The dielectric constant of the lunar regolith can directly influence the reflection coefficient and the trans-mission coefficient of the Moon′s surface, and plays an important role in the Moon research. In order to s...The dielectric constant of the lunar regolith can directly influence the reflection coefficient and the trans-mission coefficient of the Moon′s surface, and plays an important role in the Moon research. In order to study the di-electric properties of the lunar regolith, the lunar regolith simulant was made according to the making procedure of the CAS-1 simulant made by Chinese Academy of Sciences. Then the dielectric constants of the lunar regolith simulant were measured with 85070E Aiglent Microwave Network Analyzer in the frequency ranging from 0.2 GHz to 20.0 GHz and at temperature of 25.1℃, 17.7℃, 13.1℃, 11.5℃, 9.6℃, 8.0℃, 4.1℃, -0.3℃, -4.7℃, -9.5℃, -18.7℃, -27.7℃, and -32.6℃, respectively. The Odelevsky model was employed to remove the influence of water in the air on the final effective dielectric constants. The results indicate that frequency and temperature have apparent influences on the dielectric constants of the lunar regolith simulant. The real parts of the dielectric constants increase fast over the range of 0.2 GHz to 3.0 GHz, but decrease slowly over the range of 4.0 GHz to 20.0 GHz. The opposite phenomenon occurs in the imaginary parts. The influences of the frequency and temperature on the brightness temperature were also estimated based on the radiative transfer equation. The result shows that the variation of the frequency and temperature results in great changes of the microwave brightness temperature emitting from the lunar regolith.展开更多
Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information...Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information. In this paper, we present a new method for mineral extraction aimed at solving the difficulty of mineral identification in vegetation covered areas. The method selected six sets of spectral difference coupling between soil and plant(SVSCD). These sets have the same vegetation spectra reflectance and a maximum different reflectance of soil and mineral spectra from Hyperion image based on spectral reflectance characteristics of measured spectra. The central wavelengths of the six, selected band pairs were 2314 and 701 nm, 1699 and 721 nm, 1336 and 742 nm, 2203 and 681 nm, 2183 and 671 nm, and 2072 and 548 nm. Each data set's reflectance was used to calculate the difference value. After band difference calculation, vegetation information was suppressed and mineral abnormal information was enhanced compared to the scatter plot of original band. Six spectral difference couplings, after vegetation inhibition, were arranged in a new data set that requires two components that have the largest eigenvalue difference from principal component analysis(PCA). The spatial geometric structure features of PC1 and PC2 was used to identify altered minerals by spectral feature fitting(SFF). The collecting rocks from the 10 points that were selected in the concentration of mineral extraction were analyzed under a high-resolution microscope to identify metal minerals and nonmetallic minerals. Results indicated that the extracted minerals were well matched with the verified samples, especially with the sample 2, 4, 5 and 8. It demonstrated that the method can effectively detect altered minerals in vegetation covered area in Hyperion image.展开更多
基金Under the auspices of National Natural Science Foundation of China (No. 40901159, 40901187)Doctoral Fund of Ministry of Education of China (No. 20090061120055)+1 种基金the Fundamental Research Funds for the Central Universities (No. 200903047)National High Technology Research and Development Program of China (No. 2010AA122203)
文摘The dielectric constant of the lunar regolith can directly influence the reflection coefficient and the trans-mission coefficient of the Moon′s surface, and plays an important role in the Moon research. In order to study the di-electric properties of the lunar regolith, the lunar regolith simulant was made according to the making procedure of the CAS-1 simulant made by Chinese Academy of Sciences. Then the dielectric constants of the lunar regolith simulant were measured with 85070E Aiglent Microwave Network Analyzer in the frequency ranging from 0.2 GHz to 20.0 GHz and at temperature of 25.1℃, 17.7℃, 13.1℃, 11.5℃, 9.6℃, 8.0℃, 4.1℃, -0.3℃, -4.7℃, -9.5℃, -18.7℃, -27.7℃, and -32.6℃, respectively. The Odelevsky model was employed to remove the influence of water in the air on the final effective dielectric constants. The results indicate that frequency and temperature have apparent influences on the dielectric constants of the lunar regolith simulant. The real parts of the dielectric constants increase fast over the range of 0.2 GHz to 3.0 GHz, but decrease slowly over the range of 4.0 GHz to 20.0 GHz. The opposite phenomenon occurs in the imaginary parts. The influences of the frequency and temperature on the brightness temperature were also estimated based on the radiative transfer equation. The result shows that the variation of the frequency and temperature results in great changes of the microwave brightness temperature emitting from the lunar regolith.
基金Under the auspices of National Science and Technology Major Project of China(No.04-Y20A35-9001-15/17)the Program for JLU Science and Technology Innovative Research Team(No.JLUSTIRT,2017TD-26)the Changbai Mountain Scholars Program,Jilin Province,China
文摘Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information. In this paper, we present a new method for mineral extraction aimed at solving the difficulty of mineral identification in vegetation covered areas. The method selected six sets of spectral difference coupling between soil and plant(SVSCD). These sets have the same vegetation spectra reflectance and a maximum different reflectance of soil and mineral spectra from Hyperion image based on spectral reflectance characteristics of measured spectra. The central wavelengths of the six, selected band pairs were 2314 and 701 nm, 1699 and 721 nm, 1336 and 742 nm, 2203 and 681 nm, 2183 and 671 nm, and 2072 and 548 nm. Each data set's reflectance was used to calculate the difference value. After band difference calculation, vegetation information was suppressed and mineral abnormal information was enhanced compared to the scatter plot of original band. Six spectral difference couplings, after vegetation inhibition, were arranged in a new data set that requires two components that have the largest eigenvalue difference from principal component analysis(PCA). The spatial geometric structure features of PC1 and PC2 was used to identify altered minerals by spectral feature fitting(SFF). The collecting rocks from the 10 points that were selected in the concentration of mineral extraction were analyzed under a high-resolution microscope to identify metal minerals and nonmetallic minerals. Results indicated that the extracted minerals were well matched with the verified samples, especially with the sample 2, 4, 5 and 8. It demonstrated that the method can effectively detect altered minerals in vegetation covered area in Hyperion image.
