The Nomenclature of Territorial Units for Statistics (NUTS) is a hierarchical classification of statistical regions and subdivides the EU economic territory into regions of four different levels (NUTS 0, 1, 2 and 3, moving respectively from larger to smaller territorial units). NUTS 1 is the most aggregated level. An additional Country level (NUTS 0) is also available for countries where the the nation at statistical level does not coincide with the administrative boundaries. For example Mt Athos in Greece and Mellum and Minsener Ogg in Germany. The NUTS classification has been officially established through Regulation (EC) No 2016/2066 of the European Parliament and of the Council and its amendments. A non-official NUTS-like classification has been defined for the EFTA countries and candidate countries. An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview. The datasets are based on: EuroBoundaryMap (EBM) from EuroGeographics (scale of 1:100.000), Global Administrative Unit Layer (GAUL) country data from UN/FAO, data from the National Statistical Institute of Turkey (TurkStat) (might vary for different years). The different scale levels were derived by generalisation of the 100K scale. The public datasets are available under the Download link indicated below. Available scales are: 100k, 1M, 3M, 10M, 20M, 60M. Date of the NUTS regions are currently available for the years 2003, 2006, 2010, 2013, 2016 and 2021. The full datasets are available via the EC restricted download link. Here six scale ranges (100K, 1M, 3M, 10M and 20M, 60M) are available. Coverage is the economic territory of the EU, EFTA countries and candidate countries as in the respective year.

This dataset represents the regions for levels 1, 2 and 3 of the Nomenclature of Territorial Units for Statistics (NUTS) for 2016. The NUTS nomenclature is a hierarchical classification of statistical regions and subdivides the EU economic territory into regions of four different levels (NUTS , 1, 2 and 3, moving respectively from larger to smaller territorial units). NUTS 1 is the most aggregated level. An additional Country level (NUTS 0) is also available for countries where the the nation at statistical level does not coincide with the administrative boundaries. For example Mt Athos in Greece and Mellum and Minsener Ogg in Germany. The NUTS classification has been officially established through Regulation (EC) No 2016/2066 of the European Parliament and of the Council and its amendments. A non-official NUTS-like classification has been defined for the EFTA countries and candidate countries. An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview. This dataset has been created mainly from the EuroBoundary Map v 12 (Eurogeographics) and geographic information from TurkStat for Turkey. The public dataset is available under the Download link indicated below. Available scales are 1M, 3M, 10M, 20M, 60M). The full dataset is available via the EC restricted download link under GISCO.NUTS_2016. Here six scale ranges (100K, 1M, 3M, 10M and 20M, 60M) are available. Coverage is the economic territory of the EU, EFTA countries and candidate countries as in 2013.

This dataset represents the regions for levels 1, 2 and 3 of the Nomenclature of Territorial Units for Statistics (NUTS) for 2016. The NUTS nomenclature is a hierarchical classification of statistical regions and subdivides the EU economic territory into regions of four different levels (NUTS , 1, 2 and 3, moving respectively from larger to smaller territorial units). NUTS 1 is the most aggregated level. An additional Country level (NUTS 0) is also available for countries where the the nation at statistical level does not coincide with the administrative boundaries. For example Mt Athos in Greece and Mellum and Minsener Ogg in Germany. The NUTS classification has been officially established through Regulation (EC) No 2016/2066 of the European Parliament and of the Council and its amendments. A non-official NUTS-like classification has been defined for the EFTA countries and candidate countries. An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview. This dataset has been created mainly from the EuroBoundary Map v 12 (Eurogeographics) and geographic information from TurkStat for Türkiye. The public dataset is available at 1M, 3M, 10M, 20M, 60M, while the full dataset at 100K is restricted. Coverage is the economic territory of the EU, EFTA countries and candidate countries as in 2016. This metadata only refers to a pre-release version of the full nuts 2016 dataset at 100k (it does not contain Albanian boundaries) and shall only be used internally by the EEA following the conditions stated in the document "GISCO-LicenseconditionsforEGdatasets.pdf" provided with the dataset. This metadata has been slightly adapted from the original metadata file provided by Eurostat (European Commission) and is to be used only for internal EEA purposes. For reference, the original metadata file provided by ESTAT (NUTS_2016.xml) is also available for download together with the dataset. The public datasets, at smaller scales, are available on http://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units/nuts#nuts16.

The graph presented in this dataset contains all German municipalities and their metadata keyed by NUTS Level 3, provided by the DE BKG as of 06/2019 - changed. All data renderings provided here were done in Cytoscape 3.7.1 (Season file for replication purposes is included in the archives). NUTS is a categorization system for European regions ranging from whole nations (NUTS 0), countries (NUTS 1 and 2), municipalities (NUTS 3) to even smaller regions in some cases (LAU). The AGS (amtlicher Gemeindeschlüssel), which is unique to germany, is also included in the Metadata. Thus the data can be linked with european and german institution sourced data at the same time.

The archive files contain the following items:

• Edge-List (NutsA-NutsB) wth NUTS only

• Node-List with all metadata provided by BKG files.

• Example Edge-List with Population-Density-Metric connection values

• Season-File for Cytoscape 3.7.1 to reproduce the renderings in this paper

All table files are in CSV format with UTF-8 encoding and ; delimiter. Special character like ö, ä, ß, ü have been replaced (with oe, ae, ss, ue) to ensure compatibility.

This landcover map was produced as an intermediate result in the course of the project incora (Inwertsetzung von Copernicus-Daten für die Raumbeobachtung, mFUND Förderkennzeichen: 19F2079C) in cooperation with ILS (Institut für Landes- und Stadtentwicklungsforschung gGmbH) and BBSR (Bundesinstitut für Bau-, Stadt- und Raumforschung) funded by BMVI (Federal Ministry of Transport and Digital Infrastructure). The goal of incora is an analysis of settlement and infrastructure dynamics in Germany based on Copernicus Sentinel data. This classification is based on a time-series of monthly averaged, atmospherically corrected Sentinel-2 tiles (MAJA L3A-WASP: https://geoservice.dlr.de/web/maps/sentinel2:l3a:wasp; DLR (2019): Sentinel-2 MSI - Level 2A (MAJA-Tiles)- Germany). It consists of the following landcover classes: 10: forest 20: low vegetation 30: water 40: built-up 50: bare soil 60: agriculture Potential training and validation areas were automatically extracted using spectral indices and their temporal variability from the Sentinel-2 data itself as well as the following auxiliary datasets: - OpenStreetMap (Map data copyrighted OpenStreetMap contributors and available from htttps://www.openstreetmap.org) - Copernicus HRL Imperviousness Status Map 2018 (© European Union, Copernicus Land Monitoring Service 2018, European Environment Agency (EEA)) - S2GLC Land Cover Map of Europe 2017 (Malinowski et al. 2020: Automated Production of Land Cover/Use Map of Europe Based on Sentinel-2 Imagery. Remote Sens. 2020, 12(21), 3523; https://doi.org/10.3390/rs12213523) - Germany NUTS administrative areas 1:250000 (© GeoBasis-DE / BKG 2020 / dl-de/by-2-0 / https://gdz.bkg.bund.de/index.php/default/nuts-gebiete-1-250-000-stand-31-12-nuts250-31-12.html) - Contains modified Copernicus Sentinel data (2016), processed by mundialis Processing was performed for blocks of federal states and individual maps were mosaicked afterwards. For each class 100,000 pixels from the potential training areas were extracted as training data. An exemplary validation of the classification results was perfomed for the federal state of North Rhine-Westphalia as its open data policy allows for direct access to official data to be used as reference. Rules to convert relevant ATKIS Basis-DLM object classes to the incora nomenclature were defined. Subsequently, 5.000 reference points were randomly sampled and their classification in each case visually examined and, if necessary, revised to obtain a robust reference data set. The comparison of this reference data set with the incora classification yielded the following results: overall accuracy: 88.4% class: user's accuracy / producer's accuracy (number of reference points n) forest: 96.7% / 94.3% (1410) low vegetation: 70.6% / 84.0% (844) water: 98.5% / 94.2% (69) built-up: 98.2% / 89.8% (983) bare soil: 19.7% / 58.5% (41) agriculture: 91.7% / 85.3% (1653) Incora report with details on methods and results: pending

1. TABLE CONTENTS The table contains information on commuters and employees at the place of work by country of residence (country of residence). This information was compiled as part of the two Interreg programs Germany-Netherlands and Flanders-Netherlands to provide cross-border labor market data. Data available from: 2010 reporting period 2010-2019 Status of the figures: The figures in this table are final. Changes as of 25 March 2022: Added figures for 2019. In addition, the dates for old years have changed slightly for some regions. The German data is newly supplied, which means we have fewer unknown numbers. The Dutch data has been modified as newer versions of different registrations were used and the method of imputing unknown information was improved. Changes as of November 12, 2020: Dates for 2018 have been added. From January 1st, 2019, a new administrative structure will apply to Belgium. The updated data follows the new outline. Due to an improvement in the method used, there are changes in the Dutch figures. When will new figures be published? (When will new figures be published?) New figures The new figures will be published in the fourth quarter of 2022

This table contains figures on employees by country of residence and work region in the Netherlands, Belgium, Lower Saxony and North Rhine-Westphalia. The data can be further broken down by gender and industry. This information has been compiled in the context of an Interreg project within the Germany-Netherlands and Flanders-Netherlands program to make cross-border labor market data available. Data available from: 2010. Reporting period 2010-2019 Status of the figures: The figures in this table are final. Changes as of 25 March 2022 Figures for 2019 have been added. In addition, the dates for old years have changed slightly for some regions. The German data has been delivered again, so we have fewer unknowns. The Dutch data has been changed because newer versions of various registrations have been used and the method for imputing unknown information has been improved. Changes as of 3 November 2020 The figures for 2018 have been added. The Belgian regional breakdown has been adjusted according to the reclassifications in 2019. Due to an improvement in the method used, there are changes in the Dutch figures. When will new numbers come out? The new figures will be available in the fourth quarter of 2022.