API src

Found 898 results.

Related terms

Floods Reference Spatial Datasets reported under Floods Directive - version 3.0, Mar. 2025

The Floods Directive (FD) was adopted in 2007 (https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex:32007L0060). The purpose of the FD is to establish a framework for the assessment and management of flood risks, aiming at the reduction of the adverse consequences for human health, the environment, cultural heritage and economic activity associated with floods in the European Union. ‘Flood’ means the temporary covering by water of land not normally covered by water. This shall include floods from rivers, mountain torrents, Mediterranean ephemeral water courses, and floods from the sea in coastal areas, and may exclude floods from sewerage systems. This reference spatial dataset, reported under the Floods Directive, includes the areas of potential significant flood risk (APSFR), as they were lastly reported by the Member States to the European Commission, and the Units of Management (UoM).

Climate related hazards

This series refers to datasets related to the potential occurrence of a climate-induced physical event or trend that may cause loss of life, injury, or other health impacts, as well as damage and loss to property, infrastructure, livelihoods, service provision, ecosystems and environmental resources. It includes datasets on flooding, drought, urban heat island and heatwaves, extreme temperatures and precipitations, fire danger as well as climate suitability for vectors of infectious diseases. The datasets are part of the European Climate Adaptation Platform (Climate-ADAPT) accessible here: https://climate-adapt.eea.europa.eu/

GISCO - Nomenclature of Territorial Units for Statistics 2021 (NUTS 2021), May 2021

The 'GISCO NUTS 2021' data set represents the NUTS 2021 regulation and statistical regions by means of multipart polygon, polyline and point topology. The NUTS geographical information is completed by attribute tables and a set of cartographic help lines to better visualize multipart polygonal regions. The NUTS nomenclature is a hierarchical classification of statistical regions defined by Eurostat. The NUTS classification subdivides the EU economic territory into 3 statistical levels. The NUTS 2021 classification has been established through the Commission Delegated Regulation 2019/1755, which entered into force on 8th August 2019 and applies from 1st January 2021. A non official NUTS-like classification has been defined for the EFTA countries and the candidate countries. At present, six scale ranges (100K, 1M, 3M, 10M and 20M, 60M) are maintained in the GISCO geodatabase. The polygon and boundary classes delineate the regions, while the points provide an anchor for each region. Associated tables contain basic information such as the name of the region. The public data set will be available at 1M, 3M, 10M, 20M, 60M, while the full data set at 100K is restricted. The data set covers EU Member States, EFTA countries, EU candidate countries and the UK. Following the departure of the UK from the European Union, the UK is no longer flagged as an EU Member State but retains its place in the NUTS and statistical regions data set. This dataset (NUTS_2021) is derived from the EuroBoundary Map 2020 (EBM2020) from Eurogeographics as well as GISCO NUTS 2016 (from Türkiye). The list of NUTS2021 codes including changes with respect to NUTS2016 is available on https://ec.europa.eu/eurostat/documents/345175/629341/NUTS2021.xlsx. The public metadata for NUTS 2021 released by Eurostat is available here: https://gisco-services.ec.europa.eu/distribution/v2/nuts/nuts-2021-metadata.xml. This revision (May 2021) includes minor changes in the dataset such as (see https://gisco-services.ec.europa.eu/distribution/v2/nuts/nuts-2021-release-notes.txt): * 2020-10-05 Point snapping is disabled in all datasets, number of decimals increased for 01M datasets. * 2020-11-18 Inclusion of Jan Mayen and Svalbard in to Norways Statistical Regions. Amendment to Serbia NUTS BN line status. * 2020-12-05 Fixed broken utf-8 encoding. * 2021-03-15 Added LAU 2011,2012,2013,2014,2015,2020 * 2021-04-26 Fixed country labels 2001, 2006 (incorrect Kosovo coordinates) IMPORTANT NOTE: Additional information, including the conditions of use and acknowledgement notice is included in the document provided with the dataset "GISCO NUTS 2021 Additional Information.pdf". Public access to this data set is restricted due to intellectual property rights. It shall only be used internally by the EEA, its ETCs and subcontractors working on behalf of the EEA. This metadata has been slightly adapted from the original metadata information provided by Eurostat (European Commission) and is to be used only for internal EEA purposes. An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview.

Model Output Statistics for TALLINN-HARKU (26038)

DWD’s fully automatic MOSMIX product optimizes and interprets the forecast calculations of the NWP models ICON (DWD) and IFS (ECMWF), combines these and calculates statistically optimized weather forecasts in terms of point forecasts (PFCs). Thus, statistically corrected, updated forecasts for the next ten days are calculated for about 5400 locations around the world. Most forecasting locations are spread over Germany and Europe. MOSMIX forecasts (PFCs) include nearly all common meteorological parameters measured by weather stations. For further information please refer to: [in German: https://www.dwd.de/DE/leistungen/met_verfahren_mosmix/met_verfahren_mosmix.html ] [in English: https://www.dwd.de/EN/ourservices/met_application_mosmix/met_application_mosmix.html ]

Schwerpunktprogramm (SPP) 527: Bereich Infrastruktur - International Ocean Discovery Program, Teilprojekt: Die Beziehung von Makrobenthos-Diversität in der Tiefsee und globalem Wandel - bathyale Atelostomata als Modell-Organismen

Die Tiefsee ist das größte Ökosystem auf der Erde, das uns aufgrund der Unerreichbarkeit und immensen Ausdehnung in weiten Teilen noch fremd ist. Wegen der geringen Verbreitung von Tiefsee-Sedimenten auf dem Festland und dem Mangel einer kontinuierlichen Fossil-Überlieferung ist unsere Kenntnis über Tiefseepaläobiogeographie und Tiefsee-Evolution ebenfalls recht limitiert. Eine Sichtung unterkretazischer bis obermiozäner Sedimente in ODP/DSDP/IODP-Bohrkernen (Paläoablagerungstiefe: tiefes Bathyal über 2000 m) erbrachte überraschende Ergebnisse: Sklerite von Echinodermata (Holothurien, Ophiuren, Asteroideen, Crinoiden), die heute einen wichtigen Anteil der Tiefseefaunafauna stellen, fehlen nahezu völlig. Dafür sind Stacheln von irregulären Echiniden (Holasteroida, Spatangoida: Atelostomata) häufig. Da die Stacheln morphologisch sehr variabel sind, bergen Klassifizierung der morphologischen Bandbreite ('Morphospace'), der Morphospace-Veränderung in der Zeit und die berechnete Stachel-Akkumulationsrate das Potential, Diversitäts- und Abundanz-Veränderungen in Bezug zu globalem Klimawandel zu kartieren. Da die derzeitige globale Erwärmung besonders in offenen Ozeanen zu geringerer Produktivität und verringertem Export von Organik in die Tiefsee führt, eignet sich der östliche tropische Pazifik als Modell-Region um zwei Arbeitshypothesen zu testen. i) Die Stachel-Diversität der Atelostomata korreliert invers mit känozoischen Warmzeiten, was die 'Productivity-Diversity Relation' stützt; und ii) Die Abundanz von Atelostomata-Stacheln als Ausdruck von Biomasse und Export-Productivity ist geringer in warmen Perioden als in kühlen. Für das Projekt wurde exemplarisch känozoisches Material aus einer sich rapide ändernden Welt berücksichtigt (Abkühlung Mittel-Miozän, mittelmiozänes Klimaoptimum, Abkühlung oberstes Oligozän, Warmphase Ober-Oligozän, oligozäne Oi-2 Eiszeiten & Nachspiel). Klassifizierbare Merkmale der Stacheln (z.B. Morphologie des Schaftes, Anwesenheit, Verteilung, Häufigkeit von Stacheln und Dornen, Form/Anzahl von Poren, Form der Stachelspitze u.a.) werden in eine Datenmatrix eingepflegt und statistisch ausgewertet. Variationen der Stachel-Diversität (Shannon-Wiener-Index) sind Ausdruck sich verändernder Biodiversität, und eine Abnahme der Diversität sowie der Stachel-Akkumulationsrate werden in Kontext mit Warmphasen vermutet. Eine 'Principal Component Analysis' von Stachel-Vergesellschaftungen einzelner Zeitintervalle ermöglicht es, die Disparität des Morphospace der berücksichtigten Intervalle zu erarbeiten. Hieraus lassen sich darüber hinaus Aussagen über graduelle (Evolution?) oder abrupte (Aussterben und Speziation/Immigration) Faunenveränderungen in der Tiefsee treffen, die in Beziehung zu schwankender Primärproduktivität durch globale Temperaturschwankungen gesetzt werden können (Hypothese 2).

WISE WFD Reference Spatial Datasets reported under Water Framework Directive 2016 - PUBLIC VERSION - version 1.9, Sep. 2025

The dataset contains information on the European river basin districts, the river basin district sub-units, the surface water bodies and the groundwater bodies delineated for the 2nd River Basin Management Plans (RBMP) under the Water Framework Directive (WFD) as well as the European monitoring sites used for the assessment of the status of the above mentioned surface water bodies and groundwater bodies. The information was reported to the European Commission under the Water Framework Directive (WFD) reporting obligations. The dataset compiles the available spatial data related to the 2nd RBMPs due in 2016 (hereafter WFD2016). See http://rod.eionet.europa.eu/obligations/715 for further information on the WFD2016 reporting. See also https://rod.eionet.europa.eu/obligations/766 for information on the Environmental Quality Standards Directive - Preliminary programmes of measures and supplementary monitoring. Where available, spatial data related to the 3rd RBMPs due in 2022 (hereafter WFD2022) was used to update the WFD2016 data. See https://rod.eionet.europa.eu/obligations/780 for further information on the WFD2022 reporting. Note: * This dataset has been reported by the member states. The subsequent QC revealed some problems caused by self-intersections elements. Data in GPKG-format should be processed using QGIS.

WISE WFD Reference Spatial Datasets reported under Water Framework Directive 2016 - INTERNAL VERSION - version 1.7, Jul. 2024

The dataset contains information on the European river basin districts, the river basin district sub-units, the surface water bodies and the groundwater bodies delineated for the 2nd River Basin Management Plans (RBMP) under the Water Framework Directive (WFD) as well as the European monitoring sites used for the assessment of the status of the above mentioned surface water bodies and groundwater bodies. This data set is available only for internal use of the European Commission and the European Environment Agency. Please use the "PUBLIC VERSION": https://sdi.eea.europa.eu/catalogue/srv/eng/catalog.search#/metadata/a0731ebf-6bcc-4afe-bab0-39e7aa88eaba for external use. The information was reported to the European Commission under the Water Framework Directive (WFD) reporting obligations. The dataset compiles the available spatial data related to the 2nd RBMPs due in 2016 (hereafter WFD2016). See http://rod.eionet.europa.eu/obligations/715 for further information on the WFD2016 reporting. See also https://rod.eionet.europa.eu/obligations/766 for information on the Environmental Quality Standards Directive - Preliminary programmes of measures and supplementary monitoring. Where available, spatial data related to the 3rd RBMPs due in 2022 (hereafter WFD2022) was used to update the WFD2016 data. See https://rod.eionet.europa.eu/obligations/780 for further information on the WFD2022 reporting.

A spatially explicit Global Reef Island Database (GRID v1.1) that captures distribution, diversity and relative vulnerability of the world's low-lying reef islands

Low-lying coral reef islands harbour a distinct, yet highly threatened biological and cultural diversity that is increasingly exposed to climate change impacts. The combination of low elevation, small size, sensitivity to changes in boundary conditions (sea level, waves and currents, locally generated sediment supply) and at some locations high population densities, is why low-lying reef islands (LRIs) are considered among the most vulnerable environments on Earth to climate change. To date, their global distribution and influence of climatic, oceanographic, and geologic setting are only poorly documented or restricted to smaller scales. Here, I present the first detailed global analysis of LRIs utilising freely available global datasets to produce a global reef island database (GRID) and associated intrinsic and extrinsic characteristics that can be used within a coastal vulnerability index (CVI). All datasets used to create the GRID were released between 30 November 2015 and 3 August 2023, while the current version (version 1.1) of the GRID database was completed in August 2026. When developing the GRID, LRIs are defined as landmasses <30 km² located on or within 3 km of coral reef and with an elevation of <16 m. Development of the GRID required: 1) the creation of a global shoreline vector file containing the geographic distribution of LRIs and 2) the development of a comprehensive global database of LRIs including eight intrinsic and ten extrinsic variables extracted from global datasets. Intrinsic variables include: 1) human populations, 2) island area, 3) island perimeter, 4) mean elevation, 5) island circularity/shape, 6) underlying reef type, 7) geographic isolation and 8) distance to the nearest neighbouring reef island. Extrinsic variables include: 1) mean water depth, 2) standard deviation of mean water depth, 3) mean annual significant wave height, 4) mean annual wave period, 5) mean spring tidal range, 6) relative tidal range, 7) wave-tide regime, 8) relative wave exposure, 9) relative tropical storm exposure and 10) year-2100 projected median sea level rise rate. The GRID was initially derived from version 2.1 of the UNEP-WCMC Global Island Database, a global shoreline vector file based on geometry data from Open Street Map® (OSM) and released in November 2015. The initial vector file was projected using the Mollweide projection, an equal-area pseudo cylindrical map projection chosen for its accurate derivation of area, especially in regions close to the equator, where most LRIs are located. The final GRID contains 33,292 individual LRIs distributed throughout tropical regions of the world's oceans, amassing a total land area of nearly 11,000 km² with approximately 60,500 km of shoreline and housing around 2.6 million people. While intrinsic variables are typically spatially homogenous, LRIs are generally highly spatially clustered throughout the GRID with respect to extrinsic variables. The spatial distribution of LRIs within the GRID was validated using: 1) published data and 2) quantitative accuracy assessments using satellite imagery. Spatial distributions of LRIs captured in the GRID are extremely consistent with those published in the literature (r² = 0.96) and those derived from independent analysis of satellite imagery (r² = 0.94). Finally, the GRID was used to develop an island vulnerability index (IVI) for each LRI on a scale of 0-1 with 0 representing no vulnerability and 1 representing maximum vulnerability. The GRID database is provided as a tab-delimited text file as well as ESRI shapefiles (points and polygons in WGS84 and Mollweide projection) and a comma-separated value file.

Waterbase - UWWTD: Urban Waste Water Treatment Directive – reported data

The Urban Waste Water Treatment Directive concerns the collection, treatment and discharge of urban waste water and the treatment and discharge of waste water from certain industrial sectors. The objective of the Directive is to protect the environment from the adverse effects of the above mentioned waste water discharges. This series contains time series of spatial and tabular data covering Agglomerations, Discharge Points, and Treatment Plants.

Geographic Information System of the European Commission (GISCO)

This metadata refers to the whole content of GISCO reference database, which contains both public datasets (also available for the general public through http://ec.europa.eu/eurostat/web/gisco/geodata) and datasets to be used only internally by the EEA (typically, but not only, GISCO datasets at 1:100k).

1 2 3 4 5 … 88 89 90