The EnMAP HSI L2A dataset collection comprises a standardized, consistent, systematically processed, and cloud-native level-2A dataset series for the entire mission. It is especially useful for big data or time series analyses. The dataset is processed with the atmospheric correction over land processor and is provided in cloud-optimized GeoTIFF format for direct access and download. The metadata follows the CEOS Analysis Ready Data (CEOS-ARD) framework. The database is constantly updated with newly acquired data. The Environmental Mapping and Analysis Program (EnMAP) is a German hyperspectral satellite mission that monitors and characterizes Earth’s environment on a global scale. EnMAP delivers accurate data that provides information on the status and evolution of terrestrial and aquatic ecosystems, supporting environmental monitoring, management, and decision-making. For more information, please see the mission website: https://www.enmap.org/mission/

The Al Zaatari refugee camp in Jordan is situated approx. 12 km from the Syrian border and in close proximity to the city of Al Mafraq (10 km). Due to heavy rainfall in the region parts of the Zaatari camp are affected by flooding. The map shows the flood situation derived by semi-automatic image analysis of TerraSAR-X data acquired on January 10, 2013 at 03:38:49 UTC. Furthermore basic reference information, digitized on the basis of WorldView-2 satellite data acquired on January 03, 2013, at 08:52:52 UTC, is depicted. The contour lines were derived from ASTER GDEM 2 data (vertical accuracy +/- 6m). For a more detailed view on the flood situation, parts of the camp area are also shown in the zoom boxes. The results of the image interpretation and analysis have not been validated in the field. WorldView-2 satellite data acquired on January 03, 2013, is used as backdrop. Please note that flood waters in settlement areas might not be fully captured and the water extent might be underestimated due to sensor characteristics. Thus especially shallow water bodies might not be fully captured. The products elaborated for this Rapid Mapping Activity are realised to the best of our ability, within a very short time frame, optimising the material available. All geographic information has limitations due to the scale, resolution, date and interpretation of the original source materials. No liability concerning the content or the use thereof is assumed by the producer. The ZKI crisis maps are constantly updated. Please make sure to visit http://www.zki.dlr.de for the latest version of this product.

The map shows the elevation of the surroundings of the Al Zaatari refugee camp in Jordan. The elevation information is derived from ASTER GDEM 2 data (vertical accuracy +/- 6m). Furthermore basic reference information, digitized on the basis of WorldView-2 satellite data acquired on January 03, 2013, at 08:52:52 UTC and LANDSAT-7 data acquired on December 16, 2012 at 08:07:11 UTC, is depicted. Not all settlements are captured. The results have not been validated in the field. ASTER GDEM 2 data as well as a hillshade derived from this data is used as backdrop. Please note, that information on elevation derived from ASTER data does not apply for the refugee camp area. ASTER data was acquired before 2011 and the elevation might have changed due to construction works. The products elaborated for this Rapid Mapping Activity are realised to the best of our ability, within a very short time frame, optimising the material available. All geographic information has limitations due to the scale, resolution, date and interpretation of the original source materials. No liability concerning the content or the use thereof is assumed by the producer. The ZKI crisis maps are constantly updated. Please make sure to visit http://www.zki.dlr.de for the latest version of this product.

The map shows the Al Zaatari refugee camp in Jordan. It is situated approx. 12 km from the Syrian border and in close proximity to the city of Al Mafraq (10 km). The camp was set up on July 28, 2012, to shelter refugees fleeing the conflict in Syria. The map shows general characteristics of the camp infrastructure, including camp extent, location of shelters, containers and facility buildings, road infrastructure and the runway area. For a more detailed view parts of the camp area are also shown in the zoom boxes. The vector data have been digitized on the basis of WorldView-2 satellite data (0.5 m spatial resolution) acquired on January 03, 2013. The results have not been validated in the field. WorldView-2 satellite data acquired on January 03, 2013, is used as backdrop. The products elaborated for this Rapid Mapping Activity are realised to the best of our ability, within a very short time frame, optimising the material available. All geographic information has limitations due to the scale, resolution, date and interpretation of the original source materials. No liability concerning the content or the use thereof is assumed by the producer. The ZKI crisis maps are constantly updated.

The map shows the Al Zaatari refugee camp in Jordan. It is situated approx. 12 km from the Syrian border and in close proximity to the city of Al Mafraq (10 km). The camp was set up on July 28, 2012 to shelter refugees fleeing the conflict in Syria. The vector data have been digitized on the basis of WorldView-2 satellite data (0.5m spatial resolution) acquired on January 03, 2013. The results have not been validated in the field. WorldView-2 satellite data acquired on January 03, 2013 is used as backdrop. The products elaborated for this Rapid Mapping Activity are realised to the best of our ability, within a very short time frame, optimising the material available. All geographic information has limitations due to the scale, resolution, date and interpretation of the original source materials. No liability concerning the content or the use thereof is assumed by the producer. The ZKI crisis maps are constantly updated. Please make sure to visit http://www.zki.dlr.de for the latest version of this product.

This collection contains Sentinel-2 Level 2A surface reflectances, which are computed for the country of Germany using the time-series based MAJA processor. During the Level 2A processing, the data are corrected for atmospheric effects and clouds and their shadows are detected. The MAJA L2A product is available online for the last 12 months. Further data are kept in the archive and are available upon request. Please see https://logiciels.cnes.fr/en/content/maja for additional information on the MAJA product. The MAJA product offers an alternative to the official ESA L2A product and has been processed with consideration of the characteristics of the Sentinel-2 mission (fast collection of time series, constant sensor perspective, and global coverage). Assumptions about the temporal constancy of the ground cover are taken into account for a robust detection of clouds and a more flexible determination of aerosol properties. As a result, an improved determination of the reflectance of sunlight at the earth's surface (pixel values of the multispectral image) is derived. Further Sentinel-2 Level 2A data computed using MAJA are available on the following website: https://theia.cnes.fr

The PolarLakes dataset provides bi-weekly observations of supraglacial lakes on Antarctic ice shelves, utilizing imagery from Sentinel-2 and Sentinel-1 to address time series gaps caused by frequent cloud cover. These observations detect the extents of supraglacial lakes with a U-Net model for every two weeks from November to March, with each sensor operating independently before the data is merged. The resulting bi-weekly product reflects the maximum lake extents for the first and second halves of each month. When combined for an entire season, the dataset consolidates all bi-weekly records over these five months, allowing for analysis of the maximum lake extent per season and the frequency of lake formation, which can occur up to ten times (5 months á two weeks). The year indicated in the dataset corresponds to January of the melt season, as this month typically experiences the highest melt rates (e.g., 2023 refers to the season from November 2022 to March 2023). The aggregation of all annual datasets creates a recurrence layer that illustrates the frequency of lake presence throughout the entire observation period, which spans from 2014 to 2024, depending on satellite data availability for each ice shelf. The PolarLakes dataset provides valuable insights into the dynamics of supraglacial lakes and serves as a crucial resource for hydrological and climate modeling.

The degree of urbanization provides urbanization level information at 100x100 meter grids for Germany. It is based on population numbers, building density and the share of building types. It is provided as a continuous percentage value representing the probability of the degree of urbanization, as well as five discrete values representing classes of the degree of urbanization: definitely ‘urban’, probably ‘urban’, area of uncertainty, probably ‘rural’, definitely ‘rural’.

This dataset provides monthly maximum Land Surface Temperature (LST) values over Europe, derived from 1-km AVHRR observations. The data is generated by DLR and provided in the framework of the TIMELINE project. LST values are retrieved using physically-based split- and mono-window algorithms and corrected for atmospheric influences and surface emissivity. Only cloud-free observations with sensor view angles below 50 degrees are used. Due to reliance on infrared observations, data may be limited under persistent cloud cover. To ensure temporal consistency across sensors and overpass times, an orbit drift correction method was applied. This method harmonizes LST values to a fixed reference time of 13:00 local solar time, approximating the daily maximum temperature. The dataset is gridded in a 1-km LAEA ETRS89 projection. The product is provided in four tiles, covering the extent of the European Environmental Agency (EEA) reference grid, which includes the area from 900 000 m East and 900 000m North to 7 400 000m East and 5 500 000m North. The TIMELINE (TIMe Series Processing of Medium Resolution Earth Observation Data assessing Long-Term Dynamics In our Natural Environment) project, led by the German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR), focuses on generating a consistent, multi-decadal time series derived from NOAA and Metop AVHRR data. Spanning more than 40 years from the early 1980s to the present this dataset covers Europe and North Africa. TIMELINE establishes an operational environment for the systematic reprocessing of AVHRR raw data into Level 1b, Level 2, and Level 3 geoinformation products at 1.1 km spatial resolution. These products maintain uniform standards in format, projection, and spatial coverage. The dataset includes a comprehensive suite of land and atmospheric parameters such as atmospherically corrected surface reflectance, NDVI, snow cover, fire hotspots, burnt area, land and sea surface temperatures, and various cloud physical properties (e.g., cloud top temperature). By combining traditional and innovative remote sensing products with robust processing algorithms and state-of-the-art validation techniques, TIMELINE provides a unique, high-quality dataset for global change research.

The SAR4Tectonics project aims to provide open-access, global measurements of ground deformation in high-strain areas near tectonic plate boundaries. By leveraging the capabilities of the Persistent and Distributed Scatterer (PS/DS) technique with Sentinel-1 SAR images, the project seeks to deliver comprehensive and accurate data on ground deformation, which is crucial for understanding geological processes, assessing seismic risks in these regions, and advance our understanding of Earth's dynamic processes in general. The PS/DS technique offers significantly denser spatial coverage than GNSS, enabling the detection of more localized deformation signals. For the first time, such a vast and detailed dataset is made publicly available. By making this data openly accessible, the SAR4Tectonics project hopes to reduce the burden of SAR data processing for geoscientists, facilitating future studies.The project involved processing 6.5 years of SAR data, focusing on areas where the second invariant of strain exceeds 3 nanostrain per year. Various error corrections were employed, including tropospheric delay correction using ECMWF reanalysis data, ionospheric mitigation via CODE total electron content maps, and solid earth tide modeling. Additionally, the impact of vegetation and soil moisture on distributed scatterers was minimized through a full covariance matrix (phase linking) approach, and the results were calibrated using GNSS data. The final dataset includes line-of-sight average velocity maps, deformation time series, projection vectors, and reference plate modeled velocities.