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imageryBaseMapsEarthCover

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  • The PlanetScope satellite constellation, called ‘Flock’, consists of multiple launches of groups of individual Dove satellites into a 400 km orbit. Some of them were launched from the ISS. Therefore, on-orbit capacity is constantly improving in capability or quantity. Each Dove satellite is a CubeSat with a size of 10 x 10 x 34 cm. The complete PlanetScope constellation of approximately 130 satellites is able to image the entire land surface of the Earth every day, equating to a daily collection capacity of 200 million km². In 2014 the first Dove satellites started operationally acquiring images from the earth’s surface. The optical sensors mounted on the individual Dove satellites operate in the visual and near-infrared parts of the electromagnetic spectrum with a spatial resolution between 3 and 5 meters. A third generation of PlanetScope sensors (known as SuperDove or PSB.SD) is currently in orbit and is producing limited quantities of imagery with 5 spectral bands (BGRNIR + Red Edge). These satellites have the potential to produce imagery with 8 separate spectral bands. The PlanetScope data of this collection has been purchased by the German Space Agency with funds from the Ministry of Economy and is available for Germany-based researchers for scientific use. The data collection is maintained by the German Satellite Data Archive (D-SDA) of DLR’s Earth Observation Center and can be accessed via the EOWEB Geoportal. This collection comprises the PlanetScope L1B Basic Scene 4-band multispectral image products with three visual RGB and one near-infrared band. The Basic Scene product is a scaled Top of Atmosphere Radiance (at sensor) and sensor corrected product, providing imagery as seen from the spacecraft without correction for any geometric distortions. It has a scene-based framing, and is not mapped to a cartographic projection. If available, the Surface Reflectance layer which corrects for the effects of the Earth's atmosphere is added to the product.

  • 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

  • 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. With 5 m resolution and products covering areas up to 23.5 km x 23.5 km IRS LISS-IV multispectral data provide a cost effective solution for mapping tasks up to 1:25'000 scale.

  • The objective of the pan-European project CORINE Land Cover (CLC) is the provision of a unique and comparable data set of land cover for Europe and the delivery of regular updates to register also the land cover and land use changes over time. It is part of the European Union programme CORINE (Coordination of Information on the Environment). The mapping of the land cover and land use was performed on the basis of satellite remote sensing images. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). Further details: http://www.dlr.de/eoc/en/desktopdefault.aspx/tabid-11882/20871_read-48836/

  • 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. With 5 m resolution and products covering areas up to 70 km x 70 km IRS LISS-IV mono data provide a cost effective solution for mapping tasks up to 1:25'000 scale.

  • This collection contains radar image products of the German national TerraSAR-X mission acquired in StripMap mode. StripMap imaging allows for a spatial resolution of up to 3 m at a scene size of 30 km (across swath) x 50-1650 km (in orbit direction). TerraSAR-X is a sun-synchronous polar-orbiting, all-weather, day-and-night X-band radar earth observation mission realized in the frame of a public-private partnership between the German Aerospace Center (DLR) and Airbus Defence and Space. For more information concerning the TerraSAR-X mission, the reader is referred to: http://www.dlr.de/dlr/en/desktopdefault.aspx/tabid-10377/565_read-436/

  • 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. With 5 m resolution and products covering areas up to 70 km x 70 km IRS LISS-IV mono data provide a cost effective solution for mapping tasks up to 1:25'000 scale.

  • This product shows Snow Cover Duration (SCD) for the whole hydrological year (Sept. 1st of a given year until Aug. 31st of the next year). Information about extent, beginning, duration and melt of snow cover are important for climate research, hydrological applications, flood prediction and weather forecast. Climate change is influencing the characteristics and duration of snow cover, affecting landscape, hydrology, flora, fauna, and humans in equal measure. Therefore, precise information about the different snow parameters and their development over time are particularly important for various research fields. The “Global SnowPack” is a dataset containing information about snow cover parameters on a global scale. Overall, early season, and late season snow cover duration are included and allow detailed insights in the characteristics of this most relevant part of Earth’s cryosphere. The parameters are being derived from daily, operational MODIS snow cover products for every year since 2000. The negative effects of polar darkness and cloud coverage are compensated by applying several processing steps. Thereby, a unique global dataset can be provided that is characterized by its high accuracy, a spatial resolution of 500 meter and continuous future enhancements. For more information please also refer to: Dietz, A. J., C. Kuenzer, and S. Dech. 2015: Global SnowPack – “A new set of snow cover parameters to study status and dynamics of the planetary snow cover extent.“ accepted for publication in Remote Sensing Letters. Dietz, A. J., C. Conrad, C. Kuenzer, G. Gesell, and S. Dech. 2014. “Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data.” Remote Sensing 6 (12): 12752–75. doi:10.3390/rs61212752. Dietz, A. J., C. Kuenzer, and C. Conrad. 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 (11): 3879–3902. Dietz, A. J., C. Wohner, and C. Kuenzer. 2012. “European Snow Cover Characteristics between 2000 and 2011 Derived from Improved MODIS Daily Snow Cover Products.” Remote Sensing 4 (8): 2432–54. doi:10.3390/rs4082432.

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