This collection contains surface NO2 concentrations for Germany derived from Sentinel-5P/TROPOMI data. The Sentinel-5P NO2 data is generated by DLR and provided in the framework of the mFUND-Project "S-VELD". The surface NO2 data are concentrations with the unit "µg/m3". Sentinel-5P observes Germany once per day at ~12:00 UTC. These daily observations are gridded onto a regular UTM grid. The day and measurement time are included in the netCDF data file. Only surface NO2 data for cloud-free Sentinel-5P measurements are provided (cloud fraction less than ~0.2). Sentinel-5P cloud fraction data is included in this collection as well.

The digital terrain model of waterways for the estuary of river Elbe (DGM-W 2016) in high resolution based on airborne laser scanning and echo sounder data is produced and published by the German Federal Waterways and Shipping Administration (Wasserstraßen- und Schifffahrtsverwaltung des Bundes, WSV). The data includes the Outer Elbe and the tidally influenced side branches of the Elbe estuary upstream to the town Geesthacht. The data is available in a raster resolution of 1 meter. Coordinate reference system: EPSG 25852, ETRS89 / UTM Zone 32N Elevation reference system: DHHN92, NHN Survey methods: Airborne laser scanning (ALS) 02. - 04.2016 Multibeam echo sounder, single beam echo sounder 2015-2017 It is strongly recommended to use the data source map for quality assessment.

This collection contains tropospheric NO2 columns for Germany and surrounding areas derived from Sentinel-5P/TROPOMI Level-1B data. The Sentinel-5P tropospheric NO2 data is generated by DLR and provided in the framework of the mFUND-Project "S-VELD". The tropospheric NO2 data are vertical column densities with the unit "µmol/m2". Sentinel-5P observes Germany once per day at ~12:00 UTC. These daily observations are gridded onto a regular UTM grid. The day and measurement time are included in the netCDF data file. Only tropospheric NO2 data for cloud-free Sentinel-5P measurements are provided (cloud fraction < ~0.2). Sentinel-5P cloud fraction data is included in this collection as well.

The hyperspectral instrument DESIS (DLR Earth Sensing Imaging Spectrometer) is one of four possible payloads of MUSES (Multi-User System for Earth Sensing), which is mounted on the International Space Station (ISS). DLR developed and delivered a Visual/Near-Infrared Imaging Spectrometer to Teledyne Brown Engineering, which was responsible for integrating the instrument. Teledyne Brown designed and constructed, integrated and tested the platform before delivered to NASA. Teledyne Brown collaborates with DLR in several areas, including basic and applied research for use of data. DESIS is operated in the wavelength range from visible through the near infrared and enables precise data acquisition from Earth's surface for applications including fire-detection, change detection, maritime domain awareness, and atmospheric research. Three product types can be ordered, which are Level 1B (systematic and radiometric corrected), Level 1C (geometrically corrected) and Level 2A (atmospherically corrected). The spatial resolution is about 30m on ground. DESIS is sensitive between 400nm and 1000nm with a spectral resolution of about 3.3nm. DESIS data are delivered in tiles of about 30x30km. For more information concerning DESIS the reader is referred to https://www.dlr.de/de/eoc/forschung-transfer/projekte-und-missionen/desis

This change map was produced on the basis of a classification method developed in 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. The map indicates land cover changes between the years 2019 and 2020. It is a difference map from two classifications based on Sentinel-2 MAJA data (MAJA L3A-WASP: https://geoservice.dlr.de/web/maps/sentinel2:l3a:wasp; DLR (2019): Sentinel-2 MSI - Level 2A (MAJA-Tiles)- Germany). More information on the two basis classifications can be found here: https://data.mundialis.de/geonetwork/srv/eng/catalog.search#/metadata/36512b46-f3aa-4aa4-8281-7584ec46c813 https://data.mundialis.de/geonetwork/srv/eng/catalog.search#/metadata/9246503f-6adf-460b-a31e-73a649182d07 To keep only significant changes in the change detection map, the following postprocessing steps are applied to the initial difference raster: - Modefilter (3x3) to eliminate isolated pixels and edge effects - Information gain in a 4x4 window compares class distribution within the window from the two timesteps. High values indicate that the class distribution in the window has changed, and thus a change is likely. Gain ranges from 0 to 1, all changes < 0.5 are omitted. - Change areas < 1ha are removed The resulting map has the following nomenclature: 0: No Change 1: Change from low vegetation to forest 2: Change from water to forest 3: Change from built-up to forest 4: Change from bare soil to forest 5: Change from agriculture to forest 6: Change from forest to low vegetation 7: Change from water to low vegetation 8: Change from built-up to low vegetation 9: Change from bare soil to low vegetation 10: Change from agriculture to low vegetation 11: Change from forest to water 12: Change from low vegetation to water 13: Change from built-up to water 14: Change from bare soil to water 15: Change from agriculture to water 16: Change from forest to built-up 17: Change from low vegetation to built-up 18: Change from water to built-up 19: Change from bare soil to built-up 20: Change from agriculture to built-up 21: Change from forest to bare soil 22: Change from low vegetation to bare soil 23: Change from water to bare soil 24: Change from built-up to bare soil 25: Change from agriculture to bare soil 26: Change from forest to agriculture 27: Change from low vegetation to agriculture 28: Change from water to agriculture 29: Change from built-up to agriculture 30: Change from bare soil to agriculture - Contains modified Copernicus Sentinel data (2019/2020), processed by mundialis Incora report with details on methods and results: pending

This collection contains monthly mean surface NO2 concentrations for Germany derived from Sentinel-5P/TROPOMI data. The Sentinel-5P NO2 data is generated by DLR and provided in the framework of the mFUND-Project "S-VELD". The surface NO2 data are concentrations with the unit "μg/m3". Sentinel-5P observes Germany once per day at ~12:00 UTC and only cloud-free measurements (cloud fraction less than ~0.2) are used. The Sentinel-5P surface NO2 data within each month are averaged and gridded onto a regular UTM grid. The number of measurements used in the calculation of the averaged value are included in this collection as well.

This collection contains monthly mean tropospheric NO2 columns for Germany and surrounding areas derived from Sentinel-5P/TROPOMI Level-1B data. The Sentinel-5P tropospheric NO2 data is generated by DLR and provided in the framework of the mFUND-Project "S-VELD". The tropospheric NO2 data are vertical column densities with the unit "μmol/m2". Sentinel-5P observes Germany once per day at ~12:00 UTC and only cloud-free measurements (cloud fraction < ~0.2) are used. The Sentinel-5P tropospheric NO2 data within each month are averaged and gridded onto a regular UTM grid. The number of measurements used in the calculation of the averaged value are included in this collection as well.