Geoservice Maps List of Web Maps Contexts

Abstract: 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. 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 on a scale of 1:100,000. The first CLC data base CLC1990, which was finalised in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. In the project CORINE Land Cover 2000 (CLC2000), an update of the database and a mapping of changes have been accomplished using the year 2000 as reference. The project CLC2000, which resulted in area-wide land use and land use change maps of Germany, was led by the German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR) on behalf of the Federal Environmental Agency (UBA). With CLC2000 a reliable, objective and comparable data base for the description of the current situation (at 2000) and the analysis of changes during the decade between 1990 and 2000 is available. Integrated in the European GMES activities, a further update of CORINE Land Cover was done in 37 European countries with the reference year 2006. The project CLC2006 in Germany was again performed by the German Remote Sensing Data Center, on behalf of the Federal Environment Agency (UBA). The update CORINE Land Cover 2006 for Germany is available since February 2010. Besides the status in 2006, an analysis of the changes between 2000 and 2006 is available. More details: http://www.corine.dfd.dlr.de/intro_en.html The CLC2000 project in Germany was executed using financial support by DG Regio and the German Federal Ministry on Environment, Nature Conservation and Nuclear Safety (BMU) on behalf of the German Federal Environmental Agency (UBA), project no. UBA FKZ 201 12 209. The CLC2006 project in Germany was under the responsibility of the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) and was performed on behalf of the Federal Environment Agency (UBA), project no. UBA FKZ 3707 12 200 and UBA FKZ 3708 12 200.

Keywords:DLR, CORINE, CORINE2000, CORINE2006, Land cover, Germany

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Abstract: MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment (from http://modis.gsfc.nasa.gov/). This mosaic has been generated from TERRA and AQUA products between 30 Sept. to 03 Oct. 2011 he MODIS data used in this product were obtained through the online Data Pool at the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota (https://lpdaac.usgs.gov/get_data).

Keywords:DLR, MODIS-DE, TERRA, AQUA, Orthoimagery

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Abstract:These EOC Basemaps are projected in Antarctic Polar Stereographic coordinate system with WGS84 datum. The EPSG code for this coordinate system is EPSG:3031. More details can be found at http://epsg.io/3031

Keywords:Antarctic Polar Stereographic, EPSG:3031, Basemap, EOC, DLR

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Abstract:These EOC Basemaps are projected in Lambert Azimuthal Equal Area (LAEA) coordinate system using the European Terrestrial Reference System 1989 (ETRS89). The EPSG code for this coordinate system is EPSG:3035. More details can be found at http://epsg.io/3035

Keywords:Lambert Azimuthal Equal Area, EPSG:3035, Basemap, EOC, DLR

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Abstract:These EOC Basemaps are projected in Pseudo-Mercator (or Spherical Mercator) coordinate system with WGS84 datum. The EPSG code for this coordinate system is EPSG:3857. More details can be found at http://epsg.io/3857

Keywords:Pseudo-Mercator, EPSG:3857, Basemap, EOC, DLR

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Abstract:These EOC Basemaps are projected in Arctic Polar Stereographic coordinate system with WGS84 datum. The EPSG code for this coordinate system is EPSG:3995. More details can be found at http://epsg.io/3995

Keywords:Arctic Polar Stereographic, EPSG:3995, Basemap, EOC, DLR

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Abstract:These EOC Basemaps are rendered using the World Geodetic System 1984 (WGS84) Geodetic coordinate system. The EPSG code for this coordinate system is EPSG:4326. More details can be found at http://epsg.io/4326

Keywords:World Geodetic System, EPSG:4326, Basemap, EOC, DLR

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Abstract: 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 (September 1st - August 31st of the next calendar year), early season (September 1st - January 15th of the next calendar year), and late season (January 16th - August 31st) snow cover duration are included and allow detailed insights in the characteristics of this most relevant part of Earths 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.

Keywords:DLR, EOC, Land, Global Snowpack, Snow Cover Duration Early Season, SCDES, Snow Cover Duration, SCD, Snow Cover Duration Late Season, SCDLS

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Abstract: The GUF® maps show two land cover categories (e. g. in a B&W representation): Built-up areas (vertical structures only) in black and non-built-up surfaces in white; in addition, areas of no coverage by theTSX/TDX satellites (NoData) are coded in grey (most parts of the oceans). The focus on two categories clearly highlights the settlement patterns, improving the ability to analyze and compare them with other built-up areas across the world, in an urban or in a rural context. Unlike previous approaches, the fully automatic evaluation procedure detects the characteristic vertical structures of human habitations are primarily buildings. In contrast, areas used for infrastructure purposes, like roads, are not mapped. This is why broad urban canyons or expanses of greenery within the cities are shown as white corridors and patches.

Keywords:Land Cover, Land, Urbanization, Global Mapping, Settlement Patterns, TerraSAR-X, TanDEM-X, Texture, GUF, Global Urban Footprint

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Abstract: The GUF® maps show two land cover categories (e. g. in a B&W representation): Built-up areas (vertical structures only) in black and non-built-up surfaces in white; in addition, areas of no coverage by theTSX/TDX satellites (NoData) are coded in grey (most parts of the oceans). The focus on two categories clearly highlights the settlement patterns, improving the ability to analyze and compare them with other built-up areas across the world, in an urban or in a rural context. Unlike previous approaches, the fully automatic evaluation procedure detects the characteristic vertical structures of human habitations are primarily buildings. In contrast, areas used for infrastructure purposes, like roads, are not mapped. This is why broad urban canyons or expanses of greenery within the cities are shown as white corridors and patches.

Keywords:Land Cover, Land, Urbanization, Global Mapping, Settlement Patterns, TerraSAR-X, TanDEM-X, Texture, GUF, Global Urban Footprint

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Abstract: The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key instrument aboard the American satellites Terra and Aqua. The MODIS-EU image mosaic is a seamless true color composite of all Terra and Aqua passes received at DLR during one day. Daily and Near Real Time (NRT) products are available. For the composite, MODIS channels 1, 4, 3 are used. The channels are re-projected, radiometrically enhanced, and seamlessly stitched to obtain a visually appealing result. Terra passes from north to south across the equator in the morning, while Aqua passes the equator south to north in the afternoon. Both MODIS instruments are viewing the entire Earth surface every 1 to 2 days, acquiring data in 36 spectral bands. These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment

Keywords:DLR, EOC, MODIS-EU, Orthoimagery, TERRA, AQUA

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Abstract: This map shows daily (about 3 days old) products of different trace gases measured by the Global Ozone Monitoring Experiment-2 (GOME-2) which was launched on October 2006 on board EUMETSAT's Meteorological Operational Satellite (MetOp-A) and the following mission MetOp-B which became fully operational spring 2013. A wide range of atmospheric trace constituents are measured, with the emphasis on global ozone distributions. Furthermore cloud properties and intensities of ultraviolet radiation are retrieved. DLR generates operational GOME-2/MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). GOME-2 daily products are available about three days after sensing. Within this map layers of 9 trace gases of both missions can be loaded. All these layers in combination with different basemap layers can be selected separately or in combination to create overlays for example to compare layers of different missions.

Keywords:DLR, EOC, Atmos, MetOp-A, MetOp-B, GOME-2, O3M-SAF, Total Column, Atmosphere, Remote Sensing, Daily, Ozone, BrO, NO2, NO2Tropo, H2O, HCHO, CF, COT, CTP

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Abstract: This map shows latest combined products (MetOp-AB) generated out of missions MetOp-A and MetOp-B of different trace gases measured by the Global Ozone Monitoring Experiment-2 (GOME-2) which was launched on October 2006 on board EUMETSAT's Meteorological Operational Satellite (MetOp-A) and the following mission MetOp-B which became fully operational spring 2013. A wide range of atmospheric trace constituents are measured, with the emphasis on global ozone distributions. Furthermore cloud properties and intensities of ultraviolet radiation are retrieved. DLR generates operational GOME-2/MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). GOME-2 latest MetOp-AB products are available about two hours after sensing. Within this map layers of 9 trace gases of both missions can be loaded. All these layers in combination with different basemap layers can be selected separately or in combination.

Keywords:DLR, EOC, Atmos, MetOp-A, MetOp-B, MetOp-AB, GOME-2, Total Column, Ozone, BRO, NO2, SO2, NO2Tropo, H2O, HCHO, CF, COT, CTP, Atmosphere, Remote Sensing, NRT, latest

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Abstract: This map shows combined products (MetOp-AB) of yesterday generated out of missions MetOp-A and MetOp-B of different trace gases measured by the Global Ozone Monitoring Experiment-2 (GOME-2) which was launched on October 2006 on board EUMETSAT's Meteorological Operational Satellite (MetOp-A) and the following mission MetOp-B which became fully operational spring 2013. A wide range of atmospheric trace constituents are measured, with the emphasis on global ozone distributions. Furthermore cloud properties and intensities of ultraviolet radiation are retrieved. DLR generates operational GOME-2/MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). GOME-2 previous MetOp-AB products are available shortly after midnight (UTC). Within this map layers of 9 trace gases of both missions can be loaded. All these layers in combination with different basemap layers can be selected separately or in combination.

Keywords:DLR, EOC, Atmos, MetOp-A, MetOp-B, MetOp-AB, GOME-2, Total Column, Ozone, BRO, NO2, SO2, NO2Tropo, H2O, HCHO, CF, COT, CTP, Atmosphere, Remote Sensing, NRT, previous

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Abstract: This map shows elevation products of the X-SAR/SRTM mission covering the globe between 60° North and 58° South with a resolution of approximately 25 x 25 m. X-SAR/SRTM was an innovative way of collecting highly accurate topographic information using spaceborne radar instruments. Three mosaics have been generated: the SRTM X-SAR Elevation, Hillshade and Error mosaic. The SRTM X-SAR Elevation Mosaic has been generated by grouping and mosaicking the original elevation files. The SRTM X-SAR Hillshade Mosaic is a greyscale shaded relief based on the SRTM X-SAR Elevation Mosaic. Combined with the latter, it can be used to add a 3D effect and enhance the visual resolution by pronouncing peaks and valleys. Finally, the SRTM X-SAR Error Mosaic is based on the height error map and provides a local measure of the achieved accuracy. It is statistically determined from a neighborhood of image cells mainly considering the phase and baseline stability. Thus it describes the precision relative to the surrounding. The determination of the absolute accuracy requires the consideration of reference measures. All these layers in combination with different basemap layers can be selected separately or in combination to create the overlays looked-for.

Keywords:DLR, SRTM, X-SAR, DEM, HEM, Hillshade, Elevation

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