A geophysical investigation was carried across the M3 burial mound from Silvașu de Jos —Dealu Țapului, a tumuli necropolis in western Romania, where the presence of the Yamnaya people was certified archaeologically. For characterizing the inner structure of the mound, two conventional geophysical methods have been used: a geomagnetic survey and electrical resistivity tomography (ERT). The results allowed the mapping of the central features of the mound and the establishment of the relative stratigraphy of the mantle, which indicated at least two chronological phases. Archaeological excavations performed in the central part of the mound accurately validated the non-invasive geophysical survey and offered a valuable chronological record of the long-forgotten archaeological monument. Geophysical approaches proved to be an invaluable instrument for the exploration of the monument and suggest a fast constructive tool for the investigation of the entire necropolis which currently has a number of distinct mounds.

This communication study aims to provide evidence on how Sentinel sensors and Copernicus Programme’s contributing missions can support heritage endangered by natural hazards. The recent catastrophic floods of 2022 in Pakistan, mainly in the Indus Valley, threatened one of the most iconic sites within the country; thus, the UNESCO World Heritage Site of Mohenjo-Daro was selected here as a case study. Even if the main area of the site was not directly affected by the floods but rather by the heavy rains, its landscape suffered profound damage. This study aims to report a combined remote-sensing methodology for a rapid assessment of the flooded areas around the site. By using Sentinel-1 radar data in combination with mid-resolution Sentinel-2 data and Planet Lab images, it was possible to accurately map the affected areas near the site. This approach can be used to better understand the extent of the affected areas and build a better recovery strategy. A near-real-time satellite-based investigation and observations combining various sensors and resolutions (Sentinel 1 and 2 images, as well as Planet Lab images) can provide valuable insights for local heritage managers.

This study evaluates the impact of seepage on the integrity of artificial levees in low-lying regions, with a particular focus on Hungary, where levees built over a century ago lack comprehensive construction documentation, complicating current assessments of their effectiveness. Advanced geophysical methods – electrical resistivity tomography (ERT) and ground-penetrating radar (GPR) – were applied in a controlled tank experiment designed to simulate varied flood conditions along a 37-m levee section. The three-dimensional (3D) ERT profiles successfully delineated seepage pathways as the tank filled, while the 3D GPR profiles indicated areas of increased amplitude, corresponding to seepage zones and the water table. Validation through drilling confirmed the geophysical findings, underscoring the accuracy of ERT and GPR in non-destructively identifying subsurface features and seepage channels. The results highlight the applicability of these methods for evaluating levee integrity and seepage dynamics, offering a reliable approach for flood risk assessment in Hungary and similar flood-prone areas worldwide.

Artificial levees along major rivers are critical for flood-risk mitigation, yet many aging structures have poorly constrained internal composition and material heterogeneity, limiting the reliability of conventional safety assessments. This study develops a quantitative, non-destructive framework for characterizing levee internal structure by integrating electrical resistivity tomography (ERT) with borehole (BH) observations. ERT profiles were combined with borehole measurements of grain size (D50) and water content to investigate subsurface compositional variability and to evaluate relationships between sedimentological and geophysical parameters. Grain-size data from borehole samples were modeled using four predictive approaches—random forest regression (RFR), artificial neural networks (ANN), linear regression (LR), and support vector regression (SVR)—based on ERT-derived resistivity and moisture information. The results reveal pronounced internal heterogeneity within the investigated levees and demonstrate consistent relationships between sediment composition, water content, and electrical resistivity. Among the tested models, the ensemble-based RFR provided the highest predictive performance (R² = 0.81). These findings indicate that D50 characteristics of levee materials can be reliably inferred from ERT data using machine learning, reducing the need for destructive sampling. The proposed approach offers a transferable methodology for levee assessment and supports future applications in non-destructive monitoring, spatially explicit flood-risk analysis, and climate-resilient flood-protection management.

GeoQuickView is a software application designed to bridge the gap between advanced Geographic Information Systems (GIS) and users with no prior experience in GIS. This paper explores the development, functionality, and user-centric design of GeoQuickView, highlighting its capabilities in loading, visualizing, and analyzing geographic data. Emphasis is placed on its use with LiDAR-derived Digital Terrain Models (DTMs), user-friendly interface, and robust tools for measurement and digitization. The application’s role in democratizing access to complex geospatial data is discussed. The software was designed to work seamlessly with data from Romania and can display various types of raster elevation data. While the Coordinate Reference System (CRS) may present challenges for data extraction outside of Romania, the data can still be visualized effectively within the app. The application is available upon request.