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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.

[EU SDG 06_60] Water exploitation index, plus (WEI+)

The WEI+ provides a measure of total water consumption as a percentage of the renewable freshwater resources available for a given territory and period. The WEI+ is an advanced geo-referenced version of the WEI. It quantifies how much water is abstracted monthly or seasonally and how much water is returned before or after use to the environment via river basins (e.g. leakages, discharges by economic sectors). The difference between water abstractions and water returns is regarded as ‘water consumption’.

Bathing Water Directive - Status of bathing water

The EU Bathing Waters Directive requires Member States to identify popular bathing places in fresh and coastal waters and monitor them for indicators of microbiological pollution (and other substances) throughout the bathing season which runs from May to September

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.

Fossile Faunen und Floren Kretas/Albaniens und ihre stratigraphische und ökologische Bedeutung

Im Anschluss an ältere, vor allem in der zweiten Hälfte der achtziger Jahre durchgeführte Untersuchungen in Griechenland und später Albanien sind einige ergänzende Geländearbeiten mit Kollegen der genannten Länder geplant, wozu alleine Reisemittel beantragt werden. Die biostratigraphisch ungegliederten Plattenkalke des Lefka-Gebirges führen nach Funden auf sekundärer Lagerstätte offensichtlich Fossilien, die im Anstehenden gesucht werden sollen. Die besonders von unserer Arbeitsgruppe gut untersuchten neogenen marinen Schichten Kretas sollen jetzt zusätzlich isotopen-stratigraphisch erfasst werden, wozu eine Mitarbeiterin die Proben nehmen muss. Rezente und fossile Algen-Vermetiden-Riffe Westkretas sind einer ersten Untersuchung unterzogen worden, jedoch fehlt noch eine quantitative Aufnahme bzw. Beprobung. Im Rahmen eines größeren Projektes über die Molassesedimente in der albanischen periadriatischen Depression wird ein Mitarbeiter an ausgewählten Profilen Beprobungen zur Untersuchung des Mikro- bzw. schwerpunktmäßig des Nannoplanktons durchführen und im Rahmen einer Dissertation untersuchen.

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/

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.

Exposure to climate hazards

This series refers to datasets related to the presence of people; livelihoods; species or ecosystems; environmental functions, services, and resources; infrastructure; or economic, social, or cultural assets in places and settings that could be adversely affected by climate hazards, including flooding, wildfires and urban heat island effects. The datasets are part of the European Climate Adaptation Platform (Climate-ADAPT) accessible here: https://climate-adapt.eea.europa.eu/

Auswirkungen von Migration und Rücküberweisungen auf die Landwirtschaft und die ländliche Entwicklung in Kosovo und Albanien

Die Mehrheit der internationalen Abwanderungen aus dem Kosovo und Albanien entstammen ländlicher Gebiete, die durch geringes Pro-Kopf-Einkommen, niedrige landwirtschaftliche Produktivität und hohe Arbeitslosenquoten gekennzeichnet sind und wo Familienbetriebe zum Eigenbedarf mit einfachen Landbaussystemen, hohem Grad an Ausschuss und schlechten landwirtschaftlichen Methoden die Norm sind. Die Migration in urbane Gebiete oder auf lukrativere westliche Arbeitsmärkte ist ein wesentlicher Teil der Existenzstrategien ländlicher Haushalte geworden. Die übergreifende Ziele dieser Forschungsarbeit sind: a) ein umfassendes Verständnis der Auswirkungen der internationalen Migration auf die Landwirtschaft und die ländliche Entwicklung im Kosovo und in Albanien zu schaffen, b) diese Auswirkungen auf ländliche Einkommensungleichheit und Armut, landwirtschaftliche Produktivität sowie Investitionen auf und außerhalb der Höfe zu quantifizieren, und c) Politikempfehlungen zu geben, wie die internationale Migration wirksam für die Entwicklung von einkommensschwachen ländlichen Gebieten in Albanien und im Kosovo eingesetzt werden kann. Für die Studie werden sowohl primäre, durch Feldforschung erhobene Daten verwendet, als auch zwei existierende Mikroleveldatensätze aus Albanien und dem Kosovo (Living Standard Measurement Survey - LSMS 2012 für Albanien und die UNDP 2011 Kosovo Remittance Survey).

Stakeholders, Interests and Power as Drivers of Community Forestry: Comparative Analysis of Albania, Germany, Cameroon, Indonesia, Namibia, Nepal and Thailand

Community forestry has not met the great public expectations on a significant contribution to sustainable forestry yet. Recent research in the management and policy of community forestry describes a complex process of multi level social choice which determines the outcomes. Our hypothesis is that the key factors determining the outcomes of community forestry are the interests and power of the external stake holders. This hypothesis will be tested in a comparative quantitative and qualitative analysis. In seven countries comprising developed and developing countries 84 cases will be used for comparison. The comparative analysis will be carried out by one PhD student financed by the project. He will do the field work in close cooperation with PhD students who are already conducting their PhD analysis the different countries. The comparative analysis is aimed to explore key drivers of community forestry which are not yet identified in literature.

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