S3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Clementine UVVIS and LRO-NAC data\u003c/h2\u003e \u003cp\u003eWe have used 5-band Clementine UVVIS (200 m/pixel) and high-resolution LRO-NAC (0.5 m/pixel) data to validate the results from the IIRS-derived surface temperatures to decipher possible mineralogical variations and estimate the age of the selected site, i.e., a pyroclastic deposit on the floor of the Schr\u0026ouml;dinger Basin. A colour-ratio map was then generated from the UVVIS reflectance data (with band centres at 415, 750, 900, 950, and 1,000 nm), which was prepared using the following colour-combination \u0026ndash; red: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{750}{415}\\right)\\)\u003c/span\u003e\u003c/span\u003enm, green: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{750}{950}\\right)\\)\u003c/span\u003e\u003c/span\u003enm, and blue: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{415}{750}\\right)\\)\u003c/span\u003e\u003c/span\u003e, as described in McEwen et al., (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). The LRO-NAC images were used to obtain age estimates based on crater chronology \u003cb\u003e(\u003c/b\u003eMichael and Neukum, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e of the vent in order to determine the period of major emplacements and resurfacings. Accordingly, crater size-frequency distribution (CSFD) measurements have been used to reveal the age of the vent. Sufficient care was taken to avoid the count areas with significant slopes (\u0026lt;\u0026thinsp;7\u0026deg;), which further act in minimizing the chances of errors in the estimation of surface ages. A cumulative resurfacing correction has been applied to account for the errors induced due to erosion mantling of smaller craters and other resurfacing processes \u003cb\u003e(\u003c/b\u003eMichael and Neukum, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results and discussion","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Analysis of surface temperatures derived from IIRS and the thermal model\u003c/h2\u003e \u003cp\u003eOur analysis of the IIRS dataset (images obtained between the lunar local times of ~\u0026thinsp;08:00 and ~\u0026thinsp;16:30 hours) reveals that the mean temperature differences (obtained by subtracting the IIRS temperature means from the corresponding model-derived temperature means for each image) are the highest towards the early morning (prior to ~\u0026thinsp;09:30 hours) as well as later in the day (after ~\u0026thinsp;14:00 hours) on the Moon (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Based on this analysis, we were able to identify a block of time during which the mean differences between IIRS and model-derived temperature data were comparatively less. The mean difference varied between 0.69 K \u0026ndash; 23.9 K between ~\u0026thinsp;09:30 and ~\u0026thinsp;14:00 hours on the lunar surface. Therefore, the local lunar times of ~\u0026thinsp;09:30 to ~\u0026thinsp;14:00 hours represent the optimum time range during which the temperatures estimated from IIRS would be the most reliable and comparable to the corresponding model-derived temperature data. During these local timings, the Sun remains at a sufficient angle above the lunar surface (\u0026lt;\u0026thinsp;40\u003csup\u003eο\u003c/sup\u003e) (Williams et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), which allows IIRS to accumulate sufficient thermally emitted signal in the spectral range of 4.5 to 5 \u0026micro;m. Beyond these times, a large deviation between IIRS and model-derived temperatures is recorded, due to non-optimum solar illuminationconditions. Similar discrepancies are observed when we compared the IIRS-derived temperatures with the temperatures derived from Diviner (Fig. S1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo analyse the differences between the model-derived and observed temperatures, we used 9 IIRS images such that they were acquired within our proposed time frame. The temperatures estimated from IIRS were compared with the model using two different criteria \u0026ndash; (i) at every 10\u0026deg; latitude we compared IIRS-derived mean temperature against the model-derived temperature across an entire lunar day, and (ii) at a fixed local time (IIRS image acquisition time) and over latitude bins of 1\u0026deg; (\u0026plusmn;\u0026thinsp;0.5\u0026deg;), we plotted IIRS data pixels from within that bin. From the population of pixels of an entire IIRS image, we have selected a small sample of pixels (~\u0026thinsp;80,000 to ~\u0026thinsp;100,000) within a\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg; latitudinal range around each specific latitude and then calculated the mean for that range. For every corresponding latitudinal bin of IIRS, temperatures were also estimated from the thermal model at every 0.5\u0026deg; latitude, which have been plotted over the IIRS temperature pixels (Figs. S1 to S4). To better describe the goodness of fit between the temperatures obtained from IIRS and the thermal model, pixels sampled from IIRS images along with their mean (dashed red line) were plotted across the different latitudes and were overlaid by the values retrieved from the thermal model at latitudinal intervals of 0.5\u0026deg; (solid yellow line). The estimated temperatures fell within the 2σ bounds as shown in Fig. S1 (d-f), Fig. S2 (f-j), Fig. S3 (c-d), and Fig. S4 (n-z) by the light red band, which ensured the statistical significance of this data. This comparison allowed us to analyse the temperature variations observed in real time from IIRS caused by differences in latitude, lunar local time, topography, and solar incidence angle at a higher spatial resolution.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTable showing mean temperature values obtained from the modeled data as well as the observed IIRS data and their absolute differences in K, with respect to different local times and latitudes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImage IDs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLocal acquisition time\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLatitudes (\u0026plusmn;\u0026thinsp;0.5\u0026deg; bins)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIIRS mean temperature (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel mean temperature (K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAbsolute difference\u003c/p\u003e \u003cp\u003e[IIRS-Model] (K)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCH2_IIR_NCI_20210706T0928053245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e09:28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e358.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e354.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e361.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e359.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e363.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e360.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCH2_IIR_NCI_20231119T1021387279\u003c/p\u003e \u003cp\u003eCH2_IIR_NCI_20211130T1106576194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e10:21 to 11:06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e344.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e352.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e352.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e366.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e351.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e375.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e358.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e380.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e21.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e358.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e381.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCH2_IIR_NCI_20211231T1149584496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e11:49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e345.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e359.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e358.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e373.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"12\" rowspan=\"13\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"12\" rowspan=\"13\"\u003e \u003cp\u003eCH2_IIR_NCI_20210610T1302166936\u003c/p\u003e \u003cp\u003eCH2_IIR_NCI_20191206T1305147603\u003c/p\u003e \u003cp\u003eCH2_IIR_NCI_20191210T1310531966\u003c/p\u003e \u003cp\u003eCH2_IIR_NCI_20240122T1333597453\u003c/p\u003e \u003cp\u003eCH2_IIR_NCI_20210126T1349194455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"12\" rowspan=\"13\"\u003e \u003cp\u003e13:02 to 13:49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e311.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e303.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e324.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e331.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e342.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e351.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e356.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e365.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e367.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e374.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e379.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e379.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e380.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e381.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e370.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e379.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e362.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e374.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e12.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e353.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e365.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e12.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e337.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e352.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e327.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e332.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e301.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e305.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, four separate groups (Groups 1 to 4) were created, which consists of the nine IIRS images that were acquired at a specific local time (between ~\u0026thinsp;09:30 to ~\u0026thinsp;14:00 hours). These groups have been created on the basis of local time such that images acquired within a period of one hour could be compared with each other as well as with the model. By analysing the data from all the four groups, we found the temperature differences between the model and the observed dataset to be in line with the expected trends for the lunar surface. However, at a few latitudes (in Group 2, between 0\u0026deg; to 20\u0026deg; and Group 4, between \u0026minus;\u0026thinsp;10\u0026deg; and \u0026minus;\u0026thinsp;30\u0026deg;), some anomalous differences have been noted that can be identified from the figures (Figs. S2 and S4). In these cases, the mean of the modeled temperature exceeds the 2σ range of the sampled pixels, which could be attributed to local topography, solar incidence angles, regolith properties, unusual albedo/emissivity properties of the crater walls/floors, and anisotropic thermal emissions from rough, sunlit surfaces \u003cb\u003e(Paige et al., 2010)\u003c/b\u003e. We have also shown for each group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (a-d)) the temperature range (maximum and minimum) obtained from each IIRS data as per the data shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (in blue), 2σ bound (in green), \u0026lsquo;X\u0026rsquo; (in red) signifying the model-derived temperature, with the actual latitude range created according to 1\u0026deg; bin (in yellow) for every 10\u0026deg; latitude as per each IIRS image extent. The absolute differences obtained between the thermal model and IIRS data between the latitudes of \u0026plusmn;\u0026thinsp;60\u0026deg; (Group-4) have been shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Application of the IIRS-derived surface temperatures: A case-study from the Schr\u0026ouml;dinger Basin\u003c/h2\u003e \u003cp\u003eTo describe the utility of the surface temperatures derived from IIRS, we performed a case-study on a volcanic deposit that is located around a vent on the floor of the ~\u0026thinsp;326-km-wide Schr\u0026ouml;dinger Basin. The importance of such a study on the floor of the Schr\u0026ouml;dinger Basin can be underscored by the following reasons \u0026ndash; it is the best-preserved impact basin of its size on the Moon \u003cb\u003e(\u003c/b\u003eKramer et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Wilhelms et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1987\u003c/span\u003e); the location of Schr\u0026ouml;dinger at the eastern edge of the oldest and the largest impact basin on the Moon - the South Pole-Aitken (SPA) Basin, provides an exciting opportunity to study the possibility of the presence of ejecta from SPA being found in and around Schr\u0026ouml;dinger itself and, the fact that a vent located on the floor of the basin could have acted as a large source of volatiles as well as harbour a large pyroclastic deposit, thus highlighting the immense potential of Schr\u0026ouml;dinger Basin being an interesting location for a near-future human exploration base. An investigation that focuses on the thermal aspects of the floor of the basin would likely add impetus to the ongoing studies of the scientifically important Schr\u0026ouml;dinger Basin and the nearby Permanently Shadowed Regions (PSRs) located near the Lunar South Pole.\u003c/p\u003e \u003cp\u003eWe investigated the surface temperatures obtained from around a vent (75.33\u0026deg; S, 139.22\u0026deg; E) inside the ~\u0026thinsp;326-km-diameter Schr\u0026ouml;dinger Basin (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Surrounding the vent is a large mafic deposit encompassing an area of ~\u0026thinsp;795 km\u003csup\u003e2\u003c/sup\u003e, which is the focus of our study. A longitudinal fracture passing through the centre of the vent appears to dissect the vent into two symmetric parts. A 3-D rendering created using LRO-NAC DTM (5 m/pixel) shows the elevated nature of the vent (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn this case-study, we have used two IIRS images that overlap each other near the vent, allowing us to investigate the thermal characteristics of the surface around the vent. These two IIRS images were acquired at 08:27 and 10:25 hours local time from a polar region. We selected the image obtained at 08:27 hours despite it lying beyond the recommended timeframe as well as latitude range (Section \u003cspan refid=\"Sec7\" class=\"InternalRef\"\u003e4.1\u003c/span\u003e) because we wanted to study the relative temperature difference between the two images. Also, the Schr\u0026ouml;dinger Basin is one of the limited regions where a sufficient overlap among two IIRS images was available. In order to investigate possible temperature variations, the overlapping part between the two images were extracted and temperature differences were obtained (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (a-c)). A temperature asymmetry around the vent is quite evident in the overlapping part wherein the south-eastern part shows considerably lower temperatures as compared to the north-western part (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (a, b)), suggesting the possibility of the occurrence of two distinct units. Also, the temperature differences around the vent were found to be non-uniform (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (c)). A marked variation exists between the north-western and the south-eastern side. In order to quantify this variation, two subsets, Subset-1 and Subset-2, were created on either side of the vent (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (c)). Subset-1 showed an average temperature variation (i.e., the difference between the maximum and minimum temperatures) of ~\u0026thinsp;50 K, whereas the Subset-2 experienced an average temperature difference of ~\u0026thinsp;62 K, during approximately two hours of difference in data acquisition time. This further strengthens the proposition that there could be two distinct units around the vent. Subsequently, to delineate the entire extent of the volcanic deposit, we merged the two temperature images, assuming them to be acquired during similar time of a lunar day. This resulted in the generation of a temperature map of the study area, using which we were able to identify the boundaries of the two units (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The relatively warmer unit is named as Unit-1, while the other unit is named as Unit-2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The average surface temperature for Unit-1 is ~\u0026thinsp;305 K, whereas the average for Unit-2 is ~\u0026thinsp;277 K. Possible reasons for this could be due to variation in material composition, physical properties, and topography. Delineation of the effect of these parameters warrants a further investigation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe studied the mineralogical composition of the Units-1 and \u0026minus;\u0026thinsp;2 using Clementine UVVIS data. A colour-ratio map (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e) generated using the band-combinations of McEwen et al., (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) indicate a difference in the surface composition of the area around the vent. The Unit-1 predominantly shows red-orange tones which are suggestive of the presence of low-Ti mafic soils in the region. In contrast, the Unit-2 primarily shows a bluish tone, indicating the presence of higher-Ti mafic soils. In order to estimate the emplacement history of the region, crater counting has been carried out for the Units 1 and 2. The results reveal an age of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{3.6}_{-0.08}^{0.05}\\)\u003c/span\u003e\u003c/span\u003e Ga for the Unit-1 by fitting the curve for crater diameter (D) range 500 m\u0026thinsp;\u0026lt;\u0026thinsp;D\u0026thinsp;\u0026lt;\u0026thinsp;2000 m (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). Volcanic resurfacing has been observed in the Unit-1 at 1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 Ga by fitting the curve for crater diameter range 250 m\u0026thinsp;\u0026lt;\u0026thinsp;D\u0026thinsp;\u0026lt;\u0026thinsp;500 m. On the other hand, Unit-2 exhibits a crater chronology-derived age of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{3.7}_{-0.01}^{0.06}\\)\u003c/span\u003e\u003c/span\u003e Ga by fitting the curve for crater diameter range 500 m\u0026thinsp;\u0026lt;\u0026thinsp;D\u0026thinsp;\u0026lt;\u0026thinsp;1000 m. Similar to Unit-1, a volcanic resurfacing also occurred in Unit-2 at 2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 Ga, which was interpreted by fitting the curve for crater diameter range 250 m\u0026thinsp;\u0026lt;\u0026thinsp;D\u0026thinsp;\u0026lt;\u0026thinsp;500 m. Hence, three different episodes of volcanic activity have been observed around the vent. Although the statistical significance of the difference in ages between Units 1 and 2 is 1.56σ, the compositional study indicates that these are two distinct units with different mineralogy. Therefore, it is quite likely that they were emplaced during separate volcanic eruptions. The older ages for Unit-1 are consistent with the results from Kring et al., (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, the younger episodes at ~\u0026thinsp;1.8 Ga and ~\u0026thinsp;2.5 Ga in Units-1 \u0026amp; -2, respectively, have been reported herein for the first time. Thus, the units deciphered on the basis of IIRS-derived temperature maps exhibit different compositions and they were emplaced during timeframes. It is important to note that the ~\u0026thinsp;1.8 Ga resurfacing found in Unit-1 is the youngest reported volcanic activity in the Schr\u0026ouml;dinger Basin.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe physical properties of the regolith could also be playing a role in the temperature variation of the region. These physical properties can be influenced by the compositional differences and the age of the unit. It is also possible that the topography could affect the derived temperatures. However, the slope of the entire region around the vent is gradual (\u0026lt;\u0026thinsp;7\u0026deg;), indicating a lack of significant topography around it (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). Hence, the local topography does not seem to be playing a major role in this region, as evident in the temperature difference image in (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (c)). Therefore, the observed temperature differences could likely be due to the existence of two distinct types of surfaces on the opposite sides of the vent.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eA detailed analysis of the surface temperatures derived from IIRS radiance data has been carried out in this study. Sixteen IIRS images have been used to understand how surface temperatures vary across different latitudes, terrains, and local time. The IIRS images studied in this work showed the expected latitudinal variations - decreasing temperatures with increasing latitude amongst all the images. In order to compare and validate the results obtained from IIRS data, we have used the lunar thermal model implemented by Hayne et al., (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and at every 10\u0026deg; latitude we compared IIRS-derived mean temperature against the model-derived temperature across an entire lunar day as well as at a fixed local time (IIRS image acquisition time) and over latitude bins of 1\u0026deg; (\u0026plusmn;\u0026thinsp;0.5). In addition to the thermal model, we have also used Diviner data to test and validate the temperatures obtained from IIRS.\u003c/p\u003e \u003cp\u003eOur analyses of the IIRS-derived temperatures reveal the following information: (1) IIRS data captured between ~\u0026thinsp;09:30 and ~\u0026thinsp;14:00 hours local time can be reliably used to estimate lunar surface temperatures between the latitudes of \u0026plusmn;\u0026thinsp;60\u0026deg; across the lunar surface, and (2) the temperature differences obtained from IIRS, the thermal model and Diviner data point towards the expected trends across the lunar surface. We checked data from the three datasets over maria and highlands while keeping the latitudes and times of acquisition as constant and found that the mean differences tend to vary more across the highlands as compared to the mare. When we fixed the surface types as well as the time of data acquisition and varied the latitudes, we found the differences to increase as a function of latitude. Additionally, it was found that the temperatures retrieved from the thermal model fit the IIRS-derived temperatures across different latitudes as well as local time. Absolute errors calculated between the model and IIRS varied between ~\u0026thinsp;0.7 K and ~\u0026thinsp;24 K.\u003c/p\u003e \u003cp\u003eFurther, using two more IIRS images, we conducted a case study on the floor of the Schr\u0026ouml;dinger Basin which includes a volcanic vent, known as Schr\u0026ouml;dinger G. Based on our analysis, we were able to identify two distinctly different units within the same deposit. In order to validate the finding, we have used multispectral Clementine-UVVIS data to generate a colour-ratio map (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Further, we found that these two units experienced late-stage volcanic activity. Unit-1 experienced volcanic resurfacing at ~\u0026thinsp;1.8 Ga, whereas the Unit-2 had volcanic resurfacing at ~\u0026thinsp;2.5 Ga (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). Hence, IIRS data was instrumental in bringing out the differences in the volcanic units, using which we were able to discern the geological diversity of the region.\u003c/p\u003e \u003cp\u003eThus, in a nut-shell, the results obtained in this study bring out the potential of using IIRS data for estimating the day time surface temperatures across the lunar surface at a high spatial resolution and highlight its usefulness in deciphering the geological diversity. Also, for the first time, a comparison between a thermal model and IIRS data has been shown in this study, which strengthens the reliability and robustness of the IIRS data within the suggested time frame. We propose that the surface temperatures measured by IIRS could be used to further understand the lunar thermal environment at a high spatial resolution.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Department of Space, Government of India, for providing financial support for this work. We acknowledge the use of data from Chandrayaan-2, the second lunar mission of the Indian Space Research Organization (ISRO), archived at the Indian Space Science Data Centre (ISSDC), publicly available at ISSDC \u003cem\u003ePradan\u003c/em\u003e (https://pradan.issdc.gov.in/ch2/). We also gratefully acknowledge the LRO-Diviner science team, the LRO-WAC, and LRO-NAC teams for providing publicly accessible data. Annu Kumari is gratefully acknowledged for help in seleno-referencing the IIRS dataset. We are thankful to Prof. Anil Bhardwaj, Director, PRL, and Prof. Varun Sheel, Chairman, PSDN, for their constant support to carry out this work. Shri A. S. Kiran Kumar, Chairman, PRL Council of Management, is gratefully acknowledged for providing useful suggestions that led to substantial improvement of the work. We would like to express our sincere gratitude to the two anonymous reviewers for providing insightful comments and suggestions.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFa, W., Jin, Y.-Q., 2010. A primary analysis of microwave brightness temperature of lunar surface from Chang-E 1 multi-channel radiometer observation and inversion of regolith layer thickness. Icarus 207, 605\u0026ndash;615. https://doi.org/10.1016/j.icarus.2009.11.034\u003c/li\u003e\n\u003cli\u003eGong, X., Jin, Y.-Q., 2012. Diurnal physical temperature at Sinus Iridum area retrieved from observations of Chinese Chang\u0026rsquo;E-1 microwave radiometer. 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U.S. Geological Survey, Washington D.C.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Physical Research Laboratory","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Moon, Moon, surface, Schrödinger Basin, Infrared observations, Instrumentation","lastPublishedDoi":"10.21203/rs.3.rs-6816265/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6816265/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Imaging Infra-Red Spectrometer (IIRS) on-board Chandrayaan-2 has been mapping the lunar surface since 2019 with high spatial (80 m/pixel) and spectral resolutions (20\u0026ndash;25 nm). IIRS\u0026rsquo;s spectral range from 0.7 to 5 \u0026micro;m allows it to differentiate between the reflected as well as the thermal components. In this study, we have derived surface temperatures from sixteen IIRS strips, sourced from different parts of the lunar surface by inverting the Planck\u0026rsquo;s equation. Thereafter, for the first time, we have compared IIRS-derived temperatures with those retrieved from a lunar thermal model and Diviner. The results show that the temperature estimates from IIRS data are in good agreement with the thermal model and the Diviner data over a specific latitude range of \u0026plusmn;\u0026thinsp;60\u0026deg; and time window of 09:30\u0026thinsp;\u0026minus;\u0026thinsp;14:00 hours local lunar time. The minimum and maximum mean absolute differences obtained for the temperature estimates by IIRS and the thermal model are 0.69 K and 23.9 K, respectively, for our suggested time and latitudinal range. These results demonstrate the robustness and reliability of the high-resolution IIRS-derived surface temperatures. Further, using the temperatures obtained from IIRS data, we investigated a part of the floor of the Schr\u0026ouml;dinger Basin comprising of a volcanic vent and found compositional diversity pointing towards the most recent and previously undetected episode of magmatic activity in the region. The findings were validated using Clementine-UVVIS multispectral data and crater chronology studies using Lunar Reconnaissance Orbiter \u0026ndash; Narrow Angle Camera (LRO-NAC) data. This study, thus, highlights the importance of using high-resolution surface temperatures from IIRS to unravel such hitherto unknown aspects of lunar geology.\u003c/p\u003e","manuscriptTitle":"Daytime surface temperatures of the Moon derived from high-resolution IIRS on-board Chandrayaan-2","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-09 08:01:06","doi":"10.21203/rs.3.rs-6816265/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5e176e6a-ed7f-408f-93aa-61f40a26789d","owner":[],"postedDate":"June 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49539165,"name":"Planetary Science"},{"id":49539166,"name":"Planetary Geology"}],"tags":[],"updatedAt":"2025-06-09T08:01:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-09 08:01:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6816265","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6816265","identity":"rs-6816265","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}