Mare Serenitatis (28°N, 17.5°E) has undergone intricate volcanic events, leading to the deposition of basaltic lava flows from various stages in the basin. This study presents prospective geological insights into the mare basalts within Mare Serenitatis by using data from the Chang’E-2 Lunar Microwave Sounder (CELMS), thereby aiding in enhancing comprehension of magma dynamics, thermal evolution, and volcanic activities. The following are the results obtained from this study: 1) the potential geological information in Mare Serenitatis was analyzed using brightness temperature (TB), identifying potential connections between deep-seated units within the basin; 2) the distribution and causes of TB anomalies in Mare Serenitatis were investigated, revealing that daytime hot anomalies mainly occur at its southern rim, with TiO2 abundance (TA) being the primary influencing factor. The nighttime cold anomalies appear near several craters and extend with depth; and 3) an untypical TB anomaly was observed in the central region of Mare Serenitatis, exhibiting lower TB at daytime and higher TB at nighttime. This study suggests the presence of a material with a lower loss tangent on the surface of the central region of Mare Serenitatis and suggests that this material is related to Mg-rich rock.

Brightness temperature (TB) data from the Chinese Chang’E-2 (CE-2) microwave radiometer (MRM) are constrained by the limited quantity of the original dataset, which cannot express global TB distribution. In order to construct the lunar TB model with the TB data obtained by the MRM on board CE-2, we propose a novel spherical geometric B-spline (SGB-spline) model. The model fully integrates the observed TB data with the lunar geometric features and determines optimal fitting parameters through a subdivision-based optimization process. More specifically, the establishment of the lunar TB model begins by employing spherical area coordinates (SACs) for CE-2 TB data representation across all four frequency channels, followed by applying geometric B-splines to refine the TB distribution. At the same time, it preserves the geometric integrity of the Moon. We observed that the SGB-spline model constructs the more comprehensive TB models during both lunar daytime and nighttime in the 3D Euclidean space, providing a more detailed representation of the spherical spatial information and the effect of frequency channels. Experimental results demonstrated that the proposed SGB-spline model significantly outperforms representative interpolation approaches.

The Chang’e-2 (CE-2) microwave radiometer (MRM) brightness temperature (TB) observations have significantly enhanced our understanding of lunar subsurface thermal features. While existing TB mapping approaches rely heavily on interpolation methods, this study proposes an advanced framework that combines heat conduction with multilayer microwave radiative transfer to generate continuous TB distributions over 24 hours. The proposed approach incorporates key lunar thermophysical parameters to ensure physical consistency in TB simulations. A spatiotemporal integration and validation scheme was also proposed to enhance data quality. Systematic biases between observed and modeled TB values were then addressed through a calibration approach using sine functions. The simulated TBs align well with the CE-2 MRM observations at both 19.35 GHz and 37.0 GHz. The approach accurately captures global TB patterns while preserving local thermal signatures across diverse geologic units. Detailed analyses at CE landing sites further validate the model’s capability to capture fine-scale thermal variations. The improved spatiotemporal coverage and accuracy of these TB maps provide valuable insights into lunar thermal and geological processes.

Brightness temperature (TB) derived from micro- wave radiometers (MRMs) onboard China’s Chang’e (CE) satellites has provided significant insights into the Moon’s subsurface thermal conditions and evolution. However, conventional TB mapping techniques emphasize spatial correlations among observational data points while largely neglecting the influence of inherent lunar surface factors. In this study, we propose a novel TB estimation approach utilizing geographically neural network weighted regression (GNNWR) combined with multisource lunar remote sensing data to generate TB maps at a higher spatial resolution of$0.0625^{\circ } \times 0.0625^{\circ }$. This method integrates crucial lunar surface parameters in heat conduction and radiation transfer models in a new framework, thereby reducing the risk of overestimation associated with high-resolution targets in sparsely distributed samples. In addition, by replacing the traditional geographically weighted regression (GWR) kernel with a spatially weighted neural network (SWNN), the model effectively addresses spatial nonstationarity and heterogeneity present in TB data and microwave radiative transfer. Comparative analyses demonstrate that the GNNWR approach achieves superior performance, as evidenced by the highest$R^{2}$and the lowest mean absolute error (MAE), the mean absolute percentage error (MAPE), and the root mean square error (RMSE). Furthermore, the generated TB maps demonstrate strong alignment with observed spatial trends. These maps also reveal fine-scale thermal features typically obscured by conventional interpolation methods, enhancing their utility for microwave thermal emission analysis and geological studies.

Mare Marginis (13.3 °N, 86.1 °E) is situated on the lunar nearside with rich geological diversity. This letter analyzes the brightness temperature ($T_{B}$) features of Mare Marginis through the normalized brightness temperature ($\text{n}T_{B}$) performances and brightness temperature difference ($\text{d}T_{B}$) using data from the Chang’E-2 Lunar Microwave Sounder (CELMS), in combination with slope, rock abundance (RA), and (FeO + TiO2) abundance (FTA). The results are as follows. First, the$\text{n}T_{B}$of Mare Marginis is relatively high at both daytime and nighttime. The daytime$\text{n}T_{B}$shows consistency with FTA distribution. Second, the$\text{d}T_{B}$of Mare Marginis is basically consistent with the FTA distribution, the consistency decreases as the frequency increases. Third, the correlation analysis shows that slope and FTA are the main factors influencing$\text{n}T_{B}$. In addition, the high substrate temperature is identified as the primary factor responsible for nighttime$\text{n}T_{B}$anomalies of Mare Marginis, whereas the high RA accounts for the emergence of the cold spot phenomenon at Goddard A crater.

Mare Humorum is located on the nearside of the Moon, at 24.4S and 38.6W. This region has rich geological structures, which not only experienced early lunar volcanic activity but also obtained a mascon. The research on thermal behaviors in Mare Humorum can bring new insights into the multiring impact basins. In this study, Chang’e-2 lunar microwave sounder (CELMS) data were used to obtain brightness temperature (TB) maps. To highlight the characteristics of Mare Humorum, the normalized TB (nTB) was generated. By analyzing the daytime and nighttime nTB maps, we found that there are both hot regions and cold spots in Mare Humorum. Combining Clementine UVVIS data with LRO Diviner data, some intuitive figures were made to find the reasons for these thermal anomalies in the study area. The results showed that TiO2 abundance (TA) and rock abundance (RA) are the factors for TB anomalies in Mare Humorum.

With the continuous advancements in the Chinese lunar exploration program, the substantial brightness temperature (TB) data acquired by the Chang’e (CE) orbiter series have provided unprecedented opportunities for studying the geology of the Moon. In particular, the TB data obtained by the CE-2 mission have offered a new observational perspective for investigating the geological characteristics of the Moon. In this article, we propose a novel triangulated spherical technique for constructing a TB model of the Moon with CE-2 microwave radiometer (MRM) data. Specifically, we directly parameterize spherical TB data based on spherical area coordinates and use spherical Bézier surfaces to capture the TB distributions for daytime and nighttime across different frequency channels. This model is enabled by the theoretical characterization of spherical data, which allows us to construct geometric formulations that parameterize the entire TB data of the Moon. It incorporates an octahedral partitioning strategy and divides the lunar surface into eight regions, each undergoing iterative refinement to enhance precision through detailed analysis. Furthermore, the spherical Bézier surfaces effectively mitigate the complexity of structural components on TB estimations. Experimental results demonstrate that the proposed TB model of the Moon significantly outperforms existing approaches in characterizing the lunar TB distribution, providing important application in analyzing the geological features and thermal processes of the Moon.

Chang’E lunar microwave sounder (CELMS) data have great significance for studying the lunar surface’s thermophysical features and internal structure. In this study, an area centered at Glushko crater (8.4°N, 77.6°W), one of the typical Copernican craters on the Moon, is selected as the study area. Its microwave thermal emission features (MTE) were investigated with the CE-2 CELMS data. The main results are as follows. First, Glushko crater is revealed as a cold spot for the first time due to its special brightness temperature (TB) performance. Second, the correlation analysis shows that the high rock abundance plays the most important role in theTBperformance observed at Glushko crater. Moreover, other factors, such as the ilmenite and the surface topography, contribute to theTBdistribution to a certain degree, but they do not possess the decisive influence. Furthermore, the spatial difference of theTBof Glushko crater floor reveals that lunar rocks are probably less abundant in the southern and western parts of Glushko crater.