The Environmental Mapping and Analysis Program (EnMAP) is a German hyperspectral satellite mission that aims at monitoring and characterising the Earth's environment on a global scale. EnMAP measures and models key dynamic processes of Earth’s ecosystems by extracting geochemical, biochemical and biophysical parameters that provide information on the status and evolution of various terrestrial and aquatic ecosystems. The mission’s main objective is to study and decipher coupled environmental processes and to assist and promote the sustainable management of Earth’s resources. This collection includes Level 2A (atmospheric correction over land) products of the mission. 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 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 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 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 dataset is a derivative of the WSF3D raster dataset tailored for the web. As a tiled vector dataset, it enables dynamic client-side visualization of the WSF3D metrics

The dataset is based on the analysis of forest cover dynamics in the Paraguayan Chaco (northeastern part of Paraguay) between 1987 and 2020. The underlying forest masks were derived through annual forst classifications with a Random-Forest-Classifier trained on Landsat data from 1987 until 2020. The map shows the year in which the forest area was lost.

The dataset is based on an analysis combining Sentinel-1 (SAR), -2 (Multispectral) and GEDI (Global Ecosystem Dynamics Investigation, LiDAR) data to model vegetation structure information. The derived products show high-spatial resolution maps (10 m) of total canopy cover (cover density in %), Foliage height diversity (Fhd) index in meter, Plant area index (Pai) in meter and canopy height (rh95) in meter.

The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product displays the Cloud Fraction (CF) around the globe. Clouds play a crucial role in the Earth's climate system and have significant effects on trace gas retrievals. The radiometric cloud fraction is retrieved from the UV using the OCRA algorithm. Daily observations are binned onto a regular latitude-longitude grid. This product is created in the scope of the project INPULS. It develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.

This inventory of traffic areas in the city of Brunswick, Germany, is based on image sequences acquired during six flight campaigns at different times of the day and year in 2019 and 2020. Each aerial image is segmented by a neural network into the classes (1) Parking area, (2) Road, and (3) Access way, with the latter two classes differing in terms of their primary transportation function (mobility versus access). The individual segmentations are subsequently merged, since in addition to dedicated parking areas, those traffic areas that are regularly used for parking a motorized vehicle (e.g., at the curbside) are also to be classified as such. Furthermore, the multitemporal fusion enhances the robustness and completeness of the traffic area map (TAM). Potential applications include: urban planning, traffic modeling, and parking management. For more information about the project, the reader is referred to: https://elib.dlr.de/191145/1/Hellekes_et_al_2022_Parking_space_inventory_from_above.pdf