The Medium Resolution Imaging Spectrometer (MERIS) on Board ESA’s ENVISAT provides spectral high resolution image data in the visible-near infrared spectral region (412-900 nm) at a spatial resolution of 300 m. For more details on ENVISAT and MERIS see http://envisat.esa.int/ Spectral high resolution measurements allow to assess different water constituents in optically complex case-2 waters (IOCCG, 2000). The main groups of constituents are Chlorophyll, corresponding to living phytoplankton, suspended minerals or sediments and dissolved organic matter. They are characterised by their specific inherent optical properties, in particular scattering and absorption spectra. The Baltic Sea Water Constituents product was developed in a co-operative effort of DLR (Remote Sensing Technology Institute IMF, German Remote Sensing Data Centre DFD), Brockmann Consult (BC) and Baltic Sea Research Institute (IOW) in the frame of the MAPP project (MERIS Application and Regional Products Projects). The data are processed on a regular (daily) basis using ESA standard Level-1 and -2 data as input and producing regional specific value added Level-3 products. The regular data reception is realised at DFD ground station in Neustrelitz. For more details the reader is referred to http://wdc.dlr.de/sensors/meris/ and http://wdc.dlr.de/sensors/meris/documents/Mapp_ATBD_final_i3r0dez2001.pdf This product provides daily maps.

The Medium Resolution Imaging Spectrometer (MERIS) on Board ESA’s ENVISAT provides spectral high resolution image data in the visible-near infrared spectral region (412-900 nm) at a spatial resolution of 300 m. For more details on ENVISAT and MERIS see http://envisat.esa.int/ Spectral high resolution measurements allow to assess different water constituents in optically complex case-2 waters (IOCCG, 2000). The main groups of constituents are Chlorophyll, corresponding to living phytoplankton, suspended minerals or sediments and dissolved organic matter. They are characterised by their specific inherent optical properties, in particular scattering and absorption spectra. The Baltic Sea Water Constituents product was developed in a co-operative effort of DLR (Remote Sensing Technology Institute IMF, German Remote Sensing Data Centre DFD), Brockmann Consult (BC) and Baltic Sea Research Institute (IOW) in the frame of the MAPP project (MERIS Application and Regional Products Projects). The data are processed on a regular (daily) basis using ESA standard Level-1 and -2 data as input and producing regional specific value added Level-3 products. The regular data reception is realised at DFD ground station in Neustrelitz. For more details the reader is referred to http://wdc.dlr.de/sensors/meris/ and http://wdc.dlr.de/sensors/meris/documents/Mapp_ATBD_final_i3r0dez2001.pdf This product provides 10-day maps.

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 sulphur dioxide (SO2) concentration around the globe. Sulphur dioxide enters the atmosphere through volcanic eruptions and human-related activities. Daily observations are binned onto a regular latitude-longitude grid. This product is created in the scope of the project INPULS. The DLR INPULS project 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

This product shows the snow cover duration for a hydrological year. Its beginning differs from the calendar year, since some of the precipitation that falls in late autumn and winter falls as snow and only drains away when the snow melts in the following spring or summer. The meteorological seasons are used for subdivision and the hydrological year begins in autumn and ends in summer. The snow cover duration is made available for three time periods: the snow cover duration for the entire hydrological year (SCD), the early snow cover duration (SCDE), which extends from autumn to midwinter (), and the late snow cover duration (SCDL), which in turn extends over the period from mid-winter to the end of summer. For the northern hemisphere SCD lasts from September 1st to August 31st, for the southern hemisphere it lasts from March 1st to February 28th/29th. The SCDE lasts from September 1st to January 14th in the northern hemisphere and from March 1st to July 14th in the southern hemisphere. The SCDL lasts from January 15th to August 31st in the northern hemisphere and from July 15th to February 28th/29th in the southern hemisphere. The “Global SnowPack” is derived from daily, operational MODIS snow cover product for each day since February 2000. Data gaps due to polar night and cloud cover are filled in several processing steps, which provides a unique global data set characterized by its high accuracy, spatial resolution of 500 meters and continuous future expansion. It consists of the two main elements daily snow cover extent (SCE) and seasonal snow cover duration (SCD; full and for early and late season). Both parameters have been designated by the WMO as essential climate variables, the accurate determination of which is important in order to be able to record the effects of climate change. Changes in the largest part of the cryosphere in terms of area have drastic effects on people and the environment. For more information please also refer to: Dietz, A.J., Kuenzer, C., Conrad, C., 2013. Snow-cover variability in central Asia between 2000 and 2011 derived from improved MODIS daily snow-cover products. International Journal of Remote Sensing 34, 3879–3902. https://doi.org/10.1080/01431161.2013.767480 Dietz, A.J., Kuenzer, C., Dech, S., 2015. Global SnowPack: a new set of snow cover parameters for studying status and dynamics of the planetary snow cover extent. Remote Sensing Letters 6, 844–853. https://doi.org/10.1080/2150704X.2015.1084551 Dietz, A.J., Wohner, C., Kuenzer, C., 2012. European Snow Cover Characteristics between 2000 and 2011 Derived from Improved MODIS Daily Snow Cover Products. Remote Sensing 4. https://doi.org/10.3390/rs4082432 Dietz, J.A., Conrad, C., Kuenzer, C., Gesell, G., Dech, S., 2014. Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data. Remote Sensing 6. https://doi.org/10.3390/rs61212752 Rößler, S., Witt, M.S., Ikonen, J., Brown, I.A., Dietz, A.J., 2021. Remote Sensing of Snow Cover Variability and Its Influence on the Runoff of Sápmi’s Rivers. Geosciences 11, 130. https://doi.org/10.3390/geosciences11030130

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational NO2 total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The total NO2 column is retrieved from GOME solar back-scattered measurements in the visible wavelength region (425-450 nm), using the Differential Optical Absorption Spectroscopy (DOAS) method. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/

Indian Remote Sensing satellites (IRS) are a series of Earth Observation satellites, built, launched and maintained by Indian Space Research Organisation. The IRS series provides many remote sensing services to India and international ground stations. The revisit capability of only 5 days and the products coverage size of 370 km x 370 km make AWiFS products a valuable source for application fields such forestry and environmental monitoring

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.

SWACI is a research project of DLR supported by the State Government of Mecklenburg-Vorpommern. Radio signals, transmitted by modern communication and navigation systems may be heavily disturbed by space weather hazards. Thus, severe temporal and spatial changes of the electron density in the ionosphere may significantly degrade the signal quality of various radio systems which even may lead to a complete loss of the signal. By providing specific space weather information, in particular now- and forecast of the ionospheric state, the accuracy and reliability of impacted communication and navigation systems shall be improved. The equivalent slab thickness is a measure of the width of the shape of the vertical electron density profile of the ionosphere. The equivalent slab thickness is defined by the ratio of the total electron content (TEC) and the peak electron density of the local ionosphere. To compute the peak electron density, vertical sounding data from different ionosonde stations are used. The corresponding TEC data are extracted from the SWACI TEC maps. For more details see http://swaciweb.dlr.de/data-and-products/public/slabthickness/?L=1.

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