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imageryBaseMapsEarthCover

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  • 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

  • This product shows Snow Cover Duration Late Season (SCDLS). SCDLS represents the SCD between between January 16th and August 31st of a given hydrological 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.

  • This collection contains synthesized Sentinel-2 Level 3A surface reflectances for Germany on a monthly basis computed by the WASP processor (which utilizes L2A products derived from the MAJA processor). During the Level 3A processing, atmospherically corrected data from a predefined time interval are collected, weighted based on temporal distance and integrated to a new data set with the aim of removing clouds. Thereby, monthly Sentinel-2 Level 3A composites are provided for whole Germany. Please see https://logiciels.cnes.fr/en/content/maja for additional information on the MAJA product. Further Sentinel-2 Level 3A data computed using MAJA are available on the following website: https://theia.cnes.fr

  • 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 product coverage size of 800 km x 800 km make WiFS products a valuable source for application fields such as flood and snow melt monitoring.

  • 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.

  • 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 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

  • This serie clc5 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 (LBM-DE) 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.

  • The RapidEye Earth observation system comprises five satellites equipped with high-resolution optical sensors. Co-funded by the German Federal Government, the fleet of satellites was launched from the Baikonur cosmodrome in Kazakhstan in 2008. RapidEye is now being owned by Planet Labs, Inc. The RapidEye constellation is capable of taking images of the Earth's surface at high repeat rates. Each point on Earth can be imaged at least once per day. With a spatial resolution of 6.5 m the 5-band sensors onboard the RapidEye satellites operate in the visible and near-infrared portions of the electromagnetic spectrum. For more information see http://www.dlr.de/rd/en/desktopdefault.aspx/tabid-2440/3586_read-5336/ or https://www.planet.com/products/planet-imagery/ The RapidEye Science Archive (RESA), which allows Germany-based researchers to apply for free RapidEye imagery, is now being operated by Planet Labs Germany GmbH. For more information see https://resa.planet.com/

  • 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 satellite has two panchromatic cameras that were especially designed for in flight stereo viewing.

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