Aerial surveys in coastal areas using Unmanned Aerial Vehicles (UAVs) present many limitations. However, the need for detailed and accurate information in a marine environment has made UAVs very popular. The aim of this paper is to present a protocol which summarizes the parameters that affect the reliability of the data acquisition process over the marine environment using Unmanned Aerial Systems (UAS). The proposed UAS Data Acquisition Protocol consists of three main categories: (i) Morphology of the study area, (ii) Environmental conditions, (iii) Flight parameters. These categories include the parameters prevailing in the study area during a UAV mission and affect the quality of marine data. Furthermore, a UAS toolbox, which combines forecast weather data values with predefined thresholds and calculates the optimal flight window times in a day, was developed. The UAS toolbox was tested in two case studies with data acquisition over a coastal study area. The first UAS survey was operated under optimal conditions while the second was realized under non-optimal conditions. The acquired images and the produced orthophoto maps from both surveys present significant differences in quality. Moreover, a comparison between the classified maps of the case studies showed the underestimation of some habitats in the area at the non-optimal survey day. The UAS toolbox is expected to contribute to proper flight planning in marine applications. The UAS protocol can provide valuable information for mapping, monitoring, and management of the coastal and marine environment, which can be used globally in research and a variety of marine applications.

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Coastline change and human activities in shoreline zones are two factors indicating the vulnerability and the quality of a coastal environment. In this article, coastline evolution and spatiotemporal differences on coastal touristic infrastructure are presented as two case studies. Both case studies have increasing interest among scientists monitoring sensitive coastal areas, and for stakeholders evolved in the tourist industry. The study is twofold: monitors the shoreline evolution and examines how the shoreline behavior affects the seasonal anthropogenic touristic infrastructure. Shoreline detection methodology integrates unmanned aerial systems (UAS) or high-resolution satellite images for data acquisition, and geographic object-based image analysis (GEOBIA) for the shoreline recognition and the infrastructure change detection. The methodology used produced robust results in the aspect of mapping and detecting coastline changes, coastal erosion and the human pressure due to specific activities.

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