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  • Czech Technical University Prague  (1)
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    Czech Technical University Prague
    In:  EPIC331st EARSeL Symposium and 35th General Assembly 2011, Prague, CZ, 2011-05-30-2011-06-0231st EARSeL Symposium and 35th General Assembly 2011, Czech Technical University Prague, C25(A2484), pp. 10 p.
    Publication Date: 2019-07-16
    Description: The task of the ESA Data User Element DUE PERMAFROST project is to build-up an Earth Observation service for permafrost applications with extensive involvement of the permafrost research community. The DUE PERMAFROST remote sensing products are ‘Land Surface Temperature’ (LST), ‘Surface Soil Moisture’ (SSM), ‘Frozen/ Thawed Surface Status’ (Freeze/Thaw), ‘Terrain’, ‘Land Cover’ (LC), and ‘Surface Waters’. A major component is the evaluation of the DUE PERMAFROST products to test their scientific validity for high-latitude permafrost landscapes. There are no standard evaluation methods for this range of remote sensing products, specifically not for these latitudes. Evaluation experiments and intercomparison is done on a case-by-case basis, adding value and experience in validating products for these regions. A significant challenge in the evaluation of remote sensing products for high-latitude permafrost landscapes are the very sparse ground data. We relay on ground data provided by the Users and by international programmes. The primary international programme is the Global Terrestrial Network for Permafrost (GTN-P) initiated by the International Permafrost Association (IPA). Leading projects are the networks of the 'Circumpolar Active Layer Monitoring' (CALM) and the 'Thermal State of Permafrost' (TSP). Prime sites for testing methods and scaling are the long-term Russian-German Samoylov Station in the Lena River Delta (Arctic Siberia), and the tundra and taiga-tundra transition region in Western Siberia (RU). The results of the first evaluations of LST, SSM and Freeze/ Thaw using GTN-P and User’s data show the usability of the DUE PERMAFROST products for high-latitude permafrost landscapes.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , notRev
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  • 2
    Publication Date: 2019-07-16
    Description: Permafrost is an essential climate variable (ECV). It is a subsurface phenomenon which cannot be directly measured with remotely sensed data. However, many parameters which influence the ground thermal regime and surface indicators can be captured with satellite data. Those are e.g. land surface temperature, land cover and snow parameters, soil moisture and terrain changes. The capabilities of currently available remotely sensed datasets need to be assessed with respect to operational monitoring and their value enhanced by a synergistic use. Within the ESA DUE Permafrost project a wide range of EO datasets are investigated and integrated in an information system with extensive involvement of the permafrost research community. This comprises pan-boreal/arctic to regional and local scale investigations. A number of relevant global datasets do already exist or are currently in development. Land surface temperature is available from MODIS and AATSR on global scale. ESA projects such as GlobCover, GlobCarbon and GlobSnow provide important land cover parameters. An operational soil moisture monitoring system is currently provided by EUMETSAT from MetOp ASCAT. The majority of these datasets has been developed and validated outside of the circumpolar permafrost zone. The assessment of these datasets is thus an integral part of the project. The information system will comprise those global datasets and also regional and local scale monitoring results. The latter cover sites in Alaska, Mackenzie basin, Southern Yakutia and Laptev and East Siberian Sea region. The database setup considers use by permafrost modelers and scientists working on local scale (hydrology, geomorphology, botany etc.). A combination with a WebGIS portal will allow efficient dissemination of results and free access. In this paper we present the current design of the information system.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , notRev
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