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.
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.
Grain size composition of loess samples from LGM European loess sequences. Loess samples of about 200 g were prepared to extract the grain size fractions studied. Grain size separations were performed on at least 10 g of dry sample. First, the entire sample was sieved with demineralized water on 63 microns and 20 microns sieves. The rejects were collected, dried and weighed. The clay fraction was obtained by decanting the fraction below 20 microns. The rest of the sample was mixed and left to settle for 1 hour. This procedure is repeated until a transparent supernatant is obtained. The two fractions thus obtained are dried and weighed. The size of the different fractions was then checked by laser granulometry.
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 digital terrain model of waterways for the estuary of river Elbe (DGM-W 2022) in high resolution based on airborne laser scanning and echo sounder data is produced and published by the German Federal Waterways and Shipping Administration (Wasserstraßen- und Schifffahrtsverwaltung des Bundes, WSV). The data includes the Outer Elbe and the tidally influenced tributaries and branches of the Elbe estuary upstream to the town Geesthacht. The data is available in a raster resolution of 1 meter. Coordinate reference system: EPSG 25852, ETRS89 / UTM Zone 32N Elevation reference system: DHHN2016, NHN Survey methods: Airborne laser scanning (ALS) 02.04.2022 - 19.04.2022 Multibeam echo sounder, single beam echo sounder 09.02.2017 - 09.04.2023 It is strongly recommended to use the data source map for quality assessment.
Untersuchung der Restabwasser-Klaerschlaemme, insbesondere der Zellstoff-, Papier- und Pappenindustrie; Entwicklung der Technologien zur Gewinnung und Verarbeitung; neue Verwendungsgebiete in der Holzspanwerkstoff- und Kunststoffindustrie; Restabwasserklaerschlammuntersuchung; Untersuchung auf Zusammensetzung; Untersuchung der Verwertungsmoeglichkeit; Beratung zur Gewinnung; Beratung zur Verwertung; Entwicklung der Technologien; Planung von Anlagen; Brandschutz von Holzspanplatten; Brandschutzfasern aus Abwasserschlamm.
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.
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