This dataset documents a series of analogue experiments designed to investigate the coupled evolution of magma-driven surface uplift and rainfall-driven geomorphic processes. Seven controlled laboratory experiments were conducted, each combining shallow intrusion of a magma analogue with imposed rainfall of varying intensity, in order to systematically explore the role of surface processes under different forcing conditions. The experimental setup consists of a rigid Plexiglas container filled with a water-saturated granular mixture formulated to reproduce brittle crustal behaviour under wet conditions. Magmatic intrusion was simulated by injecting a fixed volume (360 cm³) of low-viscosity polyglycerine through a basal inlet at three distinct injection rates, while surface processes were imposed using an overhead rainfall system delivering three different rainfall intensities. Topographic evolution during each experiment was monitored using a structured-light laser scanner (Artec Leo). For every model run, six Digital Elevation Models (DEMs) were generated at synchronised stages corresponding to 0%, 20%, 40%, 60%, 80% and 100% of the injected volume, yielding a total of 42 DEMs. Raw scans were processed through a triangulated irregular network (TIN) meshing workflow and subsequently rasterised to GeoTIFF format without additional post-processing, in order to preserve the original topographic signal. In parallel, time-lapse photographic documentation was acquired throughout each experiment using a digital camera, providing a complementary visual record of dome growth, surface incision and sediment redistribution. The dataset is organised into two main components: (i) high-resolution topographic datasets (DEMs) and (ii) time-indexed photographic sequences, both linked to the temporal evolution of each experiment. Quality control procedures include scanner calibration prior to acquisition, verification of mesh consistency and raster resolution, and a closed-system experimental design ensuring mass conservation. All data are distributed in their original formats and accompanied by detailed documentation describing experimental procedures, data processing workflows, and file organisation, enabling reproducibility and reuse in quantitative analyses of coupled magmatic and surface processes. This publication results from work conducted under the transnational access/national open access action at University Roma Tre, Laboratory of Experimental Tectonics (LET) supported by WP3 ILGE - MEET project, PNRR - EU Next Generation Europe program, MUR grant number D53C22001400005.
With the introduction of mobile mapping technologies, geomonitoring has become increasingly efficient and automated. The integration of Simultaneous Localization and Mapping (SLAM) and robotics has effectively addressed the challenges posed by many mapping or monitoring technologies, such as GNSS and unmanned aerial vehicles, which fail to work in underground environments. However, the complexity of underground environments, the high cost of research in this area, and the limited availability of experimental sites have hindered the progress of relevant research in the field of SLAM-based underground geomonitoring. In response, we present SubSurfaceGeoRobo, a dataset specifically focused on underground environments with unique characteristics of subsurface settings, such as extremely narrow passages, high humidity, standing water, reflective surfaces, uneven illumination, dusty conditions, complex geometry, and texture less areas. This aims to provide researchers with a free platform to develop, test, and train their methods, ultimately promoting the advancement of SLAM, navigation, and SLAM-based geomonitoring in underground environments. SubSurfaceGeoRobo was collected in September 2024 in the Freiberg silver mine in Germany using an unmanned ground vehicle equipped with a multi-sensor system, including radars, 3D LiDAR, depth and RGB cameras, IMU, and 2D laser scanners. Data from all sensors are stored as bag files, allowing researchers to replay the collected data and export it into the desired format according to their needs. To ensure the accuracy and usability of the dataset, as well as the effective fusion of sensors, all sensors have been jointly calibrated. The calibration methods and results are included as part of this dataset. Finally, a 3D point cloud ground truth with an accuracy of less than 2 mm, captured using a RIEGL scanner, is provided as a reference standard.
The GBL (INSPIRE) represents mechanically drilled boreholes approved by the State Geological Surveys of Germany (SGS). Most of the drilling data were not collected by the SGS, but were transmitted to SGS by third parties in accordance with legal requirements. Therefore, the SGS can accept no responsibility for the accuracy of the information. According to the Data Specification on Geology (D2.8.II.4_v3.0) the boreholes of each federal state are stored in one INSPIRE-compliant GML file. The GML file together with a Readme.txt file is provided in ZIP format (e.g. GBL-INSPIRE_Lower_Saxony.zip). The Readme.txt file (German/English) contains detailed information on the GML file content. Data transformation was proceeded by using the INSPIRE Solution Pack for FME according to the INSPIRE requirements.
The GBL (INSPIRE) represents mechanically drilled boreholes approved by the State Geological Surveys of Germany (SGS). Most of the drilling data were not collected by the SGS, but were transmitted to SGS by third parties in accordance with legal requirements. Therefore, the SGS can accept no responsibility for the accuracy of the information. According to the Data Specification on Geology (D2.8.II.4_v3.0) the boreholes of each federal state are stored in one INSPIRE-compliant GML file. The GML file together with a Readme.txt file is provided in ZIP format (e.g. GBL-INSPIRE_Lower_Saxony.zip). The Readme.txt file (German/English) contains detailed information on the GML file content. Data transformation was proceeded by using the INSPIRE Solution Pack for FME according to the INSPIRE requirements.
DGM1 - Laserscan-Geländemodell Im Frühjahr 2016 fand eine Airborne-Laserscan-Befliegung zur Generierung eines neuen hochgenauen Geländemodells für das gesamte Saarland statt. Dabei wurde die Geländeoberfläche mit einem im Flugzeug installierten Laser abgetastet. Als Resultat liegt seit Anfang des Jahres 2017 das hochgenaue DGM1 mit einer Rasterweite von 1m und einer durchschnittlichen Höhengenauigkeit von 1-2 dm vor. Als gewünschter Nebeneffekt wurden neben Geländedaten auch auf der Erdoberfläche befindliche Objekte wie Gebäude und Vegetation mit eingescannt, die als Oberflächendaten verfügbar sind. Digitale Geländemodelle (DGM) sind digitale, numerische, auf ein regelmäßiges Gitter reduzierte Modelle der Geländehöhen und –formen der Erdoberfläche. DGM können außerdem ergänzende Angaben (z.B. Geländekanten, Geripplinien, markante Geländepunkte) enthalten. Sie beinhalten keine Information über Bauwerke (z.B. Brücken) und Vegetation. Das DGM1 unterscheidet sich von den anderen DGM durch seine Höhengenauigkeit und seine Gitterweite.
The high-resolution digital surface model (DSM1, DOM1) of the watercourses Elbe and Lower Havel is based on the airborne laser scanning data, undertaken from 06 January 2022 to 18 March 2022 in the Elbe area and from 20 to 22 December 2021 in the Havel area. It was produced and published by Germany’s Federal Institute of Hydrology (BfG), on behalf of the River Basin Community Elbe (RBC Elbe, FGG Elbe). The work was supported by the German Federal Waterways and Shipping Administration (WSV) and the surveying offices and water management administrations of six German states - Saxony, Saxony-Anhalt, Brandenburg, Lower Saxony, Mecklenburg-Vorpommern and Schleswig-Holstein. The data cover both the area around the inland water stretches of the Elbe from the Czech-German border to the village of Zollenspieker (part of the city of Hamburg) and the Lower Havel waterway from the town of Rathenow to its confluence with the Elbe. Since the dataset has a large coverage of 4,043 km², it is split into 62 sections. They were either labelled *HW in case of flood relevant areas (in German: “hochwasser-relevante Gebiete”) or *AU in case of historical floodplains (in German: “Altauengebiete”). Financing was divided according to these categories: In the HW areas, the project was co-funded by BfG, the WSV and the federal states, while in the AU areas, BfG covered all project costs. For each section we provide hillshade (*HS) and height maps (*NHN). The data are available in a raster resolution of 1 meter in GeoTiff format; Coordinate reference frame: ETRS89.DREF91.R16; Coordinate projection: UTM Zone 33N; EPSG-Code: 25833; Height reference system: DHHN2016, national vertical reference frame in Germany (2022). For further information please contact us. Citation short: BfG et al. / i.A. FGG Elbe (2025)
This dataset contains geochemical variables measured in six depth profiles from ombrotrophic peatlands in North and Central Europe. Peat cores were taken during the spring and summer of 2022 from Amtsvenn (AV1), Germany; Drebbersches Moor (DM1), Germany; Fochteloër Veen (FV1), the Netherlands; Bagno Kusowo (KR1), Poland; Pichlmaier Moor (PI1), Austria and Pürgschachen Moor (PM1), Austria. The cores AV1, DM1 and KR1 were taken using a Wardenaar sampler (Royal Eijkelkamp, Giesbeek, the Netherlands) and had diameter of 10 cm. The cores FV1, PM1 and PI1 had an 8 cm diameter and were obtained using an Instorf sampler (Royal Eijkelkamp, Giesbeek, the Netherlands). The cores FV1, DM1 and KR1 were 100 cm, core AV1 was 95 cm, core PI1 was 85 cm and core PM1 was 200 cm. The cores were subsampeled in 1 cm (AV1, DM1, KR1, FV1) and 2 cm (PI1, PM1) sections. The subsamples were milled after freeze drying in a ballmill using tungen carbide accesoires. X-Ray Fluorescence (WD-XRF; ZSX Primus II, Rigaku, Tokyo, Japan) was used to determine Al (μg g-1), As (μg g-1), Ba (μg g-1), Br (μg g-1), Ca (g g-1), Cl (μg g-1), Cr (μg g-1), Cu (μg g-1), Fe (g g-1), K (g g-1), Mg (μg g-1), Mn (μg g-1), Na (μg g-1), P (μg g-1), Pb (μg g-1), Rb (μg g-1), S (μg g-1), Si (μg g-1), Sr (μg g-1), Ti (μg g-1) and Zn (μg g-1). These data were processed and calibrated using the iloekxrf package (Teickner & Knorr, 2024) in R. C, N and their stable isotopes were determined using an elemental analyser linked to an isotope ratio mass spectrometer (EA-3000, Eurovector, Pavia, Italy & Nu Horizon, Nu Instruments, Wrexham, UK). C and N were given in units g g-1 and stable isotopes were given as δ13C and δ15N for stable isotopes of C and N, respectively. Raw data C, N and stable isotope data were calibrated with certified standard and blank effects were corrected with the ilokeirms package (Teickner & Knorr, 2024). Using Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) (Agilent Cary 670 FTIR spectromter, Agilent Technologies, Santa Clara, Ca, USA) humification indices (HI) were determined. Spectra were recorded from 600 cm-1 to 4000 cm-1 with a resolution of 2 cm-1 and baselines corrected with the ir package (Teickner, 2025) to estimate relative peack heights. The HI (no unit) for each sample was calculated by taking the ratio of intensities at 1630 cm-1 to the intensities at 1090 cm-1. Bulk densities (g cm-3) were estimated from FT-MIR data (Teickner et al., in preparation).
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