## 4 Discussion  
The present research showcases a methodology framework for identifying coastal cultural heritage assets potentially exposed to Sea Level Rise under RCP scenarios 2.6, 4.5, and 8.5 for the target years 2050 and 2100. The algorithm uses open access data and was applied in the Mediterranean EU-27 countries, which present an ideal case study as numerous heritage assets of different historic periods can be located near the coasts of countries such as Greece, Italy, France, Spain, Croatia, etc. The main concept of the proposed algorithm is to study the evolution of the terrain relief--as currently rendered by Copernicus GLO-30 DEM--by adding the projected values of parameters such as the mean vertical ground motion and the components that have been universally identified as major contributing factors to Sea Level Change (e.g., Antarctic Ice Sheet, Greenland Ice Sheet, Glaciers, Land Water Storage, Ocean Dynamic). Finally, the algorithm filters the areas that are not currently exposed to Sea Level Change but are expected to be in 2050 or 2100. This filtering is performed so that the output of the algorithm does not provide a falsely aggravated image of the effect that Sea Level Rise scenarios will have in the future, as this climate-change-related danger is already evident in the present time. In addition, the elevation information (i.e., GLO-30 DEM), through the European Ground Motion Service dataset, was also used to address the issue of constant vertical motion observed on different ground points using SAR technologies. The mean velocity value per pixel (expressed in mm/year and calculated using time series residuals and a seasonal sinusoidal component in addition to a first-order polynomial regression model [79]) was used and projected to the target years 2050 and 2100, based on the assumption that this rate of subsidence or rise will remain more or less constant in the years to come. Although these vertical motion values are produced using cutting-edge SAR algorithms and through time series analysis (i.e., they are expected to be robust estimates of the actual mean values), one has to consider the seismic-prone character of the Eastern Mediterranean Sea (e.g., Greece and Italy), which can lead to significant modifications in the vertical ground motion rate [80; 81] and thus introduce an additional source of uncertainty at a more regional extent. The EGMS dataset partially reveals this non-uniform geological behavior when comparing the calculated time-series standard deviation of the mean velocity values in earthquake-prone areas of Greece and Italy to that of Spain and France, where seismic activity is limited. As can be seen in Table 3, the calculated mean velocity standard deviation in the selected locations of France and Spain ranges from 0.01 to 0.05, while in Greece and Italy, it ranges from 0.17 to 1.62. This can be attributed--but not limited--to the continuous geological movements recorded in seismic-prone countries. The dynamic validation and monitoring of the EGMS dataset is crucial for the regular updating of the necessary projections for the target study years. The installation of a permanent Global Navigation Satellite System (GNSS) network in key coastal heritage sites would be an important step forward in validating EGMS data through ground measurements. In any case, the annual SLR projection update based on incoming and validated EGMS data is proposed to minimize potential over- or underestimation of the vertical ground movement impact. The second external source of information used in the algorithm is the Sea Level Change Projections dataset produced by NASA based on the findings of IPCC's 6 th Assessment Report for Working Group 1. This dataset is--similarly to the EGMS Vertical Ground Motion dataset--a product of time series analysis but at a larger scale; so, it cannot capture any potential region-specific characteristics.