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Waterbase - Biology, 2024

Waterbase serves as the EEA’s central database for managing and disseminating data regarding the status and quality of Europe's rivers, lakes, groundwater bodies, transitional, coastal, and marine waters. It also includes information on the quantity of Europe’s water resources and the emissions from point and diffuse sources of pollution into surface waters. Specifically, Waterbase - Biology focuses on biology data from rivers, lakes, transitional and coastal waters collected annually through the Water Information System for Europe (WISE) – State of Environment (SoE) reporting framework. The data are expected to be collected within monitoring programs defined under the Water Framework Directive (WFD) and used in the classification of the ecological status or potential of rivers, lakes, transitional and coastal water bodies. These datasets provide harmonised, quality-assured biological monitoring data reported by EEA member and cooperating countries, as Ecological Quality Ratios (EQRs) from all surface water categories (rivers, lakes, transitional and coastal waters).

Industrial Emissions Directive 2010/75/EU and European Pollutant Release and Transfer Register Regulation (EC) No 166/2006 - ver. 15.0 Dec. 2025 (Tabular data)

This metadata refers to the geospatial dataset representing the status of the EEA Industrial Reporting database as of 15 December 2025 (version 15). The release and emissions data cover the period 2007-2024 as result of the data reported under the E-PRTR facilities, 2017-2024 for IED installations and WI/co-WIs, and 2016-2024 for LCPs. These data are reported to EEA under Industrial Emissions Directive (IED) 2010/75/EU Commission Implementing Decision 2018/1135 and the European Pollutant Release and Transfer Register (E-PRTR) Regulation (EC) No 166/2006 Commission Implementing Decision 2019/1741. The dataset brings together data formerly reported separately under E-PRTR Regulation Art.7 and under IED Art.72. Additional reporting requirements under the IED are also included.

Pictorial information (Binary coded) - Radar data Flechtdorf

High resolution radar data (lmax) of Flechtdorf

Project OTC-Genomics: Environmental and microbial time series data from the Warnow estuary and the Baltic Sea coast

Estuaries and coasts are characterized by ecological dynamics that bridge the boundary between habitats, such as fresh and marine water bodies or the open sea and the land. Because of this, these ecosystems harbor ecosystem functions that shaped human history. At the same time, they display distinct dynamics on large and small temporal and spatial scales, impeding their study. Within the framework of the OTC-Genomics project, we compiled a data set describing the community composition as well as abiotic state of an estuary and the coastal region close to it with unprecedented spatio-temporal resolution. We sampled fifteen locations in a weekly to twice weekly rhythm for a year across the Warnow river estuary and the Baltic Sea coast. From those samples, we measured temperature, salinity, and the concentrations of Chlorophyll a, phosphate, nitrate, and nitrite (physico-chemical data); we sequenced the 16S and 18S rRNA gene to explore taxonomic community composition (sequencing data and bioinformatic processing workflow); we quantified cell abundances via flow cytometry (flow cytometry data); and we measured organic trace substances in the water (organic pollutants data). Processed data products are further available on figshare.

SubSurfaceGeoRobo: A Comprehensive Underground Dataset for SLAM-based Geomonitoring with Sensor Calibration

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.

Datenraum für das Nachhaltigkeitsmonitoring der Wald- und Holzwirtschaft, Teilvorhaben: Bereitstellung von Maschinendaten sowie die Umsetzung eines maschinenspezifischen grünen digitalen Zwilling

Watershed Boundaries of Global Runoff Data Centre Stations

The Watershed Boundaries of all GRDC Stations are generated on the basis of HydroSHEDS (Lehner et al., 2008) and the Multi-Error-Removed Improved-Terrain (MERIT) Hydro dataset (Yamazaki et al., 2019). It is updated as soon as changes in the metadata occur or new stations have to be implemented. The dataset is licensed under CC-BY-4.0. Source: Lehner, B., Verdin, K., and Jarvis, A.: New Global Hydrography Derived From Spaceborne Elevation Data, EOS, 89, 93-94, https://doi.org/10.1029/2008EO100001, 2008. Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H., and Pavelsky, T. M.: MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset, Water Resources Research, 55, 5053-5073, https://doi.org/10.1029/2019WR024873, 2019. The Watershed Boundaries of all GRDC Stations are generated on the basis of HydroSHEDS (Lehner et al., 2008) and the Multi-Error-Removed Improved-Terrain (MERIT) Hydro dataset (Yamazaki et al., 2019). It is updated as soon as changes in the metadata occur or new stations have to be implemented. The dataset is licensed under CC-BY-4.0. Source: Lehner, B., Verdin, K., and Jarvis, A.: New Global Hydrography Derived From Spaceborne Elevation Data, EOS, 89, 93-94, https://doi.org/10.1029/2008EO100001, 2008. Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H., and Pavelsky, T. M.: MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset, Water Resources Research, 55, 5053-5073, https://doi.org/10.1029/2019WR024873, 2019.

Spatial distribution of fine-grained floodplain deposits and anthropogenic materials based on official borehole data in the floodplain of Leipzig, Germany

This data set contains data representing the thickness and spatial distribution of fine-grained floodplain deposits and anthropogenic material in the Leipzig floodplain area. It includes four raster layers (.tif format): one showing the interpolated distribution of the top level of fluvial gravel deposits in the floodplain and one showing the top level of fluvial gravels. The third raster layer presents the thickness of fine-grained floodplain deposits. Additionally, the stratigraphic data was used to spatially model the distribution of thickness of the anthropogenic material in the research area. A shapefile is provided, containing processed data from 3,414 drillings used to develop the spatial model. The data set originates from drilling records provided by the Saxon State Office for Environment, Agriculture, and Geology (LfULG) which were filtered and categorized by their stratigraphical characteristics. Further information on methodological details is described in Graubner and Schmidt (2024) - Data in Brief.

Member States' use of revenues from the auctioning of EU ETS allowances, 2020-2024

This metadata overs the dataset containing information on how EU Member States spend the revenues from auctioning EU ETS emission allowances in one calendar year. More information on the EU Emissions Trading System (EU ETS) can be found here. The revenues from the auctioning of these allowances represent an increasing income source for Member States. This data is being collected under Article 19 of the Governance Regulation. The Regulation’s aim is to help the EU reach its 2030 climate and energy targets by setting common rules for planning, reporting and monitoring. The Regulation also ensures that EU planning and reporting are synchronised with the ambition cycles under the Paris Agreement. Reporting is mandatory for EU Member States. Some information is only mandatory to report if the data is available.

In situ high spectral resolution inherent and apparent optical property data from diverse aquatic environments

Light emerging from natural water bodies and measured by remote sensing radiometers contains information about the local type and concentrations of phytoplankton, non-algal particles and colored dissolved organic matter in the underlying waters. An increase in spectral resolution in forthcoming satellite and airborne remote sensing missions is expected to lead to new or improved capabilities to characterize aquatic ecosystems. Such upcoming missions include NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Mission; the NASA Surface Biology and Geology observable mission; and NASA Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) - Next Generation airborne missions. In anticipation of these missions, we present an organized dataset of geographically diverse, quality-controlled, high spectral resolution inherent and apparent optical property (IOP/AOP) aquatic data. The data are intended to be of use to increase our understanding of aquatic optical properties, to develop aquatic remote sensing data product algorithms, and to perform calibration and validation activities for forthcoming aquatic-focused imaging spectrometry missions. The dataset is comprised of contributions from several investigators and investigating teams collected over a range of geographic areas and water types, including inland waters, estuaries and oceans. Specific in situ measurements include coefficients describing particulate absorption, particulate attenuation, non-algal particulate absorption, colored dissolved organic matter absorption, phytoplankton absorption, total absorption, total attenuation, particulate backscattering, and total backscattering, as well as remote sensing reflectance, and irradiance reflectance.

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