3eab45fd-5049-4c93-8041-d949bea00b0a Dataset German Aerospace Center (DLR) geoservice@dlr.de 2025-11-27T16:23:59 19115-1:2014/19139 1.0 2 65120 10 87740 10 false EPSG:3035 Noise - Road Traffic Lden (AI Prediction) - Germany, 2017 2025-10-16T10:48:00 1.0 https://geoservice.dlr.de/catalogue/srv/metadata/3eab45fd-5049-4c93-8041-d949bea00b0a DOI: 10.15489/5non57bdli63 This dataset includes a road traffic noise estimation using ensemble learning and multimodal geodata. The official noise indicator, Lden (Day-Evening-Night Level), mapped according to the European Noise Directive (2002/49/EC) for large urban agglomerations is extrapolated to suburban areas and beyond. This novel information closes previous data gaps and is herewith available for environmental noise assessments evaluating the impact of road traffic noise on human health and well-being at a spatial resolution of 10 x 10m nation-wide. German Aerospace Center (DLR) geoservice@dlr.de Jeroen Staab German Aerospace Center (DLR) jeroen.staab@dlr.de Michael Wurm German Aerospace Center (DLR) michael.wurm@dlr.de Hannes Taubenböck German Aerospace Center (DLR) hannes.taubenboeck@dlr.de https://geoservice.dlr.de/catalogue/srv/api/records/3eab45fd-5049-4c93-8041-d949bea00b0a/attachments/noise2nako_noiseai_lden_ql_s.jpg thumbnail https://geoservice.dlr.de/catalogue/srv/api/records/3eab45fd-5049-4c93-8041-d949bea00b0a/attachments/noise2nako_noiseai_lden_ql.jpg large_thumbnail Transport networks Human health and safety GEMET - INSPIRE themes, version 1.0 2008-06-01 geonetwork.thesaurus.local.theme.inspire-theme Road Traffic Noise Exposure Residential environment Health 2002/49/EC Germany Nutzungseinschränkungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Use Limitations: DLR not liable for damage resulting from use. License Nutzungsbedingungen: Lizenz, https://creativecommons.org/licenses/by-nc/4.0 / Terms of use: License, https://creativecommons.org/licenses/by-nc/4.0 {"id": "cc-by/4.0", "name": "Creative Commons Namensnennung - Nicht kommerziell 4.0 International (CC BY 4.0)", "url": "http://dcat-ap.de/def/licenses/cc-by/4.0", "quelle": "Copyright DLR (year of production)"} 20000 transportation environment 5.39 15.57 47.12 55.03 2017-01-01T00:00:00 2017-12-31T00:00:00 GeoTIFF https://geoservice.dlr.de/eoc/land/wms? OGC:WMS N2N_NOISE_AI_DE_2017 Noise - Road Traffic Lden (AI Prediction) - Germany, 2017 https://geoservice.dlr.de/web/maps/eoc:n2nnoiseai WWW:LINK-1.0-http--link EOC Geoservice Map Context EOC Geoservice Map Context (eoc:n2nnoisea) https://download.geoservice.dlr.de/NOISE2NAKO/files/NOISE/AI_Prediction/ WWW:LINK-1.0-http--link HTTP Download HTTP Download (Noise2Nako NOISE) https://www.dlr.de/de/eoc/forschung-transfer/projekte-und-missionen/noise2nako-ai WWW:LINK-1.0-http--link Noise2NAKO(AI) project website Website of the Noise2NAKO(AI) project https://doi.org/10.1016/j.trd.2025.105063 WWW:LINK-1.0-http--link Scientific publication Jeroen Staab, Matthias Weigand, Arthur Schady, Ariane Droin, Donatella Cea, Marco Dallavalle, Nikolaos Nikolaou, Mahyar Valizadeh, Kathrin Wolf, Michael Wurm, Tobia Lakes, Hannes Taubenböck. 2025. National road traffic noise estimation with ensemble learning and multimodal geodata, Transportation Research Part D: Transport and Environment. 149, 105063. Conformity_001 INSPIRE Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 See the referenced specification. true Input data: Selected strategic noise maps reported under under the 2002/49/EC obligations to EEA (from 10.15489/a6wg11lrub77), land-cover information (Land Cover DE - Sentinel-2 - Germany, 2015; https://doi.org/10.15489/1ccmlap3mn39), NDVI mosaic based on Copernicus Sentinel-2 (Sentinel-2 - Vegetation Index (NDVI) - Germany, 2015, https://doi.org/10.15489/z5rq0pr8wv85)