Swath sonar bathymetry data used for that dataset was recorded during RV MARIA S. MERIAN cruise MSM62/2 using Kongsberg EM1002 multibeam echosounder. The cruise took place between 23.03.2017 and 27.03.2017 in the Baltic Sea. The cruise aimed to investigate the impact of the Littorina transgression on the inflow of saline waters into the western Baltic and assessed the potential for future diminution of ventilation in the central and northern deeper basins due to isostatic uplift [CSR]. CI Citation: Paul Wintersteller (seafloor-imaging@marum.de) as responsible party for bathymetry raw data ingest and approval. During the MSM62/2 cruise, the moonpooled KONGSBERG EM1002 multibeam echosounder (MBES) was utilized to perform bathymetric mapping in shallow depths. The echosounder has a curved transducer in which 111 beams are formed for each ping while the seafloor is detected using amplitude and phase information for each beam sounding. For further information on the system, consult https://www.km.kongsberg.com/. Postprocessing and products were conducted by the Seafloor-Imaging & Mapping group of MARUM/FB5, responsible person Paul Wintersteller (seafloor-imaging@marum.de). The open source software MB-System (Caress, D. W., and D. N. Chayes, MB-System: Mapping the Seafloor, https://www.mbari.org/products/research-software/mb-system, 2017) was utilized for this purpose. A sound velocity correction profile was applied to the MSM62/2 data; there were no further corrections for roll, pitch and heave applied during postprocessing. A tide correction was applied, based on the Oregon State University (OSU) tidal prediction software (OTPS) that is retrievable through MB-System. CTD measurements during the cruise were sufficient to represent the changes in the sound velocity throughout the study area. Using Mbeditviz, artefacts were cleaned manually. NetCDF (GMT) grids of the edited data as well as statistics were created with mbgrid. The published bathymetric EM1002 grid of the cruise MSM62/2 has a resolution of 15 m. No total propagated uncertainty (TPU) has been calculated to gather vertical or horizontal accuracy. A higher resolution is, at least partly, achievable. The grid extended with _num represents a raster dataset with the statistical number of beams/depths taken into account to create the depth of the cell. The extended _sd -grid contains the standard deviation for each cell. The DTMs projections are given in Geographic coordinate system Lat/Lon; Geodetic Datum: WGS84.
Swath sonar bathymetry data used for that dataset was recorded during RV MARIA S. MERIAN cruise MSM52 using Kongsberg EM1002 multibeam echosounder. The cruise took place between 01.03.2016 and 28.03.2016 in the Baltic Sea. The cruise aimed gapless imagining of the major pre-alpine tectonic lineaments due to the fact that the Glückstadt Graben and the Avalonia-Baltica suture zone run across the southern Baltic [DOI: 10.2312/cr_msm52]. CI Citation: Paul Wintersteller (seafloor-imaging@marum.de) as responsible party for bathymetry raw data ingest and approval. During the MSM52 cruise, the moonpooled KONGSBERG EM1002 multibeam echosounder (MBES) was utilized to perform bathymetric mapping in shallow depths. It has a curved transducer of which 111 beams are formed for each ping while the seafloor is detected using amplitude and phase information for each beam sounding. For further information on the system, consult https://www.km.kongsberg.com/. Generally, the system was acquiring data throughout the entire cruise. Responsible person during this cruise / PI: Laura Frahm. Postprocessing and products were conducted by the Seafloor-Imaging & Mapping group of MARUM/FB5, responsible person Paul Wintersteller (seafloor-imaging@marum.de). The open source software MB-System (Caress, D. W., and D. N. Chayes, MB-System: Mapping the Seafloor, https://www.mbari.org/products/research-software/mb-system, 2017) was utilized for this purpose. A sound velocity correction profile was applied to the MSM52 data; there were no further corrections for roll, pitch and heave applied during postprocessing. A tide correction was applied, based on the Oregon State University (OSU) tidal prediction software (OTPS) that is retrievable through MB-System. CTD measurements during the cruise were sufficient to represent the changes in the sound velocity throughout the study area. Using Mbeditviz, artefacts were cleaned manually. NetCDF (GMT) grids of the edited data as well as statistics were created with mbgrid. The published bathymetric EM1002 grid of the cruise MSM52 has a resolution of 35 m. No total propagated uncertainty (TPU) has been calculated to gather vertical or horizontal accuracy. A higher resolution is, at least partly, achievable. The grid extended with _num represents a raster dataset with the statistical number of beams/depths taken into account to create the depth of the cell. The extended _sd -grid contains the standard deviation for each cell. The DTMs projections are given in Geographic coordinate system Lat/Lon; Geodetic Datum: WGS84.
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 Moderate Resolution Imaging Spectroradiometer (MODIS) is a key instrument aboard the Terra (EOS AM-1) and Aqua (EOS PM-1) satellites. The MODIS-EU image mosaic is a seamless true color composite of all Terra and Acqua passes received at DLR during a single day. Daily and Near Real Time (NRT) products are available. For the composite, MODIS channels 1, 4, 3 are used. The channels are re-projected, radiometrically enhanced, and seamlessly stitched to obtain a visually appealing result. Terra passes from north to south across the equator in the morning, while Aqua passes the equator south to north in the afternoon. Both MODIS instruments are viewing the entire Earth surface every 1 to 2 days, acquiring data in 36 spectral bands.
Grids of anomalies of monthly DWD drought index derived from GPCC data on a 1x1 degree (reference period 1961-1990), provided by WMO RA VI Regional Climate Centre (RCC) on Climate Monitoring WMO-RA6-RCC-CM
This product is based on Vaisala RS92 radiosonde measurements of temperature, humidity, wind and pressure that have been processed following the requirements of the GCOS Reference Upper Air Network (GRUAN) that were described in Immler et al. [2010]. The GRUAN data product file comply to the requirements of GRUAN in particular by providing a full uncertainty analysis. The uncertainty is calculated according to the recommendations of the “Guide for expressing uncertainty in measurement” [GUM2008]. The total uncertainty is assessed from estimates of the calibration uncertainty, the uncertainty of corrections and statistical standard deviations. Corrections are applied such that the data is bias free according to current knowledge.
The ISND81 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IS): Surface/sea level T1T2A1 (ISN): Synoptic observations from fixed land stations at non-standard time (i.e. 01, 02, 04, 05, ... UTC) A2 (D): 90°E - 0° northern hemisphere (Remarks from Volume-C: NATIONAL AUTOMATIC SYNOP)
The ISND88 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IS): Surface/sea level T1T2A1 (ISN): Synoptic observations from fixed land stations at non-standard time (i.e. 01, 02, 04, 05, ... UTC) A2 (D): 90°E - 0° northern hemisphere (Remarks from Volume-C: NATIONAL AUTOMATIC SYNOP)
The ISAH02 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IS): Surface/sea level T1T2A1 (ISA): Routinely scheduled observations for distribution from automatic (fixed or mobile) land stations (e.g. 0000, 0100, … or 0220, 0240, 0300, …, or 0715, 0745, ... UTC) A2 (H): 90°E - 0° tropical belt(The bulletin collects reports from stations: HKGR;) (Remarks from Volume-C: XXX)
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