With the increasing precision of the GRAIL gravity field models and topography from LOLA, it is possible to investigate the substructure beneath crater Clavius. An admittance between gravity and topography data is com...With the increasing precision of the GRAIL gravity field models and topography from LOLA, it is possible to investigate the substructure beneath crater Clavius. An admittance between gravity and topography data is commonly used to estimate selenophysical parameters, including load ratio, crustal thickness and density, and elastic thickness. Not only a surface load, but also a subsurface load is considered in estimation. The algorithm of particle swarm optimization(PSO) with a swarm size of 400 is employed as well.Results indicate that the observed admittance is best-fitted by the modeled admittance based on a spherical shell model, which was proved to be unsatisfactory in the previous study. The best-fitted load ratio f is around-0.194. Such a small load ratio conforms to the direct proportion between the nearly uncompensated topography and its corresponding negative gravity anomaly. It also indicates that a surface load dominates all the loads. Constrained within 2σSTD, a small crustal thickness(～30 km) and a crustal density of ～2587 kg m-3are found, quite close to the results from previous GRAIL research. Considering the well constrained crustal thickness and density, the best-fitted elastic thickness(～7 km) is rational. This result is slightly smaller than the previous study(～12 km). Such difference can be attributed to the difference in crustal density used and the precision of gravity and topography data. Considering that the small difference between the modeled gravity anomaly and observations is quite small, a parameter inversed here could be an indicator of the subsurface structure beneath Clavius.展开更多
The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs ar...The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(<1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2> 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.展开更多
基金supported by a grants from the National Natural Science Foundation of China (Grant Nos. 41864001 and U1831132)Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University (Grant No. 17P03)+3 种基金Guizhou Normal University Doctoral Research Fundsupported by grants from the Hubei Province Foundation innovation group project (2015CFA011, 2018CFA087)Open Project of Lunar and Planetary Science Laboratory, Macao University of Science and Technology (FDCT 119/2017/A3)Open Fund of Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing (KF201813)
文摘With the increasing precision of the GRAIL gravity field models and topography from LOLA, it is possible to investigate the substructure beneath crater Clavius. An admittance between gravity and topography data is commonly used to estimate selenophysical parameters, including load ratio, crustal thickness and density, and elastic thickness. Not only a surface load, but also a subsurface load is considered in estimation. The algorithm of particle swarm optimization(PSO) with a swarm size of 400 is employed as well.Results indicate that the observed admittance is best-fitted by the modeled admittance based on a spherical shell model, which was proved to be unsatisfactory in the previous study. The best-fitted load ratio f is around-0.194. Such a small load ratio conforms to the direct proportion between the nearly uncompensated topography and its corresponding negative gravity anomaly. It also indicates that a surface load dominates all the loads. Constrained within 2σSTD, a small crustal thickness(～30 km) and a crustal density of ～2587 kg m-3are found, quite close to the results from previous GRAIL research. Considering the well constrained crustal thickness and density, the best-fitted elastic thickness(～7 km) is rational. This result is slightly smaller than the previous study(～12 km). Such difference can be attributed to the difference in crustal density used and the precision of gravity and topography data. Considering that the small difference between the modeled gravity anomaly and observations is quite small, a parameter inversed here could be an indicator of the subsurface structure beneath Clavius.
基金supported in part by the Key Research Program of the Chinese Academy of Sciences under Grant (XDPB11)in part by opening fund of State Key Laboratory of Lunar and Planetary Sciences (Macao University of Science and Technology) (Macao FDCT Grant No. 119/2017/A3)+1 种基金in part by the National Natural Science Foundation of China (Grant Nos. 41490633, 41371332 and 41802246)in part by the Science and Technology Development Fund of Macao (Grant 0012/2018/A1)
文摘The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(<1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2> 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.
