On the surface of the Moon a large number of linear features are recognizable. Long and narrow depressions are defined as lunar rilles. Their morphology has different characteristics, related to their origin. Among these, the sinuous rilles represent lineaments considered remnants of shallow lava channels. In this study, a quadrant of the Moon has been analyzed to recognize and map this type of morphology. An accurate morphometric analysis has been accomplished, using the Lunar Reconnaissance Orbiter Camera (LROC) which has a resolution of 100 m/pixel, and the Digital Elevation Model from Lunar Orbiter Laser Altimeter (LOLA) with a resolution of 6 m/pixel. Fifty-one sinuous rilles have been recognized in the study area, eighteen of which are new, improving a previous catalogue. The resulting quantitative and qualitative measurements were analyze and compared each other' to identify potential morphological trends. Different relationships between morphological parameters have been proposed, and the results enhance the importance of substrate composition in the evolution of these features, emerged mainly from the variations in width and depth values. The linear relationship between these two parameters is consistent with the idea that erosion efficiency acts proportionally in both vertical and horizontal directions. Partial filling phenomena by subsequent lava flows probably occurred in some sinuous rilles located in maria. The hypothesis of a constructive genesis requires further investigation to identify the levees created by sinuous rilles' formation process.

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Abstract. This study aims to introduce a semi-automatic classification workflow for the production of a land use/land cover (LULC) map of the island of Sardinia (Italy) following the CORINE legend schema, and a ground spatial resolution compatible with a scale of 1:25.000. The classification is based on free high-resolution satellite imagery from Sentinel-1 and Sentinel-2 collected in 2020, ancillary data derived from Sardinian Geoportal, Joint Research Centre (JRC) and OpenStreetMap. The LULC map production includes three steps: 1) pixel-based classification, realized with two different approaches, that use i) information derived from existing thematic maps eventually re-coded in case of incoherencies observed between datasets and/or satellite data products, and ii) spectral indices and parameter thresholds defined on the basis of multitemporal analysis; 2) segmentation of Sentinel-1 and 2 annual composites, and pre-labelling of segments with the pixel-based classified map, obtaining the preliminary map; 3) visual inspection procedure in order to confirm, or re-assign, classes to polygons. The accuracy of the preliminary map was tested in a sample area and on specific class of non-irrigated crops through ground truth data collected from a detailed photo-interpretation, estimating 97% of overall accuracy. The results show a great improvement from existing thematic maps in terms of detail, with the possibility of a yearly updating of the map via automatic processes. However, some limitations were found, due to the high fragmentation of Sardinian landscape and the high variety of crop types and agricultural practices, that could affect the efficiency of the classifier.