Accurate three-dimensional modeling of buildings and cultural heritage objects is crucial for applications such as modeling, engineering, and documentation. Traditional methods, such as Terrestrial Laser Scanning (TLS), provide high precision. The recent incorporation of LiDAR sensors into consumer smartphones, like iPhones, presents a cost-effective and accessible alternative. However, the accuracy and limitations of freely available mobile LiDAR applications have not been sufficiently quantified.

This research aims to quantitatively assess the geometric accuracy of iPhone LiDAR as a low-cost alternative for 3D modeling. Three free iPhone LiDAR applications, Modelar, 3D Scanner, and SiteScape, were evaluated across various study cases, focusing on small-scale heritage statues, indoor corridors, and exterior façades of a building. A geodetic reference network was established using a total station, leveler, and RTK GNSS to achieve high absolute accuracy for detailed comparison of the 3D point clouds. Tracking drift was minimized via standardized scanning procedures, maintaining a distance of less than five meters and moving slowly and methodically. The acquired point clouds were processed and compared using CloudCompare, incorporating noise filtering, control point alignment, Iterative Closest Point (ICP) refinement, and multiscale model-to-model (M3C2) analysis.

The results indicate RMS errors ranging from 1.34 cm for small heritage objects to 4.6 cm for building façades, with the Modelar application achieving the highest overall accuracy. Significant errors were concentrated around reflective surfaces such as glass windows, and the removal of these points improved geometric consistency by approximately 50%. All three applications produced point clouds suitable for small to medium-scale indoor and outdoor mapping; however, the 3D Scanner and SiteScape applications exhibited greater deviations, particularly in large or complex environments.

Freely available iPhone LiDAR applications, particularly Modelar, constitute a practicable low-cost option for expeditious centimeter-level 3D modeling in Building Information Modeling (BIM) and heritage documentation. Limitations persist for large-scale architectural elements and reflective materials, wherein TLS remains the benchmark for maximal precision. These results delineate the capabilities and constraints of iPhone LiDAR relative to geodetic references.

Issa Loghmanieh is funded by the Stipendium Hungarian scholarship under the joint executive program between Hungary and Iran.

How to cite: Hamdan, A., Loghmanieh, I., and Bertalan, L.: Comparative accuracy analysis of iPhone LiDAR applications for high-resolution 3D reconstruction, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2752, https://doi.org/10.5194/egusphere-egu26-2752, 2026.

Landslide analysis in vegetated and inaccessible areas represents a key challenge for hazard assessment and risk mitigation. This study presents the application of a UAV-borne low-frequency Ground Penetrating Radar (GPR) system to investigate the internal structure and deep geometry of an earth slide located in southern Italy. The GPR system is based on a Cobra Plug-in Sub-Echo 70 antenna operating in the 20–140 MHz frequency range and mounted on a multirotor UAV. The survey consisted of an east–west transect crossing the landslide body, flown at approximately 1 m above ground level due to dense vegetation about 60–70 cm high. To ensure precise navigation and stable flight altitude, the UAV was equipped with a high-precision GNSS system and a radar altimeter, enabling accurate terrain-following acquisition in complex topographic conditions.  The acquired radargram shows a coherent subsurface response down to an investigation depth of approximately 15 m. A laterally continuous, high-amplitude reflector is clearly visible at around 10 m depth and is interpreted as the main sliding surface controlling the gravity-driven process. Above this surface, zones of chaotic and heterogeneous reflections indicate disturbed stratigraphic units and reworked debris involved in deformation processes across the main body. The analysis highlighted a roto-translational kinematics in the upper part of the source area, as often observed in this type of landslide, evolving downslope into a predominantly translational movement. The central portion of the radargram exhibits more continuous sub-parallel reflectors, suggesting partial preservation of the original stratigraphic organization within the displaced material.  Despite the limited acquisition geometry, our results demonstrate that UAV-borne low-frequency GPR provides critical subsurface information for understanding gravity-driven processes. The identification of depth and geometry of landslide failure  surfaces  represents a key contribution to landslide susceptibility analysis, hazard evaluation for definition of effective risk mitigation and monitoring strategies.

How to cite: Famiglietti, N. A., Massa, B., Revellino, P., Testa, G., Memmolo, A., Migliazza, R., and Vicari, A.: Identification of the Sliding Surface of a Dormant Landslide Using UAV-Borne Low-Frequency Ground Penetrating Radar: The Melizzano Case Study (Southern Italy), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6892, https://doi.org/10.5194/egusphere-egu26-6892, 2026.

How to cite: Padrón, E., Bañares, L., Montero, C., Pérez, N. M., Melián, G. V., Tabares, F., Asensio-Ramos, M., Hernández, P. A., Recio, P., and Cachón, J.: Design and experimental development of a portable instrument for measuring diffuse helium efflux in active volcanic systems , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8191, https://doi.org/10.5194/egusphere-egu26-8191, 2026.

Crustal movement and deformation monitoring are important methods for reflecting changes in crustal stress. Crustal deformation data can be used to accurately describe the movement and deformation characteristics of active blocks and their boundary zones, providing effective data constraints for earthquake prediction and scientific research. Crustal deformation monitoring mainly includes crustal movement monitoring (such as Global Navigation Satellite System (GNSS) observations), surface strain monitoring (such as borehole strain observations), and surface tilt monitoring (such as vertical pendulum tilt observations). The high-precision and high temporal resolution data generated are widely used in the study of slow earthquakes, volcanic activity, and earthquake precursors. Given the close relationship between geophysical instruments and observation environments, crustal deformation monitoring instruments can not only record structural signals, but also interference signals caused by changes in surrounding loads. This article is based on the analysis displacement solution caused by the point load model, and derives formulas for calculating the surrounding tilt field and strain field, providing a theoretical basis for the quantitative calculation of the influence of surrounding loads in crustal deformation monitoring. In addition, this article also proposes a method for calculating the strain effects of two-dimensional and three-dimensional irregular shaped loads. Finally, based on the four component borehole strain observation data from Guza borehole strainmeter and the observation data of the surrounding river water level, the applicability of this analytical solution in quantitatively calculating the degree of influence of irregular load models in the surrounding area was verified under the conditions of setting the surrounding medium parameters (elastic modulus and Poisson's ratio). The results indicate that: (a) for the two-dimensional irregular shaped load model problem, vector superposition calculation can be performed after load scattering; (b) For the problem of three-dimensional irregular shaped load models, different weights can be assigned to scattering points after load scattering, and the two-dimensional irregular shaped load method can be used for calculation. The convergence process during vector superposition proves the correctness and feasibility of this method. This study provides a research foundation for the quantitative analysis of the influence of surrounding load interference in crustal deformation monitoring; (c) There is a high possibility that the data disturbance information of the four component drilling strain observation data at Guzan Station in summer is affected by the disturbance of the water level data of nearby rivers. This research work can quantitatively explain the degree of influence of load type interference factors on high-precision geophysical observation data, providing a quantitative interpretation scheme for the extraction of earthquake precursor anomalies.

Fund support: Ningxia Natrual Science Foundation Project (2024AAC03436); National Natural Science Foundation of China (41704062); National Key Research and Development Program of China (2021YFC3000705-06).

Figure 1 Example of the influence of irregularly shaped loads in the near field. In the figure: (a) represents the positional relationship between the Guzan borehole strainmeter and the Dadu River; (b) Representing the comparison of the changes in actual observed data with the results of irregular load model calculations.

How to cite: Yan, W., Li, Z., Niu, A., Tang, L., Lu, X., and Zhai, L.: Analytical solution of the influence of irregularly shaped loads in the near field on crustal deformation monitoring, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9036, https://doi.org/10.5194/egusphere-egu26-9036, 2026.

Unmanned aircraft vehicle (UAV) and airborne magnetometers have recently emerged as new technology to gather, in a productive and economical way, high-resolution magnetic data. In volcanic environments, taking advantage of the strong magnetization contrasts of adjacent rock formations, magnetic field measurements can detect and characterize the main subsurface structural features and indicate areas of hydrothermal alteration, or highlight thermal anomalies. Magnetometer-equipped drones have advantages in high maneuverability and hover ability and are able to carry out large-scale magnetic surveys in areas that are difficult to access due to complex ground conditions and large topographical fluctuations or that would pose a potential hazard to operators.

Between 2024 and 2025, aeromagnetic surveys were conducted by UAV within the IRGIE project for the first time at Aeolian Islands (Italy) to identify possible areas of different magnetization potential related to hydrothermal fluid circulation. In particular, the most significant geochemistry sites have been investigated at Lipari, Salina, Panarea and Vulcano Islands. The airborne magnetic surveys were conducted using the Matrice 300 UAV with a MagArrow sensor, a laser pumped cesium total field scalar magnetometer, collecting magnetic data at a 1000 Hz sample rate synchronized on-board GPS (1 Hz sample rate). The high spatial resolution offered by the use of low-altitude drones proved essential for mapping the magnetic anomaly in detail and deducing the distribution of magnetization intensity in the investigated regions. The upcoming interpretation of acquired magnetic data, to be integrated with geophysical and geochemical data will may contribute to the development of conceptual models of geothermal circulation in the investigated areas.

How to cite: Napoli, R., De Beni, E., Cantarero, M., Sicali, A., Currenti, G., Cantucci, B., and Procesi, M.: Drone magnetic surveys of Aeolian Islands (Italy) hydrothermal areas within IRGIE project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9092, https://doi.org/10.5194/egusphere-egu26-9092, 2026.

OGS has been developing and producing cost-effective GNSS technology devices and systems in collaboration with the private sector since 2015. These systems, called LZER0, have been efficiently applied to landslide monitoring, also in collaboration with local administrations and the Regional Civil Protection. In recent years, the development of LZER0 has received new impetus from the PNRR Geoscience IR project.

We have developed a new adaptation of the LZER0 device for temporary monitoring, called LZER0-MOB. It addresses the specific needs of temporary monitoring, which may be carried out in emergency conditions, such as user-friendliness and reduced consumption and weight.

We have implemented a mobile infrastructure ready to be activated in case of emergencies due to geological hazards, consisting of a pool of LZER0-MOB stations. This infrastructure, which benefits from the low cost of these devices, will expand monitoring capabilities during emergencies to support civil protection activities and will be integrated into existing infrastructures. It will also enable continuous monitoring of areas of specific interest after the emergency phases.

In the first prototypes, the usability of LZER0 was limited by configuration management and data distribution, which were based on command line interaction. In addition, each station had to be managed individually. For this reason, we have improved the user interface for managing the cost-effective devices (as single stations or as station networks) and for querying and viewing data in real time. We have also developed an automatic system to manage the initial installation of software and its remote updating. These software improvements will enhance the usability of these systems for end users.

The technical diagrams of the instruments and the developed software are released under the CC BY 4.0 license through the repository of LZER0 on github (https://github.com/OGS-GNSS/LZER0) and the Geosciences IR research infrastructure portal (https://geosciences-ir.it/infrastruttura/).

Acknowledgements

Funded by European Union - NextGenerationEU - Mission 4 “Education and Research” - Component 2 “From Research to Business” - Investment 3.1 “Fund for the realization of an integrated system of research and innovation infrastructures” - Project IR0000037 - GeoSciences IR - CUP I53C22000800006. We thank Lunitek SRL for the collaboration provided in the creation of the instrumentation.

How to cite: Zuliani, D., Compagno, A., Fabris, P., De Giorgi, F., Galvi, S., Magrin, A., Magrin, E., Pastorutti, A., Tunini, L., Ziani, P., and Zorba, S.: LZER0-MOB: cost-effective GNSS for temporary monitoring, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11805, https://doi.org/10.5194/egusphere-egu26-11805, 2026.

Precision agriculture is increasingly using rapid and non-invasive methods to characterise soil properties and monitor field status, with the aim of enabling efficient and sustainable management. Electromagnetic induction (EMI) can be used to rapidly measure the electrical conductivity of the soil and thereby provide information about the soil complexity, water content dynamics, and nutrient availability. The use of Unmanned Aerial Vehicles (UAVs) allows measurements of soil properties on cultivated land and makes the method independent from field conditions.
We developed a lightweight, scalable EMI sensing platform with a fast data acquisition for deployment on hexacopters in the 25 kg class. The system has one transmitter and four receivers with variable coil pair distances of 1.5 m, 1.9 m, 2.3 m, and 2.7 m. The EMI system weighs less than 5 kg and allows a measurement time of approximately 15 minutes with a fully charged 100 Wh battery from a DJI600 UAV. The apparent conductivity values are recorded at a measurement rate of 10 Hz. WLAN communication, MQTT-based protocols, a TimeScale database and a web-based measurement interface enable real-time display of the data.
During the initial test and evaluation phase, EMI measurements are carried out using a UAV at several defined measurement points and at multiple elevation levels across the test field near Jülich, Germany. The goal of the test was to (a) identify the UAVs electromagnetic interference on EMI measurements at different distances from the drone, to (b) assess the feasibility of vertical measurements at different altitudes, to (c) determine reference conductivity values using a commercial EMI system at several positions on the ground, to (d) record corresponding housekeeping data from DGPS and onboard position sensors and to (e) perform a potential offset calibration based on the acquired datasets.

How to cite: Dick, M., Mester, A., Zimmermann, E., Wüestner, P., Ramm, M., Scherer, B., Bernard, J., Dogar, S. S., Montzka, C., Brogi, C., Huisman, J. A., and Natour, G.: Drone Based Field Measurements of a Lightweight Electromagnetic Induction System (SELMA-TF) for Agricultural Applications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12457, https://doi.org/10.5194/egusphere-egu26-12457, 2026.

Optimizing the informational return of measurements along existing road networks is a big challenge for real life data acquisition. Here, informational return describes the effectiveness of a survey in capturing the spatial variability of the target variable, ensuring that measurements provide maximal knowledge and minimize uncertainty when used to generate spatial maps or inform predictive models. In this study we develop a two-stage survey design framework that fuses auxiliary spatial data with road network data and formulates route planning as a combinatorial optimization problem. By integrating a fuzzy-clustered representation of the survey area heterogeneity with the road network, we identify map grid nodes reachable by a vehicle. Information values are assigned to individual road segments using fuzzy membership values and Shannon Entropy. Informative segments are selected, and the most informative pathways between them are constructed using Dijkstra’s Algorithm. An Information-rich initial route is then generated using Ant Colony Optimization (ACO).

To further economize this initial route, spatial coverage is characterized by computing a convex hull in the auxiliary data space. A subset of map grid nodes is heuristically selected to preserve most of the convex hull volume while keeping the computational cost manageable. The shortest paths between road segments covering these nodes are determined with the A* algorithm.  The ACO is applied to construct the final economized route that is both information-rich and distance-optimized.

The framework is evaluated using a large-scale case study based on mobile Cosmic Ray Neutron Sensing (CRNS) soil moisture measurements over a 4500 km² area in northeastern Germany. Compared to an empirically designed route of similar length, the optimized route substantially reduces uncertainty in regression-based soil moisture regionalization (i.e., map generation) while significantly improving spatial coverage of the survey area, data collection efficiency, and data quality. The proposed approach provides a systematic alternative to convenience-based sampling strategies commonly used in Earth and environmental sciences.

How to cite: Topaclioglu, C., Trinkle, L., Anders, J., Landmark, S., Schrön, M., Dietrich, P., and Paasche, H.: A Route Optimization Framework for Vehicle-Based Mobile Remote Sensing , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12703, https://doi.org/10.5194/egusphere-egu26-12703, 2026.

X-ray interferometry holds the potential to image astronomical objects with unprecedented, microarcsecond (μas) resolution, where 1 μas corresponds to 4.8 prad. This target resolution imposes extreme requirements for the accuracy of the spacecraft‘s attitude measurement when operating the X-ray interferometer.

Typically, the orientation of the spacecraft is measured using three single-axis gyroscopes that measure the Euler angles (yaw, pitch and roll) in a spacecraft-fixed coordinate frame. These measurements can be complemented by a star tracker as an absolute reference. Gyroscopes that are capable of determining the orientation with the required accuracy and stability needs to outperform the current high-performance navigation-grade gyroscopes by several orders of magnitude.

High-accuracy rotation angle and rotation rate measurements become increasingly important in many scientific fields: (1) Seismologists want to observe the local rotation from elastic and non-elastic deformation caused by earthquakes to fully observe the seismic wavefield. (2) The next generation of gravitational wave detectors relies on high-precision rotation measurements for enhanced active seismic noise isolation and Newtonian noise mitigation. (3) Geodesists want to measure the Earth’s rotation rate and its variations with Earth-bound instruments. All these applications require gyroscopes with a sensitivity in the range of 1 prad/s/√Hz to 1 nrad/s/√Hz, covering a frequency range from below 0.01 Hz to up to 100 Hz.

This contribution presents (1) a compilation of requirements for a sensor suite to comply with the mission needs, (2) an assessment of the state-of-the-art gyroscope technologies (e.g. fiber-optic gyroscopes, ring-laser gyroscopes, cold atom gyroscopes and mechanical gyroscopes), comprising their scaling parameters as well as technological gaps, and (3) a road map to an ultra-high performance sensor suite for 2030+.

How to cite: Brotzer, A., Bernauer, F., Guattari, F., Jaroszewicz, L. R., Kurzych, A. T., Garrido Alzar, C. L., Landragin, A., Piot, D., and De Raucourt, S.: Ultra-high performance gyroscopes for future X-ray interferometer missions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18427, https://doi.org/10.5194/egusphere-egu26-18427, 2026.

In the framework of the planetary missions, the human exploration of the Martian surface is becoming a priority. The pathway to Mars is rooted through the development of various space missions of increasing complexity, which will lead to a long-term and sustainable human presence on the Moon. The Moon is therefore an intermediate and fundamental step for testing most of the new technologies required for sustainable human exploration of deep space.

We here present an overview of two Italian National projects dedicated to the development of geophysical technologies for planetary exploration, including the “PROgramma di RIcerca Spaziale di base (PRORIS)” project, funded by the Italian Ministry of University and Research (MUR) and whose management has been assigned to the National Research Council of Italy (CNR) and the National Institute for Astrophysics (INAF), and the “Martian Analysis of Resources and Structures: Lava tubes, neAr-surface ice and aquifers Visibility and Assessment (MARS-LAVA)” project, led by CNR and INAF.

The PRORIS project is mainly related to the Moon exploration with different activities for the development of methodologies and research prototypes, and the validation of the developed technologies in terrestrial analog environments. The MARS-LAVA project instead aims at developing, optimizing and testing a suite of geophysical sensors with high potential for Mars exploration, and to develop analysis techniques based on data fusion/integration and modeling, Both the projects involve the use of magnetometric and electromagnetic geophysical methods.

In this contribution,  we dedicate a particular focus to the multiscale analysis of magnetometric data for studying lava tubes, presenting the preliminary results of magnetometric surveys carried out at Italian lava tubes test-sites.

These results underline the potential of the multiscale analysis of magnetometric data in the framework of the planetary exploration and the challenges that need to be overcome.

How to cite: Barone, A., Vitale, A., Accomando, F., Mercogliano, F., Castaldo, R., Solaro, G., Pepe, S., Catapano, I., Cortesi, U., Orosei, R., and Tizzani, P.: Multiscale analysis of geophysical data in the framework of PRORIS and MARS-LAVA projects., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19724, https://doi.org/10.5194/egusphere-egu26-19724, 2026.

The integration of Unmanned Aerial Systems (UAS) into scientific research has established a crucial link between regional-scale satellite observations and high-resolution local-scale measurements. This study illustrates the operational framework and multi-disciplinary capabilities of GAIA iLAB (CNR), a laboratory designed to provide a structured guide for experimental activities in the geo-agro-environmental and geophysical sectors. By utilizing advanced technologies such as UAS, rovers, and in-situ acquisitions, GAIA iLAB addresses complex challenges ranging from precision agriculture to deep geophysical prospecting.

The laboratory manages a diverse UAS fleet, including DJI Matrice 300 RTK and Matrice 600 PRO platforms, which serve as versatile vectors for a wide array of specialized sensors. The research topics covered by GAIA iLAB are structured into four primary pillars of equal scientific priority:

• Geophysics and Near-Surface Sensing: The lab conducts high-resolution magnetic and electromagnetic surveys. Utilizing drone-borne magnetometers (MagArrow) and vertical gradiometers (MagNimbus), the group investigates magnetization contrasts for archaeological research, geological-volcanological studies, and the search for buried structures. This is complemented by a Low-Frequency GPR system (Zond Aero LF) for urban geophysics and sub-surface investigations up to 10 meters deep.
• Geo-Environmental Monitoring: Using LiDAR (DJI Zenmuse L1) and high-resolution RGB cameras, GAIA iLAB performs detailed topographic reconstructions (DSM/DTM) to monitor hydrogeological instability, landslide movements, and seismic-tectonic processes.
• Advanced Agro-Environmental Research: The laboratory employs multispectral (Micasense Red-Edge M) and hyperspectral sensors (Senop HSC-2) to analyze vegetation health, crop water stress, and canopy temperature via thermal radiometric imaging (FLIR Vue Pro 640R).
• Electromagnetic Induction (EMI): Focused on the "Near Surface Zone," the lab utilizes FDEM sensors (CMD Explorer 6L) to characterize soil apparent electrical conductivity (ECa) and resistivity, essential for understanding soil-atmosphere interactions and anthropogenic impacts.

The GAIA iLAB workflow ensures high-quality scientific output through rigorous flight planning (UgCS), strict adherence to EASA/ENAC regulations, and advanced data post-processing using SfM photogrammetry and LiDAR360 analysis. This integrated approach demonstrates the laboratory's potential to provide innovative solutions for environmental management and geophysical exploration.

How to cite: Pepe, S., Buonanno, M., Barone, A., Vitale, A., Accomando, F., Castaldo, R., Iannuzzi, A., Mercogliano, F., Bonfante, A., and Tizzani, P.: Multi-scale and multi-sensor UAS-based approach for Geo-Agro-Environmental and Geophysical applications: the GAIA iLAB experience., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19930, https://doi.org/10.5194/egusphere-egu26-19930, 2026.

Southern Italy is a tectonically active region of major geodynamic significance, where long-lived convergence, post-collisional extension, slab rollback, and crust-mantle decoupling generate strong lateral and vertical heterogeneity in lithology, temperature, fluids, and deformation. Here, we present an integrated 3D Finite Element (FE) thermo-rheological model developed within the TRHAM project activities, aimed at reconstructing the regional thermal and mechanical architecture of the crust within a physically consistent, data-constrained framework. The FE geometry synthesizes a large body of published geological and geophysical constraints, integrating surface geology, regional structural interpretations, and deep wellbore information, complemented by gravity and magnetic evidence. The thermal field is computed under coupled conductive-convective regimes by solving the fully coupled Fourier heat-conduction and Darcy-flow equations in porous media. Boundary conditions include an altitude-dependent surface temperature, prescribed basal heat flow at Moho depth, and laterally adiabatic conditions. Key thermal parameters are calibrated through a bounded optimization strategy against independent thermal observables, while explicitly accounting for resolution limits and non-uniqueness. Rheological calculations combine a frictional failure criterion for brittle deformation and power-law creep for ductile flow, incorporating spatially variable pore-fluid pressure ratios derived from the thermo-hydraulic solution. Strain-rate scenarios are guided by regional geodetic strain-rate constraints and GNSS-informed kinematic parameters. The resulting strength envelopes and yield-stress distributions show strong spatial variations in effective crustal strength and in the depth and geometry of the BDT, both along the Apennine belt and from the Tyrrhenian side to the Adriatic foreland. The model highlights the mechanical impact of inherited crustal architecture and fluid-assisted weakening, and reproduces a systematic contrast between the Apulian foreland and the Apenninic wedge consistent with regional deformation and seismicity patterns. Explicit fluid flow further emphasizes how crustal geometry modulates hydraulic connectivity and hydrological decoupling between Apulian and Apenninic domains, focusing infiltration/discharge and shaping surface heat-flow patterns.

Acknowledgments

The activities are supported by the projects “Relation between 3D Thermo-Rheological Model and Seismic Hazard for Risk Mitigation in the Urban Areas of Southern Italy”, funded under the PRIN2022 PNRR initiative (code: P202299L2C), PRIN2022 PNRR, EU NextGenerationEU.

How to cite: Castaldo, R., Perrini, M., Accomando, F., Tizzani, P., De Landro, G., Gola, G., Fedi, M., Carafa, M. M. C., Kastelic, V., Di Naccio, D., Falcone, G., and Taroni, M.: 3D Thermo-Rheological Modelling of the Southern Apennines (Italy): Insights from the TRHAM Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20018, https://doi.org/10.5194/egusphere-egu26-20018, 2026.

Our regional aeromagnetic study of La Palma Island (Canary Islands), based on conventional airborne data, successfully imaged the island's large-scale magnetic structure. While the magnetic data provided a robust regional framework, they lacked the spatial resolution required to investigate shallow volcanic structures and post-eruptive thermal anomalies following the 2021 eruption. Therefore, a high-resolution, drone-based aeromagnetic survey was conducted over the Tajogaite volcano, targeting the area most affected by the eruption.

The survey was carried out in June 2024 and March 2025 using the DJI Matrice 210 RTK and DJI Matrice 300 RTK with a dual-sensor fluxgate magnetometer system sampling at 200 Hz. Constant-altitude flights covered an area of ~7 km², with N-S-oriented survey lines spaced 30–60 m apart and tie lines spaced 150–200 m in the perpendicular direction. The drone flew in a lawnmower pattern, and we acquired high-altitude calibration flights in low magnetic gradient conditions to quantify and correct the magnetic measurements.

Data curation involved several processing stages, including removing inconsistent flight tracks and compensating for platform-induced noise using the calibration data. The total magnetic intensity map and anomaly were obtained by applying gridding and smoothing to the signal and then removing the IGRF model.

The resulting high-resolution magnetic anomaly map provides critical detail of the shallow magnetic structure of the Tajogaite volcanic edifice, allowing the identification of fault-controlled anomalies, low-susceptibility zones (after the 3D modelling of the data) related to high temperatures, and a potential shallow magma pathway.

Additionally, we acquired new magnetotelluric data along a North-South oriented profile, perpendicular to the inferred still-hot dyke direction. This enabled us to construct a 3D electrical resistivity model that correlates with the magnetic model to further analyse this area, which is likely to be related to the final stage of magma ascension.

This multidisciplinary research emphasises the importance of drone-based surveys in investigating active volcanic environments and post-eruptive dynamics on a local scale.

How to cite: Romero-Toribio, M. C., Martín-Hernández, F., Giménez-Berenguer, C., Piña-Varas, P., Martí, A., Marcuello, A., Queralt, P., and Ledo, J.: Drone-based aeromagnetics combined with magnetotellurics to investigate volcanic structures at the Tajogaite volcano, La Palma Island., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21459, https://doi.org/10.5194/egusphere-egu26-21459, 2026.

Ground Penetrating Radar (GPR) [1-2] is a well-established geophysical technique for high-resolution subsurface investigations and is increasingly integrated with UAV platforms to enable rapid, flexible, and non-invasive surveys [3]. This contribution presents a comparative analysis of two three-dimensional microwave tomography (MWT) approaches for processing UAV-GPR multimonostatic data. The approaches differ for the adopted scattering model: the Interface Reflection Point 3D (IRP3D) model [4-5] and the Equivalent Permittivity 3D (EP3D) model, previously proposed for 2D imaging in [6]. The approaches are compared in terms of spatial resolution by inverting full-wave simulated data referred to a point like scatterer and the effect of data spacing as well as the irregular distribution is examined. Experimental data collected in laboratory-controlled conditions are considered to validate the expected performance. Furthermore, results referred to on field data acquired at the Altopiano di Verteglia (Avellino, Italy), are provided. The reconstruction capabilities are quantitatively assessed through image-based metrics, including image contrast and entropy, highlighting strengths and limitations of each approach. The results provide insights into the suitability of advanced 3D MWT algorithms for UAV-supported GPR surveys and contribute to the development of robust processing workflows for drone-based subsurface imaging.

[1] D. J. Daniels, Ground Penetrating Radar. Hoboken, NJ: Wiley, 2005.

[2] R. Persico, Introduction to Ground Penetrating Radar: Inverse Scattering and Data Processing. Hoboken, NJ: Wiley, 2014.

[3] C. Noviello, G. Gennarelli, G. Esposito, G. Ludeno, G. Fasano, L. Capozzoli, F. Soldovieri, I. Catapano, “An Overview on Down-Looking UAV-Based GPR Systems,” in Remote Sensing, 2022, 14(14):3245. https://doi.org/10.3390/rs14143245.

[4] G. Gennarelli, C. Noviello, G. Ludeno, G. Esposito, F. Soldovieri and I. Catapano, "Three-Dimensional Ray-Based Tomographic Approach for Contactless GPR Imaging," in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-14, 2023, Art no. 2000614, doi: 10.1109/TGRS.2023.3250740.

[5] G. Esposito, G. Gennarelli, F. Soldovieri and I. Catapano, "Effective 3-D Contactless GPR Imaging: Experimental Validation," in IEEE Geoscience and Remote Sensing Letters, vol. 21, pp. 1-5, 2024, Art no. 3509005, doi: 10.1109/LGRS.2024.3451729.

[6] G. Ludeno, L. Capozzoli, E. Rizzo, F. Soldovieri, I. Catapano, “A Microwave Tomography Strategy for Underwater Imaging via Ground Penetrating Radar,” in Remote Sensing, 2018, 10, 1410. https://doi.org/10.3390/rs10091410.

How to cite: Catapano, I., Esposito, G., Ludeno, G., Noviello, C., Soldovieri, F., and Gennarelli, G.: A comparison of 3D MWT Reconstruction Models for UAV-based GPR, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10503, https://doi.org/10.5194/egusphere-egu26-10503, 2026.

Low-cost seismic instruments, such as Raspberry Shake sensors, are increasingly deployed to complement traditional seismic networks and enable applications ranging from network densification and education to low-cost forensic seismology monitoring and local early warning; however, systematic performance comparisons with broadband stations remain essential.

The Cadí station, part of the CA Catalan network and operated by LEGEF-IEC, is located in the eastern Pyrenees, a region of moderate seismicity that is of particular relevance for seismic hazard assessment and emergency planning in Catalonia. CADI is installed inside an abandoned tunnel that provides stable thermal conditions and protection from atmospheric effects; despite this isolation, the site exhibits medium-to-low ambient noise levels due to the presence of nearby transportation infrastructure. In general this emplacement provides favorable conditions for instrument comparison.

In this study, we assess the data quality and detection capabilities of a Raspberry Shake RS3D short-period sensor through a direct comparison with broadband instrumentation (Guralp CMG3T and Centaur digitizer) at the CADI site. Before the comparison period, only the low-cost sensor was active due to broadband maintenance; afterward, both instruments ran together, allowing direct comparison and validation of the prior CADI recordings

Continuous seismic data recorded between September 2024 and April 2025 were analyzed and compared using cumulative Power Spectral Density (PSD) spectra and Root Mean Square (RMS) amplitude estimates, using part of the SeismoRMS free software (Lecocq et al., 2020). Broadband data were compared with Raspberry Shake recordings during their overlapping operational period to assess noise levels, frequency response, and sensitivity across relevant seismic bands. PSDs were evaluated relative to the New Low and High Noise Models to characterize baseline performance.

Results show that both instruments exhibit comparable spectral behavior above 0.1 Hz, capturing similar noise patterns and anthropogenic signals in the high-frequency band (10–40 Hz). However, the broadband sensor demonstrates superior performance at lower frequencies, reliably recording signals below the narrowband instrument’s response range.

This difference becomes critical for the detection of teleseismic events, which are only clearly recorded by the broadband station, while both sensors adequately capture local and regional earthquakes. These findings highlight the strengths and limitations of low-cost seismic instrumentation and confirm that Raspberry Shake sensors can effectively complement broadband networks for local and regional monitoring, while broadband stations remain essential for comprehensive seismic observations.

Reference

Lecocq, T., Massin, F., Satriano, C., Vanstone, M., & Megies, T. (2020). SeismoRMS - A simple python/jupyter notebook package for studying seismic noise changes (1.0). Zenodo. https://doi.org/10.5281/zenodo.3820046

How to cite: Ladero, J., Tapia, M., and Suriñach, E.: Performance of a Broadband Seismic Station Versus a Co-located Raspberry Shake: Implications for Low-Cost Seismic Monitoring , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13189, https://doi.org/10.5194/egusphere-egu26-13189, 2026.

How to cite: Restelli, F., Lindsey, J., Kerkenyakova, A., Calver, J., Kitka, K., Watkiss, N., and Hill, P.: The Güralp Stratis: A Commercial Six-Degree-of-Freedom Seismometer for Ground Motion and Structural Monitoring , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17894, https://doi.org/10.5194/egusphere-egu26-17894, 2026.