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imageryBaseMapsEarthCover

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  • Digitale Orthophotos flächendeckend für das Gebiet der Stadt Hamm, in belaubtem Zustand, im Blattschnitt der DGK

  • 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 PAN data provide a cost effective solution for mapping tasks up to 1:25'000 scale.

  • 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 dataset clc5 (2018) describes the landscape according to the CORINE Land Cover (CLC) nomenclature. These classes contain mainly information about landcover mixed with some aspects of landuse. CLC5 is based on the more detailed German landcover model from 2018 (LBM-DE2018) which uses separate classes for landcover and landuse and attribute-information about percentage of vegetation and sealing. The mimimum unit for an object is 1 ha. For the CLC5 dataset landcover and landuse classes are combined to unique CLC-classes taking into account the percentage of vegetation and sealing , followed by a generalisation process.

  • 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. IRS LISS-III data are well suited for agricultural and forestry monitoring tasks.

  • The Sentinel-2 fractional vegetation cover (fCover) product for the Netherlands was produced as part of the NextGEOSS project at the German Aerospace Center (DLR). The goal is to derive abundance maps from atmospherically corrected Sentinel-2 multispectral images for: photosynthetically active vegetation (PV); and for combined non-photosynthetically active vegetation (NPV) and bare soil (BS). The fCover product for the Netherlands has been generated by processing 10 cloud-free Sentinel-2 tiles which covered the country on 8 September 2016. The map has a spatial resolution of 60m x 60m. The Sentinel-2 scene classification layer was used to ensure that the spectral unmixing was only performed on areas of vegetation or soil. The abundance maps were made by performing MESMA unmixing on each pixel from an endmember library of PV and combined NPV + BS spectra. The purest pixels in a scene, called endmembers, were extracted using the Spatial-Spectral Endmember Extraction (SSEE) approach. The PV and NPV+BS endmembers were classified with a random forest approach and selected to form the spectral library. The spectral library was used in the µMESMA unmixing to get the PV and NPV+BS abundances.

  • 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: https://www.dlr.de/en/eoc/research-transfer/projects-missions/corine-land-cover

  • The hyperspectral instrument DESIS (DLR Earth Sensing Imaging Spectrometer) is one of four possible payloads of MUSES (Multi-User System for Earth Sensing), which is mounted on the International Space Station (ISS). DLR developed and delivered a Visual/Near-Infrared Imaging Spectrometer to Teledyne Brown Engineering, which was responsible for integrating the instrument. Teledyne Brown designed and constructed, integrated and tested the platform before delivered to NASA. Teledyne Brown collaborates with DLR in several areas, including basic and applied research for use of data. DESIS is operated in the wavelength range from visible through the near infrared and enables precise data acquisition from Earth's surface for applications including fire-detection, change detection, maritime domain awareness, and atmospheric research. Three product types can be ordered, which are Level 1B (systematic and radiometric corrected), Level 1C (geometrically corrected) and Level 2A (atmospherically corrected). The spatial resolution is about 30m on ground. DESIS is sensitive between 400nm and 1000nm with a spectral resolution of about 3.3nm. DESIS data are delivered in tiles of about 30x30km. For more information concerning DESIS the reader is referred to https://www.dlr.de/de/eoc/forschung-transfer/projekte-und-missionen/desis

  • This land cover classification of Germany was created using Sentinel-2 imagery from the years 2015 to 2017 and LUCAS 2015 in-situ reference data (https://ec.europa.eu/eurostat/web/lucas). It contains seven land cover types: (1) artificial land, (2) open soil, (3) high seasonal vegetation, (4) high perennial vegetation, (5) low seasonal vegetation, (6) low perennial vegetation and (7) water with a spatial resolution of 10m x 10m. For further information, please see the following publication: https://doi.org/10.1016/j.jag.2020.102065