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The retreat rates of Arctic coasts have increased in recent decades at many sites, and an essential part of coasts considered accumulative before have turned erosional due to global climate changes and construction in the coastal zone. In this paper, we study a 7 km long coastal section of the western Gydan Peninsula in a new construction area. Based on the interpretation of multi-temporal satellite imagery, we assessed coastal dynamics in distinct periods from 1972 to 2020. We analyzed the geological structure of the coast as well as changes in hydrometeorological parameters with time, and considering the human impact, we proposed the main drivers of spatial and temporal variations of coastal dynamics. The studied low-lying sandy accumulative marine terrace was more or less stable in the period before construction (1972–2014). However, with the area's development, the coast dynamics changed drastically: in 2014–2017, three-quarters of the studied area experienced retreat, and the average retreat rate amounted to 5.8 m/yr, up to 28.5 m/yr near the construction sites. We relate this coastal erosion intensification to human impact combined with the growth of hydrometeorological forcing. Although coastal erosion slowed down after 2017, the retreat trend remained. In the coming years, with Arctic climate warming, erosion of the studied coast will continue. [ABSTRACT FROM AUTHOR]

The amount of Earth observation images available to the public has been the main source of information, helping governments and decision-makers tackling the current world's most pressing global challenge. However, a number of highly skilled and qualified personnel are still needed to fill the gap and help turn these data into intelligence. In addition, the accuracy of this intelligence relies on the quality of these images in times of temporal, spatial, and spectral resolution. For the purpose of contributing to the global effort aiming at monitoring natural and anthropic processes affecting coastal areas, we proposed a framework for image processing to extract the shoreline and the shallow water depth on GeoEye-1 satellite image and orthomosaic image acquired by an unmanned aerial vehicle (UAV) on the coast of San Vito Lo Capo, with image preprocessing steps involving orthorectification, atmospheric correction, pan sharpening, and binary imaging for water and non-water pixels analysis. Binary imaging analysis step was followed by automatic instantaneous shoreline extraction on a digital image and satellite-derived bathymetry (SDB) mapping on GeoEye-1 water pixels. The extraction of instantaneous shoreline was conducted automatically in ENVI software using a raster to vector (R2V) algorithm, whereas the SDB was computed in ArcGIS software using a log-band ratio method applied on the satellite image and available field data for calibration and vertical referencing. The results obtained from these very high spatial resolution images demonstrated the ability of remote sensing techniques in providing information where techniques using traditional methods present some limitations, especially due to their inability to map hard-to-reach areas and very dynamic near shoreline waters. We noticed that for the period of 5 years, the shoreline of San Vito Lo Capo sand beach migrated about 15 m inland, indicating the high dynamism of this coastal area. The bathymetric information obtained on the GeoEye-1 satellite image provided water depth until 10 m deep with R2 = 0.753. In this paper, we presented cost-effective and practical methods for automatic shoreline extraction and bathymetric mapping of shallow water, which can be adopted for the management and the monitoring of coastal areas. [ABSTRACT FROM AUTHOR]

Arctic coasts composed of frozen deposits are extremely sensitive to climate change and human impact. They retreat with average rates of 1–2 m per year, depending on climatic and permafrost conditions. In recent decades, retreat rates have shown a tendency to increase. In this paper, we studied the coastal dynamics of two key sites (Ural and Yamal coasts) of Baydaratskaya Bay, Kara Sea, where a gas pipeline had been constructed. Based on multi-temporal aerial and satellite imagery, we identified coastal erosion rates at several time lapses, in natural conditions and under human impact, and discussed their temporal variability. In addition to planimetric (m/yr), we calculated volumetric (m3/m/yr) retreat rates of erosional coasts using ArcticDEM. We also estimated the influence of geomorphology, lithology, and permafrost structure of the coasts on spatial variations of their dynamics. Erosional coasts of the Ural key site retreat with higher mean rates (1.2 m/yr and 8.7 m3/m/yr) as compared to the Yamal key site (0.3 m/yr and 3.7 m3/m/yr) due to their exposure to higher open sea waves, more complex lithology, higher ice content and lower coastal bluffs. Since the 1960s, coastal retreat rates have been growing on both coasts of Baydaratskaya Bay; we relate this effect with Arctic climate warming. From the 1960s to 2005, such growth was moderate, while in 2005–2016 it became rapid, which may be explained by the enhanced wave and thermal action or by the onset of industrial development. The adjacent coastal segments, originally accumulative, remained relatively stable from the 1960s to 2005. After 2005, a considerable part of them began to retreat as a result of changing weather conditions and/or increasing human impact. [ABSTRACT FROM AUTHOR]