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  • Mit dem Europäischen Fond für regionale Entwicklung (EFRE) – Programm "Nachhaltige Stadtentwicklung" unterstützt das Sächsische Ministerium für Regionalentwicklung (SMR) Städte und Gemeinden mit mehr als 5.000 Einwohnern bei der Entwicklung benachteiligter Stadtgebiete. Die Nachhaltige Stadtentwicklung umfasst zwei Vorhabensteile. Die "Integrierte Stadtentwicklung" (ISE) und die "Integrierte Brachflächenentwicklung" (IBE). Dieser Kartenviewer zeigt die Programmgemeinden des Vorhabensteils Integrierte Brachflächenentwicklung der Förderperiode 2014 - 2020 und stellt die jeweiligen Fördervorhaben dar. Über eine Verlinkung gelangt man auf die Internetseiten der Kommunen zu den Fördervorhaben.

  • 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 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.

  • Grids are derived from DWD stations and legally and qualitatively equivalent partner stations in Germany.

  • This product shows Snow Cover Duration Early Season (SCDES). SCDES represents the SCD between September 1st and January 15th 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.

  • 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.

  • Grids are derived from DWD stations and legally and equivalent partner stations in Germany.

  • 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.

  • 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/ This product developed in the frame of the MAPP project (MERIS Application and Regional Products Projects) represents the chlorophyll concentration of the North Sea derived from MERIS data. The product is a cooperative effort of DLR-DFD and the Institute for Coastal Research at the GKSS Research Centre Geesthacht. DFD pre-processed up to the value added level whenever MERIS data for the North Sea region was received and positively checked for a water area large enough for a suitable interpretation. 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.

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