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No abstract received. [ABSTRACT FROM AUTHOR]

Increasing knowledges in the computer algorithms for calculating morphometric properties of the Earth's surface has provided in the last decades many methods of semi-automated extraction and classification of landforms. The use of digital elevation models (DEMs) and specific algorithms in GIS applications has made easier and faster the semi-automated recognition of landform classes. In this paper, we propose a new toolbox, implemented from the original version of the Jenness's landform classification, which takes into account a revision of the standard landform classes extracted by GIS. The new toolbox allowed us to extract 48 landform classes, and refined the typology of landform features in different natural landscapes, from a geomorphological point of view. The landforms classification and the morphometry of six different selected sites pertained to volcanic areas, mountain ridges, karst endorheic basins, hilly areas, fluvial sectors, and coastal plain areas were analysed and discussed. The selected areas are located in Southern Italy, where many different geological and geomorphological landscapes exist. [ABSTRACT FROM AUTHOR]

Abstract: The paper describes the current developments of a class of low-cost, light-weight autonomous underwater vehicles for coastal oceanographic applications; the vehicle class is named Fòlaga, the Italian name of an aquatic bird that swims on the water surface and dives to catch fish. The main design characteristics of the most recent vehicle of the class, the Fòlaga III, are reviewed. Navigation and control system design are discussed, with particular attention to the diving phase, which is accomplished as in oceanographic gliders by varying the vehicle buoyancy and attitude. Experimental results show that the PID robust controllers implemented are effective in the diving control phase. Finally, a distributed cooperation algorithm to be applied by a team of Fòlaga-like vehicles in adaptive oceanographic sampling applications is described. The algorithm optimizes area coverage while taking into account the accuracy in the reconstruction of the oceanographic field and inter-vehicle communication through a range constraint. The resulting dynamic programming algorithm can be implemented in a distributed fashion among the team components. [Copyright &y& Elsevier]