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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.

Anwendungspotentiale für Biokohle aus organischen Abfällen in Albanien unter besonderer Berücksichtigung der Wasseraufbereitung

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.

Water and Sewerage Project Shkodra, Albania - Feasibility Study

Nationally designated areas

The European inventory of Nationally designated areas holds information about designated areas and their designation types, which directly or indirectly create protected areas. The Nationally designated areas is the official source of protected area information from the 38 European member countries to the World Database of Protected Areas (WDPA). The Nationally designated areas data can be queried online in the European Nature Information System (EUNIS). Two versions of the public dataset are provided. The full dataset includes the entire geographical coverage including nationally designated areas in overseas entities. The European dataset excludes the overseas entities. The datasets are accompanied by tabular data which 1) includes information on the nationally designated sites and designated boundaries for public dissemination; and 2) contains information about designation types and the national and international legislative instruments, which directly or indirectly create protected designated areas in Europe.

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.

Climatic suitability for the transmission of chikungunya in Europe (1951-2021), Apr 2023

This metadata refer to the dataset presenting the annual change in the basic reproduction number (R0) for chikungunya transmission in the period 1951-2021. The basic reproduction number of chikungunya from Aedes mosquitos is calculated using a model to capture the influence of temperature and rainfall on mosquito vectorial capacity and mosquito abundance, and overlaying it with human population density data to estimate the R0 (i.e., the expected number of secondary infections resulting from one infected person).

Model Output Statistics for TIRANA (13615)

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 ]

Model Output Statistics for SHKODRA (13600)

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 ]

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