Probing the origin of the dark material on Iapetus

Among the icy satellites of Saturn, Iapetus shows a striking dichotomy between its leading and trailing hemispheres, the former being significantly darker than the latter. Thanks to the VIMS imaging spectrometer on-board Cassini, it is now possible to investigate the spectral features of the satellites in Saturn system within a wider spectral range and with an enhanced accuracy than with previously available data. In this work, we present an application of the G-mode method to the high resolution, visible and near infrared data of Phoebe, Iapetus and Hyperion collected by Cassini/VIMS, to search for compositional correlations. We also present the results of a dynamical study on the efficiency of Iapetus in capturing dust grains travelling inward in Saturn system to evaluate the viability of Poynting-Robertson drag as the physical mechanism transferring the dark material to the satellite. The results of spectroscopic classification are used jointly with the ones of the dynamical study to describe a plausible physical scenario for the origin of Iapetus' dichotomy. Our work shows that mass transfer from the outer Saturnian system is an efficient mechanism, particularly for the range of sizes hypothesised for the particles composing the newly discovered outer ring around Saturn. Both spectral and dynamical data indicate Phoebe as the main source of the dark material. However, we suggest a multi-source scenario where now extinct prograde satellites and the disruptive impacts that generated the putative collisional families played a significant role in supplying the original amount of dark material.Comment: 20 pages, 4 tables, 11 figures, major revision (manuscript extended and completed, figures added and corrected, new results added), minor revision and finalization of author list, moderate revision (update of the manuscript following reviewer's feedback and discovery of the new Saturnian outer ring

Correlations between VIMS and RADAR data over the surface of Titan: Implications for Titan's surface properties

We apply a multivariate statistical method to Titan data acquired by different instruments onboard the Cassini spacecraft. We have searched through Cassini/VIMS hyperspectral cubes, selecting those data with convenient viewing geometry and that overlap with Cassini/RADAR scatterometry footprints with a comparable spatial resolution. We look for correlations between the infrared and microwave ranges the two instruments cover. Where found, the normalized backscatter cross-section obtained from the scatterometer measurement, corrected for incidence angle, and the calibrated antenna temperature measured along with the scatterometry echoes, are combined with the infrared reflectances, with estimated errors, to produce an aggregate data set, that we process using a multivariate classification method to identify homogeneous taxonomic units in the multivariate space of the samples.In medium resolution data (from 20 to 100. km/pixel), sampling relatively large portions of the satellite's surface, we find regional geophysical units matching both the major dark and bright features seen in the optical mosaic. Given the VIMS cubes and RADAR scatterometer passes considered in this work, the largest homogeneous type is associated with the dark equatorial basins, showing similar characteristics as each other on the basis of all the considered parameters.On the other hand, the major bright features seen in these data generally do not show the same characteristics as each other. Xanadu, the largest continental feature, is as bright as the other equatorial bright features, while showing the highest backscattering coefficient of the entire satellite. Tsegihi is very bright at 5 μm but it shows a low backscattering coefficient, so it could have a low roughness on a regional scale and/or a different composition. Another well-defined region, located southwest of Xanadu beyond the Tui Regio, seems to be detached from the surrounding terrains, being bright at 2.69, 2.78 and 5 μm but having a low radar brightness. In this way, other units can be found that show correlations or anti-correlations between the scatterometric response and the spectrophotometric behavior, not evident from the optical remote sensing data. © 2010 Elsevier Inc

Multidimensional Classification Method in the Study of Natural and Anthropogenic Systems

 In this article the problem of build and use classification of multivariate observations; this issue has played a leading role in the knowledge of the world around us. When studying natural- anthropogenic systems have the greatest value probably-statistical simulation methods of objects, phenomena and processes. Among classification technologies to focus on situations of constructing classifications if there is no a priori information about the taxonomic structure of the observations. In the work described the rationale for the original statistical criterion Z2 and G-classification methods of multivariate observations. This used quantity conversion method dependent traits in an equivalent number of independent. G-method lets you select homogeneous classes and sub-classes of observations, evaluate differences between taxons, determine the informative signs and much more. The application of the classification shown in the case study method regularities of formation of chemical composition of mine waters in the Eastern Donbass. It is four main types of changes in the composition of mine waters: the first type has the most significant impact on environmental degradation in the region; the second and third types reflects the influence composition of groundwater chloride in the composition of mine water; the fourth type is the soda water, which may indicate the presence of the region's oil and gas fields

Development and use of Digital Technology when Studying of Environment

 The aim of the research is to show the possibilities of using digital classification technology in the study of patterns of formation of natural-anthropogenic systems. With the help of the original digital computer classification technology, AGAT-2 identified the types of chemical composition of mine waters in the Eastern Donbass and assessed their impact on the environment. All surveyed periods (20 years, 1966, 1992 and 2015) discovered four main types of composition of mine waters. The first type is the acidic sulphate water with high concentrations of metals Which causes the most heavy environmental pollution. The second type is formed by chloride-sulphate waters, the third by sulfatechloride to a lesser extent enriched with metals. The fourth type is formed by soda water, which may indicate the presence of oil fields in the region. An assessment of pollution of groundwater and surface water is given

The Methodological Aspect of Development and Application Multivariate Classification G-Mode for Analyses Geochemical Trend

This article is unique G-mode of multidimensional classification method and its application in the analysis of hydrogeochemistry Donetsk basin. He has the following main advantages over other methods of classification: does not require a priori information for classification of observations; earmarks homogeneous observing classes and subclasses; evaluates information weight of each indicator, determines the distance between the homogeneous taxon's; assessment of the descriptiveness of the sign of the classification and others. G-method is widely used to analyze geochemical, environmental, kosmochemical, distance and other types of information. The method successfully used in examining objects, phenomena and processes on Earth, Moon, Mars, Saturn, comets, asteroids and deep space. The results of the use of G-method in analysis of hydrogeological data for the Donetsk basin identified direct and inverse geochemical zonality. This shows that in the region can be discovered oil and gas accumulations

The Methodological Aspect of Development and Application Multivariate Classification G-Mode for Analyses Geochemical Trend

This article is unique G-mode of multidimensional classification method and its application in the analysis of hydrogeochemistry Donetsk basin. He has the following main advantages over other methods of classification: does not require a priori information for classification of observations; earmarks homogeneous observing classes and subclasses; evaluates information weight of each indicator, determines the distance between the homogeneous taxon's; assessment of the descriptiveness of the sign of the classification and others. G-method is widely used to analyze geochemical, environmental, kosmochemical, distance and other types of information. The method successfully used in examining objects, phenomena and processes on Earth, Moon, Mars, Saturn, comets, asteroids and deep space. The results of the use of G-method in analysis of hydrogeological data for the Donetsk basin identified direct and inverse geochemical zonality. This shows that in the region can be discovered oil and gas accumulations