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The 6 February 2023 earthquake doublet (Mw 7.7 and Mw 7.6) that occurred on the East Anatolian Fault Zone (EAFZ) triggered a significant amount of soil liquefaction phenomena in SE Türkiye and NW Syria. The great areal extent of the affected area and the necessity of rapid response led to the adoption and improvement of a workflow for mapping liquefaction phenomena based on remote sensing data. Using satellite imagery, we identified 1850 sites with liquefaction manifestation and lateral spreading deformation. We acquired a thorough map of earthquake-triggered liquefaction based on visual mapping with optical satellite imagery (high and very high-resolution) and the aid of radar satellite imagery and interferometry. The majority of sites are found along meandering sections of river valleys, coastal plains, drained lakes, swamps, and lacustrine basins along the East Anatolian Fault, highlighting once again the influence of geomorphology/surficial geology on the distribution of liquefaction phenomena. A total of 95% of the liquefaction occurrences were mapped within 25 km from the surface trace of the fault, confirming the distance from fault rupture as a more effective tool for predicting the distribution of liquefaction than epicentral distance. Thus, taking into consideration the rapid documentation of these phenomena without the limitations in terms of time, cost, and accessibility of the field investigation techniques, this desktop-based approach can result in a rapid and comprehensive map of liquefaction from a strong earthquake, and can also be used as a future guide for subsequent field investigations for liquefaction hazard mapping.

The correlation of coseismic landslides with the seismic and morphological parameters has been investigated in detail by many researchers, mainly after the devastating 2008 M8.0 Wenchuan, China earthquake. One of the goals of such studies is to examine the spatial distribution of the earthquake-induced landslides in order to establish a pattern depending on the type of the seismic fault. This research focusses on the island of Lefkada, Ionian Sea, Greece, that is considered one of the most prone to earthquakes regions in Europe due to its proximity to the Cephalonia Transform fault. Landslide data from the two shallow strike-slip faulting earthquakes that occurred on 2003 and 2015 are statistically analyzed in order to evaluate the landslide magnitude and area of slope failures and their frequency-area size distributions. Furthermore, the spatial distribution of failures was investigated in detail regarding its correlation to topography (slope angle, aspect, local relief, elevation), geology, and the characteristics of fault rupture. We conclude that the landslide pattern is not controlled by a single parameter and that it results from a combination and interaction of seismic, morphological, and geological factors. In particular, the parameters of slope angle, geology, and fault rupture/asperities are the ones that are clearly related to the highest landslide densities.

Rockfall is considered the main geohazard in mountainous areas with steep morphology. The main objective of this study is to assess the rockfall hazard in the cultural heritage site of the Monastery of Agia Paraskevi, Monodendri, in northern Greece, where a recent rockfall event occurred, destroying a small house and the protective fence constructed to protect the Monastery of Agia Paraskevi. To evaluate the rockfall potential, engineering geological-oriented activities were carried out, such as geostructurally oriented field measurements, aiming to simulate the rockfall path and to compute the kinetic energy and the runout distance. In addition, using remote sensing tools such as Unmanned Aerial Vehicles (UAVs), we were able to inspect the entire slope face and detect the locations of detached blocks by measuring their volume. As a result, it was concluded that the average volume of the expected detached blocks is around 1.2 m3, while the maximum kinetic energy along a rockfall trajectory ranges from 1850 to 2830 kJ, depending on the starting point (source). Furthermore, we discussed the level of similarity between the outcomes arising from the data obtained by the traditional field survey and the UAV campaigns regarding the structural analysis of discontinuity sets.

Rockfall events consist one of the most hazardous geological phenomena in mountainous landscapes, with the potential to turn catastrophic if they occur near an anthropogenic environment. Rockfall hazard and risk assessments are recognized as some of the most challenging surveys among the geoengineering society, due to the urgent need for accurate foresight of likely rockfall areas, together with their magnitude and impact. In recent decades, with the introduction of remote sensing technologies, such as Unmanned Aerial Vehicles, the construction of qualitative and quantitative analyses for rockfall events became more precise. This study primarily aims to take advantage of the UAV’s capabilities, in order to produce a detailed hazard and risk assessment via the proposition of a new semi-quantitative rating system. The area of application is located in the cultural heritage area of Kipinas Monastery in Epirus, Greece, which is characterized by the absence of pre-existing data regarding previous rockfall events. As an outcome, it was shown that the suggested methodology, with the combination of innovative remote sensing technologies with traditional engineering geological field surveys, can lead to the extraction of all the necessary quantitative data input for the proposed rating system for any natural slope.

The triggering of slope failures can cause a significant impact on human settlements and infrastructure in cities, coasts, islands and mountains. Therefore, a reliable evaluation of the landslide hazard would help mitigate the effects of such landslides and decrease the relevant risk. The goal of this paper is to develop, for the first time on a regional scale (1:100,000), a landslide susceptibility map for the entire area of the Attica region in Greece. In order to achieve this, a database of slope failures triggered in the Attica Region from 1961 to 2020 was developed and a semi-quantitative heuristic methodology called Rock Engineering System (RES) was applied through an interaction matrix, where ten parameters, selected as controlling factors for the landslide occurrence, were statistically correlated with the spatial distribution of slope failures. The generated model was validated by using historical landslide data, field-verified slope failures and a methodology developed by the Oregon Department of Geology and Mineral Industries, showing a satisfactory correlation between the expected and existing landslide susceptibility level. Having compiled the landslide susceptibility map, studies focusing on landslide risk assessment can be realized in the Attica Region.

This is the first landslide inventory map in the island of Lefkada integrating satellite imagery and reports from field surveys. In particular, satellite imagery acquired before and after the 2003 earthquake were collected and interpreted with the results of the field survey that took place 1 week after this strong (Mw = 6.3) event. The developed inventory map indicates that the density of landslides decreases from west to east. Furthermore, the spatial distribution of landslides was statistically analyzed in relation to the geology and topography for investigating their influence to landsliding. This was accomplished by overlaying these causal factors as thematic layers with landslide distribution data. Afterwards, weight values of each factor were calculated using the landslide index method and a landslide susceptibility map was developed. The susceptibility map indicates that the highest susceptibility class accounts for 38 % of the total landslide activity, while the three highest classes that cover the 10 % of the surface area, accounting for almost the 85 % of the active landslides. Our model was validated by applying the approaches of success and prediction rate to the dataset of landslides that was previously divided into two groups based on temporal criteria, estimation and validation group. The outcome of the validation dataset was that the highest susceptibility class concentrates 18 % of the total landslide activity. However, taking into account the frequency of landslides within the three highest susceptibility classes, more than 85 %, the model is characterized as reliable for a regional assessment of earthquake-induced landslides hazard.

The existence of high potential onshore and offshore active faults capable to trigger large earthquakes in the broader area of Thrace, Greece in correlation with the critical infrastructures constructed on the recent and Holocene sediments of Nestos river delta plain, was the motivation for this research. The goal of this study is twofold; compilation of a new geomorphological map of the study area and the assessment of the liquefaction susceptibility of the surficial geological units. Liquefaction susceptibility at regional scale is assessed by taking into account information dealing with the depositional environment and age of the surficial geological units. In our case, available geological mapping shows a deficient depiction of Pleistocene and Holocene deposits. Taking into consideration the heterogeneously behavior of active floodplains and deltas in terms of liquefaction, a detailed classification of geological units was mandatory. Using data provided by satellite and aerial imagery, and topographic maps, dated before the 1970’s when extensive modifications and land reclamation occurred in the area, we were able to trace fluvial and coastal geomorphological features like abandoned stream/meanders, estuaries, dunes, lagoons and ox-bow lakes. This geomorphological-oriented approach clearly classified the geological units according to their depositional environment and resulted in a more reliable liquefaction susceptibility map of 4 classes of susceptibility; Low, Moderate, High and Very High. The sediments classified as very high liquefaction susceptibility are related to fluvial landforms, the high to moderate liquefaction susceptibility ones in coastal and floodplain landforms, and low susceptibility in zones of marshes. The sediments classified in the highest group of liquefaction susceptibility cover 85.56 km2 of the study area (16.6%). Particular attention was drawn to critical infrastructure (Kavala International Airport “Alexander the Great”) constructed on the most prone to liquefaction areas.

Rockfall consists one of the most harmful geological phenomena for the man-made environment. In order to evaluate the rockfall hazard, a variety of engineering geological studies should be realized, starting from conducting a detailed field survey and ending with simulating the trajectory of likely to fail blocks in order to evaluate the kinetic energy and the runout distance. The last decade, new technologies, i.e., remotely piloted aircraft systems (RPAS) and light detection and ranging (LiDAR) are frequently used in order to obtain and analyze the characteristics of the rock mass based on a semi-automatic or manual approach. Aiming to evaluate the rockfall hazard in the area of Nestos, Greece, we applied both traditional and structure from motion (SfM)-oriented approaches and compared the results. As an outcome, it was shown that the semi-automated approaches can accurately detect the discontinuities and define their orientation, and thus can be used in inaccessible areas. Considering the rockfall risk, it was shown that the railway line in the study area is threaten by a rockfall and consequently the construction of a rockfall netting mesh or a rock shed is recommended.

Timely and rational prediction of coseismic landslides is crucial for the design and development of key infrastructure capable to protect human lives in seismically active regions. This research introduces the novel Hybrid Coseismic Landslide Forecasting model (COLAFOS) that takes into consideration three parameters namely: The Average Slope of the Active Areas, the Slope Aspect and the types of Geological forms. The developed model was tested on two datasets from the island of Lefkada Greece, for years 2003 and 2015. COLAFOS is a hybrid model, employing the Fuzzy c-Means clustering, the Ensemble Adaptive Boosting (ENS_AdaBoost) and the Ensemble Subspace k-Nearest Neighbour (ENSUB k-NN) algorithms. The introduced model managed to correctly classify the coseismic landslides according to their severity, with a success rate of 70.07% and 72.88% for 2003 and 2015, respectively. The algorithm has shown very good performance for the classes of major severity, reaching an accuracy up to 92%. Accuracy, Sensitivity, Specificity, Precision and F-1 Score, were used to evaluate the performance of the model. Given the fact that this is a multi-class classification problem, 'One Versus All' Strategy was used in the evaluation process. Although the datasets were relatively unbalanced, the evaluation indices sealed the efficiency of the model.

Medicanes, a type of strong hurricanes/cyclones occurring in the Mediterranean, can be the source of major geohazard events in Mediterranean coastal and inland areas. Medicane Ianos that hit Greece during 17–19 September 2020 caused widespread damage, with numerous landsides and floods being the most prominent. Following the landfall of Medicane Ianos, a series of field surveys were launched together with rapid response through satellite imagery. We focused on two of the areas most affected by Medicane Ianos, Cephalonia island and Karditsa, Thessaly, both in Greece. A rapid landslide inventory for the Karditsa region was prepared using Copernicus Sentinel-2 satellite imagery, the first of its kind for a severe weather event in Greece. The mountainous area of Karditsa region in western Thessaly experienced the unprecedented number of 1696 landslides, mapped through satellite imagery and examined in the field. Cephalonia Island experienced a smaller number of landsides but damaging debris flows and severe structural damages. The rapid landside inventory was then compared to new methods of automated landslide mapping through change detection of satellite imagery.