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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.

Urban Heat Island (UHI) intensity modelling, Jan. 2020

The raster dataset of urban heat island modelling shows the fine-scale (100m pixel size) temperature differences (in degrees Celsius °C) across 100 European cities, depending on the land use, soil sealing, anthropogenic heat flux, vegetation index and climatic variables such as wind speed and incoming solar radiation. In the framework of the Copernicus European Health contract for the Copernicus Climate Change Service (C3S), VITO provided 100m resolution hourly temperature data (2008-2017) for 100 European cities, based on simulations with the urban climate model UrbClim (De Ridder et al., 2015). As the cities vary in size, so do the model domains. They have been defined with the intention to have a more or less constant ratio of urban vs. non-urban pixels (as defined in the CORINE land use map), with a maximum of 400 by 400 pixels (due to computational restraints). From this data set, the average urban heat island intensity is mapped for the summer season (JJA), which is the standard way of working in the scientific literature (e.g. Dosio, 2016). The UHI is calculated by subtracting the rural (non-water) spatial P10 temperature value from the average temperature map. The 100 European cities for the urban simulations were selected based on user requirements within the health community.

GISCO - Nomenclature of Territorial Units for Statistics 2024 (NUTS 2024), May 2024 - PROVISIONAL DATA

This metadata refer to the PROVISIONAL 'GISCO NUTS 2024' data set representing the NUTS 2024 regulation and statistical regions by means of multipart polygon topology. The full dataset including polyline and point topology will be launched later in 2023. 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 2024 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 and the EU candidate countries.

AG-InstitutionsNaturalResources - Institutionenökonomik natürlicher Ressourcen

Im Rahmen des Forschungsprojektes wird - teilweise interdisziplinär - theoretische und empirische Forschung betrieben, um das Handeln von Landwirten angesichts institutioneller Sachzwänge bei der landwirtschaftlichen Wasserbewirtschaftung und der Landnutzung besser zu verstehen. In etlichen Transformationsländern sind Eigentrumsrechte sowie Rechte auf Zugang und Nutzung von Wasser nur unzureichend definiert und es mangelt an Anreizen für gemeinsame Maßnahmen um Bewässerungsinfrastrukturen zu erhalten. In anderem Umfang, von Land zu Land verschieden, trifft dies auch auf die Land- und Waldnutzung zu. Die Wissenschaftlerinnen und Wissenschaftler nutzen hauptsächlich quantitative Methoden und arbeiten hier mit Primärdaten, die in einigen Transformationsländern erhoben wurden. Sie sind aber grundsätzlich für qualitative Methoden offen. Regionale Forschungsschwerpunkte sind Transformationsländer wie China und ausgewählte Länder Zentralasiens und Südosteuropas. Folgende Qualifikationsarbeiten sind Bestandteil des Projekts: - Tapping two sources: Farmers conjunctive use of groundwater and surface water in North West China (Bearbeitung: Eefje Aarnoudse) - The land and water nexus in a transition context: the case of Tajikistan (Bearbeitung: Frederike Gehrigk) - Too much but not enough: Issues of water management in Albania (Bearbeitung: Klodjan Rama).

Copernicus National Boundary Layer with 250 m buffer, version 3, Jan. 2019

For the provision of land monitoring services within COPERNICUS, a consistent, stable, sufficiently detailed boundary layer is required at EEA, which provides a “land mask” for the area that needs to be monitored. This metadata refers to the National Boundary layer both in vector formats (GDB, SHP) and in raster format (TIFF) at 10, 20 and 100m resolution, of each of the EEA member and cooperating countries as well as the United Kingdom (former EEA39). This is a product derived from the EEA 39 Border Expert product, generalised to a scale of about 1:1 000 000 by applying a buffer of 250m and selecting the outline. Each country boundary has been projected to its respective national system(s), which are specified together with the EEA. The Border Expert product is based on the EU-Hydro Coastline Version 3 from EEA, the EEA coastline for analysis Version 2, the EBM GISCO Hybrid Layer from EEA, the EuroGeographics EuroBoundary Map Version 12, the “Water and Wetness High Resolution Layer 2015” from EEA and the JRC-Global Surface Water Occurrence layer. The production of this Border Product was coordinated by the European Environment Agency in the frame of the EU Copernicus programme.

Climatic suitability index values for tiger mosquito (Aedes albopictus) 2008-2009 (90th percentile), Jan. 2020

This vector dataset provides the climate suitability index values (0-100%) for tiger mosquito (Aedes albopictus) for 100 European cities for the years 2008-2009 (P90 - 90th percentile). Aedes Albopictus has become a common occurrence in Southern Europe and transmits diseases such as Zika, dengue and chikungunya. The climatic suitability for tiger mosquito depends on factors such as sufficient amounts of rainfall, high summer temperatures and mild winters. Climate change is anticipated to further facilitate the spread of tiger mosquitoes across Europe by changing temperature and precipitation patterns, thereby increasing the suitable habitat. In the framework of the Copernicus Climate Change Service (C3S) SIS European Health, VITO (https://vito.be/en) has provided to the Climate Data Store 100m resolution hourly temperature data for 100 European cities, based on simulations with the urban climate model UrbClim (De Ridder et al., 2015). From this dataset, this climate suitability dataset has been generated based on annual precipitation and the average temperature in January and during the summer period (months June, July and August) for the years 2008-2009, following the methodology by European Centre for Disease Prevention and Control (ECDC, 2009). This approach considers empirical suitability functions, which link a number of (aggregated) climate variables to the suitability of a habitat for a given vector species, e.g. for a species to be active a minimum threshold of temperature is required below which the species is not active. Similarly some species cannot overwinter if the winter is too cold (e.g. January temperature lower than a given value). The P90 indicator represents the specific exposure of single cities and is independent of the model domain or size of a city. The 100 European cities for the urban simulations were selected based on user requirements within the health community.

Urban Morphological Zones Changes 1990-2000 (vector) - version 16, Jun. 2013

Changes between UMZs in 1990 and UMZs in 2000 using CLC version 16. Most changes are Positive changes, understood as areas of urban sprawl (i.e. new UMZ areas between 1990 and 2000), while negative changes describe the reduction of a certain UMZ between 1990 and 2000 (warning: some negative changes might be due to different interpretations between 1990-2000).

Urban Morphological Zones 2006 (vector) - version 16, Jun. 2013

An urban morphological zone (UMZ) is defined as a "set of urban areas laying less than 200 m apart". This layer contains UMZ delineations for Europe, based on Corine Land Cover database. During 2012, the UMZ methodology was updated in order to correct errors derived for the water course as join elements between urban areas. Previous version applied over CLC v15 (and previous version) joined many small urban areas due to the water presence. This fact was erroneous from the landscape and urban perspective as most of those areas remain as urban-rural typologies. Moreover, water courses cannot be considered as roads from the urban morphological view (either from the commuting point of understanding). This new version, known as v16, corrected this effect in the majority of cases.

Internationale Karte der Eisenerz-Vorkommen in Europa 1:2.500.000 - Blatt 12 Tbilisi

Die Internationale Karte der Eisenerz-Vorkommen in Europa 1 : 2 500 000 wurde 1977 fertig gestellt und von der BGR herausgegeben. Über 70 Geologen aus Europa, Nordafrika und dem Mittlerem Osten arbeiteten gemeinsam mit dem Redaktionsteam an der Kompilation der Karte und den Erläuterungen. Die Karte, die 42 Länder in 16 Kartenblättern abdeckt, zeigt mehr als 800 Eisenerz-Vorkommen. Alle bedeutenden Vorkommen (im Abbau oder stillgelegt) sind enthalten. Auch Vorkommen, die nur von genetischem oder historischem Interesse sind, wurden mit abgebildet. Detaillierte Informationen zur Internationalen Karte der Eisenerz-Vorkommen in Europa 1 : 2 500 000 - zu Struktur, Aufbau und Hintergrunddaten - sind in den Erläuterungen zur Karte zu finden.

Internationale Hydrogeologische Karte von Europa 1:1.500.000 (IHME1500) - Blatt D6 Athina

Die Internationale Hydrogeologische Karte von Europa im Maßstab 1:1.500.000 (IHME1500) ist ein Kartenwerk hydrogeologischer Übersichtskarten, das aus 25 Kartenblättern mit dazugehörigen Erläuterungen besteht und das den gesamten europäischen Kontinent und Teile des Nahen Ostens abdeckt. Die nationalen Beiträge zu diesem Kartenwerk werden von Hydrogeologen und Spezialisten anderer verwandter Wissenschaftsbereiche unter der Schirmherrschaft der Internationalen Assoziation der Hydrogeologen (IAH) und ihrer Kommission für Hydrogeologische Karten (COHYM) geleistet. Das Kartenprojekt wird von der Kommission für die Geologische Weltkarte (CGMW) unterstützt. Die wissenschaftlich-redaktionelle Arbeit wird finanziell durch die Regierung der Bundesrepublik Deutschland über die Bundesanstalt für Geowissenschaften und Rohstoffe (BGR) und die Organisation der Vereinten Nationen für Bildung, Wissenschaft und Kultur (UNESCO) gesponsert. Beide Organisationen sind für die Kartographie, den Druck und die Publikation der Kartenblätter und Erläuterungen verantwortlich. In der IHME1500 werden die hydrogeologischen Gegebenheiten von Europa als Ganzes ohne Berücksichtigung politischer Grenzen dargestellt. Gemeinsam mit den begleitenden Erläuterungsheften kann das Kartenwerk für wissenschaftliche Zielstellungen, für regionale Planungen und als Grundlage für detaillierte hydrogeologische Kartierarbeiten genutzt werden.

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