This is a high-spatial-resolution dataset aggregating cloud-free Landsat 8 and Landsat 9 Land Surface Temperature (LST) data across five consecutive summers (2021–2025). The dataset provides a temporal aggregate of the Landsat Level 2 Collection 2 product provided by the U.S. Geological Survey (USGS), indicating surface thermal patterns across Germany. The dataset includes a supplementary observation count raster, where each pixel value indicates the total number of individual, valid, cloud-free observations contributing to the final aggregated data product.

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.

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.

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 surface PM2.5 concentrations for Germany and parts of the surrounding countries. PM2.5 surface concentrations are derived from Aqua/MODIS and Sentinel-3A/SLSTR AOD data and provided as merged MODIS/SLSTR product. The data is generated by DLR and provided in the framework of the mFUND-Project "S-VELD". The surface PM2.5 data are concentrations with the unit "µg/m3". The satellites Aqua (NASA) and Sentinel-3 (Copernicus) observe Germany on a daily basis. PM2.5 concentrations were derived on a daily basis from the two AOD products separately and combined to a merged MODIS/SLSR surface PM2.5 product. The data within each month are averaged and gridded onto a regular UTM grid. As AOD measurements are strongly depending on cloud conditions, the spatial coverage can be limited, especially in the winter months.

The Global WaterPack is a dataset containing information about open surface water cover parameters on a global scale. The water detection is derived from daily, operational MODIS datasets for every year since 2003. The negative effects of polar darkness and cloud coverage are compensated by applying interpolation processing steps. Thereby, a unique global dataset can be provided that is characterized by its high temporal resolution of one day and a spatial resolution of 250 meter. This collection includes yearly composites of the dataset with information on how often a pixel was detected as open surface water with pixel values between 0 and 365 (366 for leap years). Furthermore, a reliability layer provides information on the quality of each Global WaterPack pixel.

F-SAR, “Flugzeug-SAR”, is an airborne high-resolution imaging radar (Synthetic Aperture Radar) sensor presently operated by the German Aerospace Center (DLR), Microwaves and Radar Institute (HR) since November 02, 2006. It is operated on a Dornier Do-228 aircraft from altitudes of 2000 to 6000 m above ground in five different center frequency bands (X,C,S,L,P). Wavelengths range from 3 cm, 5 cm, 9 cm, 23 cm to 67 cm. Ka-band (1 cm wavelength) is planned to be added. Up to four center-frequencies (X,S,L,P) or (X,C,L,P) can be operated simultaneously per overflight. All frequencies are fully polarimetric (HH,HV,VV,VH) and have full repeat-pass capabilities. Single-pass interferometry in along-track (ATI) and across-track mode is available in X-band (ATI and/or XTI) and S-band (XTI). Data are processed up to three different levels: RGI (Radar Geometry Image product), INF (Repeat-pass-interferometric product) and GTC (Geocoded and Terrain-Corrected product). Resolutions range from 25 cm (X-band) to 1.5 m (P-band) in both azimuth and range direction. Data acquisition modes are typically “stripmap”, “repeat-pass” (two parallel tracks), “tomography” (several parallel tracks), ”circular” (one circle) or “circular-tomography” (several vertically distributed circles). Individually planned experiments can also be supported. For more information concerning F-SAR data, the reader is referred to: www.dlr.de/hr/f-sar

E-SAR, “Experimental-SAR”, is an airborne imaging radar (Synthetic Aperture Radar) sensor operated by the German Aerospace Center (DLR), Microwaves and Radar Institute (HR) from 1988 until November 2009. It was operated on a Dornier Do-228 aircraft from altitudes of 2000 to 6000 m above ground in four different center frequency bands (X,C,L,P). Different center frequencies were operated sequentially in different overflights. Data were acquired either in one-channel, two-channel or four-channel mode in HH, HV, VV and/or VH polarization. Fully polarimetric data are available in L- and P-band only. Repeat-pass interferometry is available in L- and P-band. Single-pass interferometry is available in X-band only, in along- and across-track antenna configuration. Data are processed up to two different levels: RGI (Radar Geometry Image product) and GTC (Geocoded and Terrain-Corrected product). Resolutions range from 25 cm (X-band) to 1.5 m (P-band) in azimuth direction and from 1.8 m (X-band) to 3 m (P-band) in range direction. Data acquisition modes are “stripmap”, “repeat-pass” (two parallel tracks) or “tomography” (several parallel tracks). For more information concerning E-SAR data, the reader is referred to: www.dlr.de/hr/e-sar

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.

Hedgerows play an important role in maintaining biodiversity, carbon sequestration, soil stability and the ecological integrity of agricultural landscapes. In this dataset, hedgerows are mapped for the whole of Bavaria. Orthophotos with a spatial resolution of 20 cm, taken in the period from 2019 to 2021, were used in a deep learning approach. Hedgerow polygons of the Bavarian in-situ biotope mapping from 5 districts (Miltenberg, Hassberge, Dillingen a.d. Donau, Freyung-Grafenau, Weilheim-Schongau) as well as other manually digitized polygons were used for training and testing as input into a DeepLabV3 Convolutional Neural Network (CNN). The CNN has a Resnet50 backbone and was optimized with the Dice loss as a cost function. The generated hedgerow probability tiles were post-processed by merging and averaging the overlapping tile boundaries, shape simplification and filtering. For more details, see Huber Garcia et al. (2025). The dataset has been created within the project FPCUP (https://www.copernicus-user-uptake.eu/) in close cooperation with Bayerisches Landesamt für Umwelt (LfU).