E. Bratsolis

Surface albedo spectral properties of geologically interesting areas on Titan

We investigate the nature and possible formation processes of three areas on Titans surface which have been suggested as geologically interesting: Hotei Regio, Tui Regio, and Sotra Patera. We also reanalyze the spectral characteristics of the Huygens Landing Site. We apply a statistical Principal Component Analysis (PCA) and a radiative transfer (RT) method on the Visual and Infrared Mapping Spectrometer Datacubes in order to retrieve the surface albedo of distinct spectral units in the near infrared. We have been able to exploit only a subset of the currently available Hotei Regio data, which are, in general, not optimal in terms of geometry for an analysis with a plane-parallel RT code. Our inferred surface albedos present generally higher values from 1 to 2 µm and lower ones at 0.94 and in the 2.6–5 µm region. The Regions of Interest (RoIs) within Hotei Regio, Tui Regio, and Sotra Patera are always significantly brighter than the surrounding areas. The largest variations are found longward of 2 µm and mainly at 5 µm. This higher surface albedo with respect to the surrounding area and, in general, the fact that the spectral behavior is different for each of these areas, is probably indicative of diverse chemical compositions and origins. We compare the spectral albedos with some suggested surface candidates on Titan (such as H2O, CO2, and CH4 ices, as well as tholin) and discuss possible chemical composition variations as well as other interpretations.

The Spectral Nature of Titan's Major Geomorphological Units: Constraints on Surface Composition

We investigate Titans low- and mid-latitude surface using spectro-imaging near-infrared data from Cassini/VIMS. We use a radiative transfer code to first evaluate atmospheric contributions and then extract the haze and the surface albedo values of major geomorphological units identified in Cassini Synthetic Aperture Radar data, which exhibit quite similar spectral response to the VIMS data. We have identified three main categories of albedo values and spectral shapes, indicating significant differences in the composition among the various areas. We compare with linear mixtures of three components (water ice, tholin-like, and a dark material) at different grain sizes. Due to the limited spectral information available, we use a simplified model, with which we find that each albedo category of regions of interest can be approximately fitted with simulations composed essentially by one of the three surface candidates. Our fits of the data are overall successful, except in some cases at 0.94, 2.03, and 2.79 μm, indicative of the limitations of our simplistic compositional model and the need for additional components to reproduce Titans complex surface. Our results show a latitudinal dependence of Titans surface composition, with water ice being the major constituent at latitudes beyond 30°N and 30°S, while Titans equatorial region appears to be dominated partly by a tholin-like or by a very dark unknown material. The albedo differences and similarities among the various geomorphological units give insights on the geological processes affecting Titans surface and, by implication, its interior. We discuss our results in terms of origin and evolution theories.

Unsupervised segmentation of agricultural regions using TerraSAR-X images

The framework of this study is focused on automatic fast recognition of agricultural interest for TerraSAR-X images. The intended goal is to label regions in an image as fast as possible, into classes significant for a given application, like crop classification. First, a filtering technique is applied to obtain the restored image. Then, two different methods of unsupervised segmentation are used. The Otsus method which is based on the optimum threshold of histogram and the k-means method which is based on the Euclidean distance.

Segmentation of lakes from the local background on the surface of Titan using Cassini SAR images

Synthetic Aperture Radar (SAR) images of Titan, the largest satellite of Saturn, reveal quasi-circular to complex features which are interpreted to be liquid hydrocarbon lakes. One of the major problems hampering the derivation of meaningful texture information from SAR imagery is the speckle noise. It overlays real structures and causes gray value variations even in homogeneous parts of the image. A filtering technique is applied to obtain the restored SAR images. Our method is based on probabilistic methods and regards an image as a random element drawn from a prespecified set of possible images. The TSPR (Total Sum Preserving Regularization) filter used here is based on a membrane model Markov random field approximation with a Gaussian conditional probability density function optimized by a synchronous local iterative method. The despeckle filter can be used as intermediate stage for the extraction of meaningful regions that correspond to structural units in the scene or distinguish objects of interest like lakes.