This study presents the comprehensive three-dimensional documentation of two ancient metallurgical galleries at Agios Sostis, on the island of Sifnos, Western Cyclades (Greece). Sifnos has long been a significant center of mining activity, with evidence dating back to the late 4th millennium BC. Its basement rocks are rich in mineral deposits, including argentiferous lead, copper, iron, and zinc resources that played a catalytic role from prehistoric times. The exploitation of these metalliferous deposits, one of the key stages in the transition from the Stone Age to the Bronze Age, contributed significantly to the islands cultural development.Data acquisition was performed using high-resolution terrestrial laser scanning from multiple fixed positions within each gallery, complemented by handheld laser scanning to capture narrow and irregular sections. Topographic control was ensured through the establishment of numerous Ground Control Points (GCPs), enabling high spatial accuracy. The surface topography above the galleries and the adjacent slag mounds was documented using photogrammetric processing of imagery collected via Unmanned Aerial Systems (UAS), producing orthoimages with ground sampling distances of 4.18 cm and 1.62 cm.The interior laser scanning datasets, comprising over 500 million georeferenced 3D points, were processed into dense point clouds and further transformed into high-resolution digital terrain models and textured meshes using specialized software and a structured methodology. By integrating subsurface and surface data, overburden thicknesses ranging from 5.2 m to 66.8 m were calculated, and the volumetric estimation of metallurgical slag deposits was determined to be approximately 4,914 m³.This Digital Twin approach underscores the potential of advanced geospatial techniques for the documentation and protection of vulnerable archaeological heritage. It offers a transferable and scalable framework for similar fragile environments.

The Amynteo mega-landslide in northern Greece represents one of the most significant mass-wasting events in southeastern Europe in recent decades, with substantial geomorphological, geotechnical, and socio-economic impacts, causing the relocation of an entire village (Anargiri). Understanding such large-scale slope failure requires a multi-scale and multitemporal approach that captures both the surface dynamics and underlying controlling processes. This study investigates pre- and post-failure surface motion associated with the event by integrating Earth Observation (EO) data and Unmanned Aerial System (UAS) surveys. Surface motion gradients extending from the mine toward the nearby village of Anargyri were assessed using multi-temporal SAR interferometry (MT-InSAR) and offset tracking techniques, together with high-resolution UAS-derived Digital Surface Models (DSMs) and orthophotos. We examined the limits of each technique in measuring surface motion and exploited their complementarities across multiple spatial and temporal scales. Multi-sensor SAR datasets, including Copernicus Sentinel-1 and TerraSAR-X, were processed using MT-InSAR, supported by Copernicus EGMS products and the SNAPPING online service. Offset tracking contributed insights in areas with high displacement gradients where phase decorrelation limited interferometric methods. Repeated UAS campaigns further enhanced spatial interpretation and deformation quantification. Our analysis indicated persistent ground deformation in the pre-failure phase, spatial variability in displacement rates, and post-failure reactivation zones. The integration of InSAR and UAS photogrammetry links geomorphic process domains, such as headscarp retreat, lateral spreading, and toe bulging, with slope kinematics. We also investigate how hydrological forcing, mining-related disturbances, and lithological controls contribute to the triggering of the landslide. The study highlights the spatial and temporal dynamics of the Amynteo landslide and demonstrates the value of integrating diverse EO and UAS techniques for advancing landslide geomorphology and hazard assessment in complex slope systems. This multi-scale, multitemporal monitoring approach enhances the early detection of instability and supports the development of early warning strategies in mining environments.

The Komolithoi badlands, located in the Kissamos providence of Chania, Crete (Greece), are dunes consisting of soft clay that form conic shapes and represent a visually striking and geomorphologically active landscape, shaped by intense erosional processes characteristic of Mediterranean semi-arid environments. Their study can offer insights into the processes and mechanisms of erosion since due to their unique rock properties, including their high clay content, low organic matter, and low infiltration capacity, they are exceptionally vulnerable to erosion. Capturing the complexity and evolution of such landforms requires high-resolution, georeferenced data and a flexible methodological framework adapted to this challenging terrain.In this study, we combine Unmanned Aerial Systems (UAS) and Terrestrial Laser Scanning (TLS) data to generate ultra-detailed 3D models of the Komolithoi formations. Two full surveys were conducted in 2023 and 2024, enabling the construction of multitemporal point clouds. The integration of aerial and terrestrial methods enables dense, accurate surface coverage, overcoming limitations posed by occlusions, steep gradients, and fine-scale roughness. The resulting point clouds achieve high spatial resolution and geolocation precision, offering valuable insights into both surface morphology and potential erosion pathways. In addition to forming a baseline for future monitoring, the datasets allow for preliminary assessment of geomorphic dynamics and sediment redistribution.This contribution emphasizes the methodological potential of combining UAS and TLS technologies for badland research. It highlights how modern geomatics can advance the study of erosional landscapes where traditional surveying methods may fall short. Ultimately, this work contributes to the development of standardized, high-accuracy protocols for mapping and modeling badlands, aligning with broader efforts to monitor landscape change and aid land management in sensitive geomorphic environments.

The present study investigates the alterations of the coastal area of the Acheloos’ deltaic complex (E. Greece) for the last 20 ka and the shoreline response to the anticipated sea level rise, according to various sea-level rise prediction scenarios. The distant and near past were reconstructed through the interpretation of seismic data, sediment cores and historical aerial imagery, while the future state was evaluated considering the IPCC sea-level rise projections, adapted to the specific geomorphological and sedimentological characteristics of the study area. The results indicate a significant alteration of the area throughout the Holocene, primarily driven by the constant sea level fluctuation, while for the recent past, severe erosion has been observed in the entire study area, in places reaching 250 m (~3.4 m/yr) for the past 75 years. The IPCC predictions for 2100 suggest a continuous reduction of the delta, by 10% to 20% of the present area, while considering the most extreme climatic scenario, the percentage of the lost area could reach up to 60% of the total deltaic plain. Regardless of the prevailing scenario, it was estimated that for each 0.1 m of sea-level rise, the average land loss at the deltaic area is approximately 2.8 km2.