Nowadays, the acquisition of very high resolution (VHR) imagery guarantees an excellent quality of coastal topographic surveys and monitoring. Alongside the rapid progress of remote sensing, digital photogrammetry and image processing of data obtained by unmanned aerial vehicles (UAVs) provides outstanding opportunities for VHR mapping of the coastal zone, including the coverage of difficult-to-access areas. Till the previous two years, the Bulgarian coast was “intact” for this modern technology and was regularly surveyed to detect and analyze the ongoing shoreline dynamics and trends of morphological changes. Both spatial planning and integrated coastal zone management, however, require highly accurate and up-to-date geodata, being among the main reasons for the wide application of drones worldwide in shoreline surveying, along with the low cost of the related mapping campaigns. This work aims to demonstrate the capabilities of UAV-based coastal landform mapping at Shabla Municipality case study site, Bulgaria. The above coastal segment was surveyed from a flight altitude of 200 m and at 5.8 cm ground sampling distance (GSD). In addition, erosion-prone areas were photographed from 50 m altitude and at 1.5 cm GSD. A digital surface model with a resolution of 20 cm for the whole coast of the Shabla Municipality was created. A finer one, with 6 cm cell size was derived after Structure for Motion data processing (SfM) for the area of Krapets Village together with the contiguous sector between Cape Shabla and Shablenska Tuzla Lagoon. A set of ground control points (GCPs) was used for georeferencing purposes. The shore was divided into erosional, erosional-depositional, and depositional segments, along with accompanying geomorphological classification of the identified landforms.
Varna and Beloslav Lakes represent the largest inland water body along the Bulgarian coast. The shores of typical firth have been transformed into highly developed industrial areas. In another point of view, in the last 50 years, the bottom of lakes has been significantly anthropogenized. The Lack of regular monitoring of morphological changes and processes on the bottom does not allow a correct assessment of lakes' status. This work presents our initial activity to create a composite digital model of the Varna - Beloslav Lake complex, with a comprehensive analysis and identification of contemporary morphological bedforms. For creating a digital terrain model of the lakes, a geo based database was created with bathymetric surveys from different years and equipment, combined with high-resolution orthophoto mosaic of the shores. The data combine sonar mosaics, single beam, and multibeam bathymetric data, and UAV images. This provides accurate (vertical accuracy of less than 0.5% of water depth), full-bottom coverage of the bathymetric data allowing the generation of a digital model of the seafloor relief with a horizontal resolution of 3 m and creation a bathymetric map with an interval of 0.5 m. The lakes' bottom forms are divided into natural and anthropogenic types. The conducted morphometric analysis gave us reason to localize specific bedforms of a coastal sloop, slightly sloping accumulative bottom, lake plains, channels, and other features of anthropogenic nature.
Recently, the application of the multibeam echosounder systems in Bulgaria has become a standard method of studying the seabed. Nowadays, our task is to combine archival bathymetric data from single-beam echo sounding and contemporary multibeam echo sounding scanning. In this work, we present our initial activity in our primary scientific goal to create a composite digital model of the Broad Burgas Bay that will allow us to the future geospatial interpretation and identification of present-day seabed morphological forms and processes on the seafloor. For this study, a geo base database was created with bathymetric surveys from different years and equipment. The used data combine sonar mosaics, single beam, and multibeam bathymetric data and raster satellite images, processed in PDS 2000, SonarWiz, and GIS environment. The data is equated in a Baltic elevation system, which allows the construction of a digital relief model accurately. The density and coverage of the bathymetric data allowed the generation of a digital bathymetric model of the seafloor relief with a horizontal resolution of 14 m. A bathymetric map with an interval of 1 m was created with high accuracy. Such a high-resolution model is a significant advance in the high-resolution mapping of the Bulgarian Black Sea seafloor.
Beach-dune systems host sensitive habitats subject to protection in compliance with the EU and national legislation. Along the Bulgarian coast, the substrata for the formation of depositional landforms are of predominantly terrigenous origin. Once eroded from the source provinces, they are transported as solid runoff and accumulated in the littoral zone. Consequently, the spatial distribution of depositional landforms is primarily related to the occurrence of gullies and ravines, estuaries and lagoons. Geomorphological mapping and classification, alongside vegetation mapping, represents the backbone of habitats identification in the case of coastal environments. Depositional landforms along the Bulgarian coast correspond to a number of sensitive habitats, enlisted in the national Red Data Book, and subject to protection pursuant to the country’s Biodiversity Act transposing the EU Council Directive 92/43/EEC (Habitats Directive). Three representative coastal segments along the North Bulgarian coast, hosting several sensitive habitat types, were surveyed in 2019 with a DJI Phantom 4 Pro quadcopter. All three are parts of the Bulgarian national nature conservation network. Accordingly, three sets of high-resolution orthoimages, digital surface models (DSMs) and 3D tiled models were generated in order to facilitate the GIS interpretations. The UAS-acquired imagery, DSMs and 3D models proved to be extremely useful geospatial data, greatly facilitating the process of coastal landforms and habitats identification. Nevertheless, as monitoring requires repetitive surveys, we should emphasize that the year 2019 marked the very first season when the approach was applied by our team. Therefore, deductions regarding long-term trends in the landform/habitat dynamics would be yet inappropriate.
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