The distribution and types of the minerals and rocks on the lunar surface is the main topic of the lunar exploration and it is helpful to investigate the origin and evolution of the moon. Hyperspectral remote sensing is effective to the exploration to the lunar minerals and rocks because of its fine spectral information and its dominant role in mineral identification.At present, the imaging spectroscopy has been widely used on the earth and the Mars and the mineral identification based on the imaging spectroscopy is mature, while the importance of the imaging spectroscopy to the lunar exploration has been recognized recently. Several hyperspectral instruments has been carried on the lunar satellite such as M3, HySI, SIR-2 carried on “Changdrayaan-1” and the Sagnac Imaging Fourier Transform Spectrometer carried on “change-1”.A lot of hyperspectral remote sensing data has been aquired by the Sagnac Imaging Fourier Transform Spectrometer which was first used in the lunar exploration.While the lack of the quantitative analysis on the spectral characteristic of the lunar soil reduces the precision of the lunar soil detection and limits the population and application of these aquired data in some sense.Therefore, studying the basic issues and the difficulty of the lunar soil detection can improve the detection precision. The goal of this paper is to investigate the theories and main algorithms of the lunar surface quantitative detection.
The main contents and research results of this paper are as follows:
(1) Based on the corresponding background information, the spectra producing mechanism of lunar soils was studied. The visible- near infrared and thermal spectral characteristics of the lunar surface minerals was inducted and analyzed using the spectral data achieved by the lunar satellite, the spectral data measured in the simulated library environment, the data observed by the earth-based telescopes.
(2) The quantitative analysis was made on the factors which may affect the spectral characteristics, such as the physical and chemical components, mineral size, the lunar surface temperature and the outer space environment. Then, the model of these factors to the spectral characteristics was built.
(3) The physical and chemical methods were applied to simulate the lunar soil using minerals on the earth and the spectral of the simulated lunar soil was measured by ASD spectrometer and Nuance multispectral imaging system.At the same time, the spectra were simulated according to the Radiative Transfer Equation.At last, these two spectral simulation methods were compared.
(4) Based on the calibration results and lunar surface illumination charcteristics, the absolute reflectance retrieval method was put forward to and several relative reflectance retrieval methods were used to the lunar image data and the retrieval results were compared. The results indicated that the Flat Field method is the best method to the lunar image data .Then, according to the radioactive transfer procedure, the emissivity retrieval was explored.
(5) In this paper the lunar surface mineral mapping was performed based on the laboratory measurements of the lunar samples spectra, the Clementine image data, and the emission spectral data.
The results indicated that the support vector machine is best to the surface features classification for the lunar spectra.Of all of the spectral matching methods,Spectral Information Divergence can detect the minimal difference between the silimar spectra of different types and different chemical component.The relationship between the laboratory measurements of the spectra and mineral and chemical component and the Clementine relative image was built to perform the TiO2 and FeO content retrival and was successfully used to the 10S015 image.The retrival results based on the emission spectral data indicated that the position and depth of the Christensen features can be used to retirive the mineral and chemical component, while the stability of the built relationship should be studied further.At the same time, the parameters setting suggestions for the next hyperspectral machine were brought forward according to the experimental results.
(6) The difficulty and the characteristics of the lunar surface minerals were analyzed and the content which was important to the lunar surface minerals detection was suggested.
This paper makes great efforts on the building of the influencing factors model, the retrievaling algorithm of lunar emissivity and reflectance and the method of lunar mineral mapping.Some suggestions on the improvement of the lunar surface minerals detection was made based on the lunar surface features in order to promote the application of the hyperspectral remote sensing in the lunar surface matters detection.
Hyperspectral remote sensing was created by the geologist when they studied the spectral features of rocks and minerals and its application in geology is earliest and most successful. Even though, the technique still is not mature and perfect because its short in satisfying some need in modern geology application. The accurate recognition of rocks an minerals based on the diagnosis spectral features, the quantificationally extraction of geochemistry information and the extraction of small geological objects all need to deep the understanding of the mechanisms and principles of spectroscopy of rocks an minerals. The technology and method for the unique application should be developed for the improving of the geological remote sensing technology.
The art of geological study by hyperspectral remote sensing was introduced in the paper, especially the spectroscopy of rocks and minerals and its information extraction methods. Then the spectral mixing models were studied, the spectral features of altered mineral groups were analyzed and the information extraction methods were investigated. The rock and mineral information extraction method was set up for alteration recognition and several tests were practiced. At last, the target detection algorithms are studied for the recognition of alteration, the proper geological object detecting strategy was set up and was practiced for the alteration information extraction in vegetation covered area and no-vegetation area. The main content and result is introduced as follows:
(1) The spectral simulating model which integrating the Hapke model and Shkuratov mixing model was provided based on the study in the linear and nonlinear spectral mixing models. The spectral simulating result using the model provided in the paper was better than the traditional linear model and was tested by the experimentation. The approximation for single scattering albedo of opacity minerals in Hapke model was provided to get the spectral simulating method adapted to the spectral simulating of mineral mixtures which containing opacity minerals. The model is useful for the establishing of the bidirectional reflectance library of rocks and minerals and can be applied in the spectral simulating of the moon and other planets.
(2) The mixed spectral experiment was practiced which integrating the high spatial resolution camera, multispectral imaging system and ASD FieldSpec FR2500. This idea gived the supporting for the study of spectral mixing model and can be applied in the aero platform in large scale in further study. A spectral simulating model for remote sensing with low resolution was provided, it integrated the linear and nonlinear model and can used for the spectral simulating of mix-pixel such as the image spectra of alteration zone.
(3) Based on the analysis of mineral component and spectral features in typical alteration wall rock, object-oriented information extraction method was provided for the extraction of rocks, minerals and alteration, which contained three steps: the object spectra simulating, spectral feature analysis and spectral matching, weight function decision. This method was used for alteration zone in Cuprite area successfully. The method was also used for the execution of the geological spectral histogram in Baogutu area taking the spectral of alteration group as reference. The accurate recognition and mapping can be realized if the spectral resolution and signal to noise is enough high. The information extraction method which integrating of spectral matching and color component can greatly enhance the rock body and alteration in the image,despite the spectral and spatial resolution of ASTER data is low.
(4) Several target detecting algorithms with objects known and background unknown considering the characteristics of geological objects were studied, such as Orthogonal Subspace Projection(OSP), Constrained Energy Minimization(CEM), Adaptive Coherence/ Cosine Estimator(ACE), Adaptive Matched Filter(AMF),Elliptically Contoured Distributions(ECD). The principle of the detectors and the factors effecting detecting efficiency were analyzed and the improved strategy was provided. The integrated weight function correlation matrix (covariance matrix) was considered and the improved algorithms can detect the big object bedides the small object. Several target detecting algorithms were selected by the detecting test of small geological object with different background in vegetation covered area and no-vegetation area, the efficiency of ACE and AMF is best and CEM is better.
The atmospheric correction of remote sensing imagery for Case 2 waters is always the main problem to be solved for inland color remote sensing. Two difficulties exist therein: 1) the optical properties of the case 2 waters (especially inland waters) are more complicated and spatially unhomogeneous with more reginal charateritics than those of case 1 waters, which is hard to meet the hypothesis in the atmospheric correction algorithms for case 1 waters; 2) the aerosol optical properties are greatly influenced by human activities and surface factors above the inland case 2 waters. Moreover, the complicated aerosol optical properties and the relative large aerosol optical thickness (AOT) result in the assumptions of some atmospheric correction algorithms questionable. So, the aforementioned probems, especially the second problem was studied during the atmosphere correction of remote sensing imagery for Taihu, the typical case 2 waters.
Aerosol and water vapor are two main factors affecting the accuraccy of atmospheric correction of remote sensing imagery. The scattering and absorbing effects of the aerosol are more complicated. So, the retrieval algorithm of the AOT and water vapor column (WVC) were studied with the multi-band sunphotometer. The AOT retrieval accuracy was analyzed by the influence of spectral response functions. The absorption features were also analyzed outside the 940nm band for these gases such as H2O, O3, NO2 ,CO2, CH4 by Line-by-Line Radiative Transfer Model (LBLRTM) and the gases’ fine spectral cross-sections of SCanning Imaging Absorption sepctroMeter for Atmospheric CartographHY (SCIAMACHY). The calculation algorithms of the optical depths for these gases were improved. Also, the relationship among absorption transmittance, WVC and observation zenith angle in 940nm-band was studied by LBLRTM. As a result, a new algorithm was proprosed with high WVC retrieval accuracy, of which the relative retrieval error was no more than 0.04 even with large zenth angle (~63°). Accordingly, a new calibration method for water absorption band which is independent to the AOTs of the neighbor bands.
The above mentioned improved methods were applied to CE318’s in-situ data around Taihu from 2005 to 2007 to retrieve AOTs. Combining with the products of Aerosol Robotic NETwork (AERONET) of Taihu, the time-spatial distribtion of aerosol optical properties was analyzed and the seasonal aerosol types of Taihu were also modeled. These results were used to improve the accuarcy of atomospheric correction.
Based on these studies, it was analyzed the influences of atmospheric correction accuracy for case 2 waters by errors such as aerosol type error, AOT error and the error of geometric imaging parameters( solar zenith, view zenith, et al.). Then a general method was proposed to establish atmospheric correction look-up tables. And the atomopheric correction was accomplished for European Space Agency’s (ESA) Project for On Board Autonomy/Compact High Resolution Iamging Spectrometer (PROBA/CHRIS) and airborne Wide field-of-view Hyperspectral Imager (WHI), respectively by image itself and by in-situ atmospheric data. In order to compensate the polarized effects of gases’s scattering and aerosol’s scattering, the vector radiative tranfer model 6SV1 was used in the radiative tranfer calculation.
Aimed to image-based atmospheric correction algorithm, present algorthms of case 2 water atmospheric correction were summarized. The iterative and noniterative atmospheric correction algorithms were proposed for hyperspectral remote sensing imagery, which were the coupled ocean-atmosphere correction algorithms with look-up tables. These algorithms could retrive remote sensing reflectance (Rrs), aerosol type, AOT, water quality parameters (suspended matter concentration, chloroyphyII-a concentration and aborption coefficients of colored dissolved organic matter), et al. 6SV1 modle and the simple bio-optical modle were adopted for atmospheric and ocean radiative transfer process, respectively. After atmospheric correction for CHRIS data and compared the results with the in-situ measured Rrs of the quasi-synchronous stations, the satisfactory Rrs retrival accuarcy were abtained by both of the algorithms.
Take WHI data as a case study: the hypersepctral remote sensing imagery was accomplished for vicarious calibration based on the synchronous measured calibraion tars’ reflectance, water Rrs and atmosphere parameters. Also the valid spectra of WHI were evaluated for case 2 waters. Then the atmospheric correction for WHI was finished based on lookup table, which was estabilshed by measured atmosphere paramters. Besides, the fast geometric rectified algorithm based on POS data was proposed for refctifying the serious geometric distortion of airborne imagery, which was used to futher process the data after atmospheric correction.
The method for aerosol optical properties in this study can be applied to can extend to other regions. Also the principle of the coupled ocean-atmosphere correction algorithms fit to all the hyperspectral data with the spectra from visable to near infrared ranges; however, small modification may be made to these algorithms according to imagery band settings.
Monitoring inland water quality by remote sensing technology has the advantages of wide coverage, rapidness, low cost, and dynamic monitoring over a long period of time. However, inland waters always have complicated opticalcharacteristics, and different inland waters have different optical characteristics. Then it is difficult to build a high-accuracy and adaptable model to retrieve inland water quality parameters. Also, most models to retrieve water quality parameters neglect the bi-directional reflectance distribution of water optical field to lose accuracy. So it has great scientific and realistic significance to build retrieval model based on optical characteristics and bi-directional reflectance distribution function of water optical field.
The paper chose two typical inland waters as study area, including eutrophic water Taihu Lake and mesotrophic-dystrophic water Three Gorges reservoir. We performed 6 times experiments in Taihu Lake, collecting multi temporal inherent optical properties and apparent optical properties, WHI (Wide Hyperspectral Imager) airborne remote sensing images and CHRIS (Compact High Resolution Imaging Spectrometer) spaceborne remote sensing images. We also performed an experiment in Three Gorges reservoir, collecting inherent optical properties, apparent optical properties, and a scene of CHRIS image. Based on these data, the paper made a comparative analysis of the reason of different optical properties distribution between Taihu Lake and Three Gorges reservoir. Then, we built inherent optical properties database and apparent optical properties database in Taihu Lake and Three Gorges reservoir, as Hydrolight inputs. We simulated bi-directional reflectance of different waters and analyzed the law of bi-directional reflectance distribution function of water optical field which was also verified by our measured data. Furthermore, we built a look-up table of bi-directional factors of water optical field. Oriented to three kinds of water quality parameters concentrations of chlorophyll-a, suspended matter and CDOM (Colored dissolved organic matter), we developed retrieval analytic
model based on inherent optical properties database and bi-directional factor look-up table. At last, we used WHI and CHRIS images to retrieve water quality parameters to
validate the models we had done, and we got good results.
The research findings in this paper are also can be applied to other similar types of inland waters. This will accelerate application of remote sensing in monitoring
water quality in different lakes and rivers.