Candidate regions on titan as promising landing sites for future in situ missions

The highly successful and still on-going Cassini-Huygens mission to the Saturnian system points to the need for a return mission, with both remote and in situ instrumentation. The surface of Saturn’s moon Titan, hosts a complex environment in which many processes occur shaping its landscape. Several of its geological features resemble terrestrial ones, albeit constructed from different material and reflecting the interiorsurface-atmosphere exchanges. The resulting observed morphotectonic features and cryovolcanic candidate regions could benefit from further extensive exploration by a return mission that would focus on these aspects with adapted state-of-the-art instrumentation affording higher spectral and spatial resolution and in situ capabilities. We suggest that some features on Titan are more promising candidate locations for future landing and we present the case for Tui Regio, Hotei Regio and Sotra Patera as to why they could provide a wealth of new scientific results

Potentially active regions on Titan: New processing of Cassini/VIMS data

The Cassini Visual and Infrared Mapping Spectrometer (VIMS) obtained data of Titan's surface from flybys performed during the last seven years. In the 0.8-5.2 µm range, these spectro-imaging data showed that the surface consists of a multivariable geological terrain hosting complex geological processes. The data from the seven narrow methane spectral "windows" centered at 0.93, 1.08, 1.27, 1.59, 2.03, 2.8 and 5 µm provide some information on the lower atmospheric context and the surface parameters that we want to determine. Atmospheric scattering and absorption need to be clearly evaluated before we can extract the surface properties. We apply here a statistical method [1, 2] and a radiative transfer method [3, 1] on three potentially "active" regions on Titan, i.e. regions possibly subject to change over time (in brightness and/or in color etc) [4]: Tui Regio (20°S, 130°W) [5], a 1,500-km long flow-like figure, Hotei Regio (26°S, 78°W) [6], a 700-km wide volcanic-like terrain, and Sotra Facula (15°S, 42°W) [7], a 235-km in diameter area. With our method of Principal Component Analysis (PCA) we have managed to isolate specific regions of distinct and diverse chemical composition. We have tested this method on the previously studied Sinlap crater [8], delimitating compositional heterogeneous areas compatible with the published conclusions by Le Mouélic et al. (2008). Our follow-up method focuses on retrieving the surface albedo of the three areas and of the surrounding terrains with different spectral response by applying a radiative transfer (RT) code. We have used as input most of the Cassini HASI and DISR measurements, as well as new methane absorption coefficients [9], which are important to evaluate the atmospheric contribution and to allow us to better constrain the real surface alterations, by comparing the spectra of these regions. By superposing these results onto the PCA maps, we can correlate composition and morphology. As a test case, we used our RT code to verify the varying brightness of Hotei Regio reported by other investigators based on models lacking proper simulation of the atmospheric absorption [10]. Even though we have used exactly the same dataset, we did not detect any significant surface albedo variations over time; this led us to revise the definition of "active" regions: even if these regions have not visually changed over the course of the Cassini mission, the determination of the chemical composition and the correlation with the morphological structures [11] observed in these areas do not rule out that past and/or ongoing cryovolcanic processes are still a possible interpretation. [1] Solomonidou, A. et al. (2011). Potentially active regions on Titan: New processing of Cassini/VIMS data. In preparation. [2] Stephan, K. et al. (2008). Reduction of instrument-dependent noise in hyperspectral image data using the principal component analysis: Applications to Galileo NIMS data. Planetary and Space Science 56, 406-419. [3] Hirtzig, M. et al. (2011). Applications of a new methane linelist to Cassini/VIMS spectra of Titan in the 1.28-5.2 µm range . In preparation. [4] Wall, s. D. et al. (2009). Cassini RADAR images at Hotei Arcus and western Xanadu, Titan: Evidence for geologically recent cryovolcanic activity. Journal of Geophysical Research 36, L04203, [5] Barnes, J.W. et al. (2006). Cassini observations of flow-like features in western Tui Regio, Titan. Geophysical Research Letters 33, L16204. [6] Soderblom, L.A. et al. (2009). The geology of Hotei Regio, Titan: Correlation of Cassini VIMS and RADAR. Icarus 204, 610-618. [7] Lopes, R.M.C. et al. (2010). Distribution and interplay of geologic processes on Titan from Cassini radar data. Icarus 205, 540-558. [8] Le Mouélic et al. (2008). Mapping and interpretation of Sinlap crater on Titan using Cassini VIMS and RADAR data. Journal of Geophysical Research 113, E04003. [9] Campargue, A. et al. (2011). An empirical line list for methane at 80 K and 296 K in the 1.26-1.71 µm region for planetary investigations. Application to Titan. Icarus. Submitted. [10] Nelson, R. et al (2009). Saturn's Titan: Surface change, ammonia, and implications for atmospheric and tectonic activity. Icarus 199, 429-441. [11] Solomonidou, A. et al. (2011). Possible morphotectonic features on Titan and their origin. Planetary and Space Science. Submitted

Astrophysical Information from Objective Prism Digitized Images: Classification with an Artificial Neural Network

<p/> <p>Stellar spectral classification is not only a tool for labeling individual stars but is also useful in studies of stellar population synthesis. Extracting the physical quantities from the digitized spectral plates involves three main stages: detection, extraction, and classification of spectra. Low-dispersion objective prism images have been used and automated methods have been developed. The detection and extraction problems have been presented in previous works. In this paper, we present a classification method based on an artificial neural network (ANN). We make a brief presentation of the entire automated system and we compare the new classification method with the previously used method of maximum correlation coefficient (MCC). Digitized photographic material has been used here. The method can also be used on CCD spectral images.</p

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 Otsu’s method which is based on the optimum threshold of histogram and the k-means method which is based on the Euclidean distanc

Restauration et segmentation d'images de télédétection (une étude de méthodes accélérées)

PARIS-Télécom ParisTech (751132302) / SudocSudocFranceF

A despeckle filter for the Cassini synthetic aperture radar images of Titan's surface

International audienc

Application of Artificial Neural Networks on improving predictions of nuclear radii

A poster presented at HNPS2018, 8-9.06.2018<br

Morphotectonic features on Titan and their possible origin

International audienc