Lack of knowledge about freshwater use in ports of tourist destinations hinders accurate assessment of water availability and water planning. In this study, freshwater use in the Port of Palma (Spain) is analyzed by sector (commercial, mixed, navy and recreational) for the period 2007–2018. This study shows the dynamics of consumption and evaluates the effects of increased cruise tourism from 2007 to 2018 in the port. Water data supplied by the Port Authority of the Balearic Islands for each sector, together with water volumes recharged by ships, allow a detailed analysis of the water used by merchants and cruise lines. Results reveal a significant increase in freshwater withdrawals by cruise ships in the Port of Palma in the last ten years, closely related to the boom of cruise activity. Water use and recharge by cruise ships increased in both the high and low tourist seasons. Homeport cruises have a significant effect on the increase of freshwater withdrawals, as each homeport cruise ship recharged a mean volume of 628 m3 per mooring. This paper proposes a water withdrawal indicator of liters loaded per passenger at the port. Given the current lack of restriction on the number of cruise ships per day docking in the Port of Palma, cruise activity may well become a threat to water availability during drought episodes and another environmental cost to add to the already questioned cruise tourism activity of the island.

We propose an optimized Structure-from-Motion (SfM) Multi-View Stereopsis (MVS) workflow, based on minimizing different errors and inaccuracies of historical aerial photograph series (1945, 1979, 1984, and 2008 surveys), prior to generation of elevation-calibrated historical Digital Surface Models (hDSM) at 1 m resolution. We applied LiDAR techniques on Airborne Laser Scanning (ALS) point clouds (Spanish PNOA LiDAR flights of 2014 and 2019) for comparison and validation purposes. Implementation of these products in multi-temporal analysis requires quality control due to the diversity of sources and technologies involved. To accomplish this, (i) we used the Mean Absolute Error (MAE) between GNSS-Validation Points and the elevations observed by DSM-ALS to evaluate the elevation accuracy of DSM-ALS generated with the LAScatalog processing engine; (ii) optimization of the SfM sparse clouds in the georeferencing step was evaluated by calculating the Root Mean Square Error (RMSE) between the Check Points extracted from DSM-ALS and the predicted elevations per sparse cloud; (iii) the MVS clouds were evaluated by calculating the MAE between ALS-Validation Points and the predicted elevations per MVS cloud; iv) the accuracy of the resulting historical SfM-MVS DSMs were assessed using the MAE between ALS-Validation Points and the observed elevations per historical DSM; and (v) we implemented a calibration method based on a linear correction to reduce the elevation discrepancies between historical DSMs and the DSM-ALS 2019 reference elevations. This optimized workflow can generate high-resolution (1 m pixel size) hDSMs with reasonable accuracy: MAE in z ranges from 0.41 m (2008 DSM) to 5.21 m (1945 DSM). Overall, hDSMs generated using historical images have great potential for geo-environmental processes monitoring in different ecosystems and, in some cases (i.e., sufficient image overlapping and quality), being an acceptable replacement for LiDAR data when it is not available.

<p>Subsidence is a highly destructive natural hazard, which can be caused by both natural and anthropogenic causes. Its impacts include a decrease in storage capacity of aquifer systems, the creation of cracks and fissures, damages to buildings and infrastructures, and an increase of the susceptibility to flooding. In this study, Persistent Scattered Interferometry (PSI) has been used to process Synthetic Aperture Radar (SAR) images, for the detection and analysis of ground deformation and subsidence processes in the island of Mallorca. The study database is composed of 120 images captured by the Sentinel 1A and 1B satellites (between May 2016 and December 2019), from which we derived a map of accumulated displacement rates occurred during a 3 years and a half period. The results show important subsidence processes of up to 3 cm per year in large areas of the sedimentary basin of Palma, and of lesser magnitude (between 1 and 2 cm per year) in locations of the Inca basin and in small basins in the Tramuntana Range. A significant relationship has been observed between the thickness of the Quaternary sediment and the observed subsidence rates. The results highlight the high degree of geomorphological dynamism at very short time scales that characterizes Mallorca, and the vulnerability of certain urban areas, such as the city of Palma (400000 inhabitants), and agricultural areas, such as the Central Depression, facing the risk of subsidence and associated damages.</p>

<p>The availability of high spatial resolution historical remote sensing products and advances in Structure from Motion (SfM), Multi-View Stereopsis (MVS) and LiDAR (Light Detection And Ranging) techniques offer a wide range of applications to understand landscape evolution and to monitor geomorphological changes. In this work, we apply an optimised SfM-MVS workflow based on minimising georeferencing error on black and white and colour historical photographs acquired in 1945 (American flight series A), 1979 (Spanish Interministerial Order), 1991 (Spanish Coastal Directorate General) and 2006 (PNOA flights) to generate 3D point clouds, Digital Elevation Models (DEM) and orthomosaics at 1 m resolution for the beach-dune system and coastal area of Es Trenc (southern Mallorca). In addition, we applied LiDAR techniques on the Airborne Laser Scanning (ALS) point clouds collected by the PNOA LiDAR flights in 2014 and 2019 to generate DEMs. The use of these products in multi-temporal analysis requires quality control of their spatial accuracy due to the diversity of sources and technologies used. The first quality control was based on evaluating the SfM sparse cloud optimisation process in the orthomosaic georeferencing step by calculating the RMSE between the Ground Validation Points (GVP) surveyed with Global Navigation Satellite System (GNSS) readings and the predicted height values at the closest point of each SfM sparse cloud. The second quality control was based on systematically assessing the vertical accuracy of the dense MVS and ALS clouds as a step prior to point interpolation to generate DEMs at 1 m resolution. The height errors of these clouds were estimated by calculating the RMSE between the Ground Test Points (GTP) read by GNSS on the ground and the predicted values at the respective nearest point for each of the MVS and ALS cloud series. Preliminary results show that the optimised SfM-MVS method applied on historical imagery can generate high-resolution orthomosaics and DEMs with acceptable accuracy: RMSE in <em>z</em> ranges from 0.2 to 10 m, with the lower accuracy obtained for the 1945 DEM, due to the lower resolution and coarse grain size (texture) of the photographs used. Overall, these products in combination with current LiDAR-derived DEMs have great potential for monitoring historical landscape evolution in coastal ecosystems.</p>