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ABSTRACTThis paper presents the results of the 2021 and 2022 field activities carried out at San Nicola Island (Tremiti Islands, Southern Adriatic Sea) by two groups of students as part of the Environmental Geomorphology Field Mapping course held within the Master's Degree in Geological Sciences and Technologies of Earth and Planets at University ‘G. d'Annunzio’ of Chieti-Pescara. Field activities were carried out following an integrated approach that involved morphometric, geological, and geomorphological analyses, supported by the combination of traditional methods with modern survey instruments and techniques. The Main Map (1:2,500 scale) comprehensively depicts the landscape of San Nicola Island, which is affected by both long- and short-term evolutionary processes, as witnessed by widespread slope landforms. The cartographic products presented in this work can represent a useful tool in territorial planning and management, as well as a valuable base for further scientific studies.

Smartphone sensors can collect data in many different contexts. They make it feasible to obtain large amounts of data at little or no cost because most people own mobile phones. In this work, we focus on collecting motion data in the car using a smartphone. Motion sensors, such as accelerometers and gyroscopes, can help obtain information about the vehicle’s dynamics. However, the different positioning of the smartphone in the car leads to difficulty interpreting the sensed data due to an unknown orientation, making the collection useless. Thus, we propose an approach to automatically re-orient smartphone data collected in the car to a standardized orientation (i.e., with zero yaw, roll, and pitch angles with respect to the vehicle). We use a combination of a least-square plane approximation and a Machine Learning model to infer the relative orientation angles. Then we populate rotation matrices and perform the data rotation. We trained the model by collecting data using a vehicle physics simulator.