## 2 Materials and Methods
### Dataset Preparation and Data Description  
The data loaded into the BESS GIS are diverse (Table 1) and concern all the parameters that allow a detailed geo-characterization of the PBs present in Sicily, Malta, Gozo, and Comino. A synthesis of these data fed the WebGIS, opening the project results to a wide stakeholder audience. Two flight surveys were conducted using different DJI (Mavic 2, 210 RTK, 600 Pro) drones during the Spring-Summer season of 2019 and Autumn-Winter season of 2019/2020. These types of drones were chosen due to their size, flight time, flight safety, stability, and the payload of sensors they can carry. DJI Mavic 2 is a small UAV equipped with an excellent Hasselblad camera, with a one-inch sensor. It has a collapsible frame and two powerful landing lights, plus collision sensors on all sides. This drone combines the high technology of stability, flight safety, and miniaturization of electronics. DJI 210 RTK is a large UAV equipped with a flight terminator and parachute. It has upper, lower, and front anti-collision sensors and a sophisticated system (DJI Airsense) for signaling proximity to traditional aircrafts. The drone is waterproof and is equipped with an RTK (real-time kinematic) system. DJI 600 Pro is a large UAV equipped with a flight terminator and parachute. It has 3 GPS and 3 inertial attitude and altitude systems (IMU). It is powered by 6 batteries, can carry a maximum of 5 kg payload, and has a flight range of about 30 min without any payload. The acquired images were processed with Pix4D mapper software to build very-high-resolution orthophotos of 1.6 cm spatial resolution. In addition, satellite images and historical maps were also used. Based on these drone orthophotos, satellite images, historical maps, data related to geomorphological-sedimentological, geometric param  
Figure 2: Lithological framework of Sicily and the Maltese Archipelago. (Revised from Geologic Map of Sicily—[PERSON], 2014). eters, lithology, bathymetry, land-use/land-cover mapping of Sicilian and Maltese PBs were extracted. The drone orthophotos were geo-referenced through on-ground placement of markers whose locations were acquired using GPS RTK (GNSS TOPCON Hiper HR composed of base + rover) [60,61]. Following [PERSON] et al. [42], [PERSON] [62], and [PERSON] et al. [63], the orthophotos were also used to define the geometry and morphological characteristics of PBs. The next step, considering the various ground control points (GCPs), was to build the digital surface models (DSMs) of the PBs and then derive the slopes expressed as a percentage with linear interpolation (to express the details at a better resolution), finally classified into 4 categories (0-5-10-15%). Beaches that were difficult to reach, such as nature reserves and private beaches or those too close to airports or military installations, were analyzed using both free (Sentinel-2 with 10 m pixel spatial resolution) and commercial (WorldView-2, 50 cm pixel spatial resolution) satellite images. The satellite images were also used to derive the bathymetry [64, 65, 66], processed by the ENVI software and then reclassified by QGIS version 3.4 (Open Source Geospatial Foundation, Chicago, USA). The reclassification was necessary to differentiate each beach because of different degrees of resolution, depending on multiple factors, such as presence of _Posidonia oceanica_, clouds, sun, and quality of previous bathymmetric data. Using this bathymetry, submerged beach closure depth was calculated, following [PERSON] et al. [67], and the mapping of the _Posidonia oceanica_ was performed for the whole number of PBs following [PERSON] et al. [68]; [PERSON] et al. [69] and [PERSON] et al. [70]. Beach sediment samples were collected along 3 shore-perpendicular transects on beaches with a shoreline length \(>\) 300 m (and along 1 transect for \(<\) 300 m). During the first field survey, sediments at backshore, shoreline, and \(-\)1 m were collected; this was restricted to a shoreline sample in a second survey.