WMS This Web Mapping Service provides access to geospatial demo map products within the Earth Observation Center (EOC). DLR EOC Demo Geoservice Manager Earth Observation Center (EOC), DLR Geospatial Service Manager Postal

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Weßling Bavaria 82234 Germany geoservice@dlr.de NONE NONE text/xml image/png application/atom+xml application/geopackage+sqlite3 application/json;type=geojson application/json;type=topojson application/json;type=utfgrid application/pdf application/rss+xml application/vnd.google-earth.kml+xml application/vnd.google-earth.kml+xml;mode=networklink application/vnd.google-earth.kmz application/vnd.mapbox-vector-tile application/x-sqlite3 image/geotiff image/geotiff8 image/gif image/jpeg image/png; mode=8bit image/svg+xml image/tiff image/tiff8 image/vnd.jpeg-png image/vnd.jpeg-png8 image/webp text/html; subtype=openlayers text/html; subtype=openlayers2 text/html; subtype=openlayers3 application/ld+json text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml; subtype=gml/3.1.1 text/html application/json XML INIMAGE BLANK JSON This Web Mapping Service provides access to geospatial demo map products within the Earth Observation Center (EOC). EPSG:3035 EPSG:3857 EPSG:4258 EPSG:4326 EPSG:25832 EPSG:32632 EPSG:900913 CRS:84 2.3385150451652477 40.933415 -24.978858 51.76534744663279 D4H_REFERENCE_WATER_MASK In the project "Demand-driven Data Services for Humanitarian Aid" (Data4Human), remote sensing data and other data sources are to be analysed in order to identify and demonstrate their possible use in the humanitarian context. This layer contains permanent reference water masks for areas which were analyzed during the monitoring of the project's area of interest. It identifies pixels classified as open and calm water, both permanent and seasonal. The reference water mask is derived by time-series analysis of archive Sentinel-2 imagery across a reference time-period to distinguish temporary flooded from permanent water. The method is described in detail in Wieland, M., Martinis S., 2019. A Modular Processing Chain for Automated Flood Monitoring from Multi-Spectral Satellite Data, Remote Sensing, 11(19), 2330. Please note that this layer is an experimental product within the framework of the project and see the corresponding disclaimer for further information. DLR EOC Data4Human ZKI Sentinel-1 floods reference water mask EPSG:4326 CRS:84 33.082571 40.933415 -24.978858 -13.395646 2019-01-01T03:07:26.000Z/2023-10-31T00:00:00.000Z/PT1S D4H_VALID_MASK In the project "Demand-driven Data Services for Humanitarian Aid" (Data4Human), remote sensing data and other data sources are to be analysed in order to identify and demonstrate their possible use in the humanitarian context. This layer contains valid observation pixels for areas which were analyzed during the monitoring of the project's area of interest in Mozambique. It distinguishes valid from invalid pixels, where invalid pixels are the result of no data values in the satellite image and/or atmospheric obstructions such as clouds or cloud-shadows (only relevant for optical satellite images). Please note that this layer is an experimental product within the framework of the project and see the corresponding disclaimer for further information. DLR EOC Data4Human ZKI Sentinel-1 floods valid pixel mask EPSG:4326 CRS:84 33.082571 40.933415 -24.978858 -13.395646 2019-01-01T03:07:26.000Z/2023-10-31T00:00:00.000Z/PT1S D4H_WATER_MASK_S1 In the project "Demand-driven Data Services for Humanitarian Aid" (Data4Human), remote sensing data and other data sources are to be analysed in order to identify and demonstrate their possible use in the humanitarian context. This layer contains the results of the water monitoring, which were classified as belonging to floodings and which are located within the project's area of interest in Mozambique. It depicts open surface water bodies as identified by an automated processing chain on the basis of C-Band Synthetic Aperture Radar (SAR) data acquired by the Sentinel-1 satellites. The underlying method uses a dynamic thresholding procedure and fuzzy-logic based refinement on VV-polarized intensity values. It is described in detail in Twele, A., Cao, W., Plank, S., Martinis, S., 2016. Sentinel-1 based flood mapping: a fully automated processing chain. International Journal of Remote Sensing, 37 (13), 2990-3004. Please note that this layer is an experimental product within the framework of the project and see the corresponding disclaimer for further information. DLR EOC Data4Human ZKI Sentinel-1 floods flood extent EPSG:4326 CRS:84 33.082571 40.933415 -24.978858 -13.395646 2019-01-01T03:07:26.000Z/2023-10-31T00:00:00.000Z/PT1S ECOLASS_CGC Crop Growth Condition ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Crop Growth Condition (CGC) EPSG:3035 CRS:84 2.647845736580539 6.502027938356638 49.31282997761663 51.003516519789905 ECOLASS_CRM Agriculture Crop Mask ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Agriculture Crop Mask (CRM) EPSG:3035 CRS:84 2.3385150451652477 6.537499203018807 49.29717625907437 51.76534744663279 ECOLASS_CRT Agriculture Crop Type ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Agriculture Crop Type (CRT) EPSG:3035 CRS:84 2.3385150451652477 6.537499203018807 49.29717625907437 51.76534744663279 ECOLASS_DLT Forest Dominant Leaf Type ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Forest Dominant Leaf Type (DLT) EPSG:3035 CRS:84 7.556549062849187 11.905218193547208 46.82208218104597 49.669310127999616 ECOLASS_GRA Grassland Mask ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Grassland Mask (GRA) GRM EPSG:3035 CRS:84 21.69041317833972 25.33253515641965 40.22533511420167 43.6270952738288 ECOLASS_GRC Grassland Incremental Change ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Grassland Incremental Change (GRC) EPSG:3035 CRS:84 21.69041317833972 25.33253515641965 40.22533511420167 43.6270952738288 ECOLASS_GRU Grassland Use Intensity ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Grassland Use Intensity (GRU) EPSG:3035 CRS:84 7.556549062849187 11.906048741659182 46.82208218104597 49.66931111601452 ECOLASS_IBU Imperviousness Built-Up Area ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Imperviousness Built-Up Area (IBU) EPSG:3035 CRS:84 7.556549062849187 11.905218193547208 46.82208218104597 49.669310127999616 ECOLASS_IMCC Imperviousness Change Classified ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Imperviousness Change Classified (IMCC) EPSG:3035 CRS:84 7.556539992849944 11.906471094885648 46.821812218308814 49.669491456740836 ECOLASS_IMD Imperviousness Degree ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Imperviousness Degree (IMD) EPSG:3035 CRS:84 7.556549062849187 11.905218193547208 46.82208218104597 49.669310127999616 ECOLASS_NLC New Landcover ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Newlandcover (NLC) EPSG:3035 CRS:84 7.556615905154676 11.906090721874955 46.82205048769406 49.66926400277193 ECOLASS_TCC Forest Tree Cover Change ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Forest Tree Cover Change (TCC) EPSG:3035 CRS:84 7.556549062849187 11.905218193547208 46.82208218104597 49.669310127999616 ECOLASS_TCD Forest Tree Cover Density ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Forest Tree Cover Density (TCD) EPSG:3035 CRS:84 7.556549062849187 11.905218193547208 46.82208218104597 49.669310127999616 ECOLASS_TCM Forest Tree Cover Mask ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Forest Tree Cover Mask (TCM) EPSG:3035 CRS:84 7.556549062849187 11.905218193547208 46.82208218104597 49.669310127999616 ECOLASS_TSI-GRA Time Series Indicator: Grassland Potential Change ECOLASS DLR EOC Evolution of Copernicus Land Services ecolass ECoLaSS Time Series Indicator (TSI) EPSG:3035 CRS:84 7.556406157057817 11.90522173089623 46.822079377596275 49.66939988682544 FCOVER_S2_ABUSSC_NL_2016 Sentinel-2 fractional vegetation cover (fCover) product for the Netherlands generated by processing 10 cloud-free Sentinel-2 tiles which covered the country on 8 September 2016. DLR EOC fcover Sentinel-2 Land cover Vegetation cover Soil cover Multispectral Imaging Netherlands opendata Unmixing Abus Scaled EPSG:3035 CRS:84 2.9997121758513026 4.579544021459421 50.45352327842689 51.451182205299816 HD_ADV_RF This layer contains the residential heat demand scenario 'advanced refurbishment' for the area of Baden Wuerttemberg at a spatial resolution of 100m x 100m. heat demand residential buildings LoD2 INSPIRE building type building age advanced refurbishment EPSG:3035 CRS:84 7.415572827174343 10.465142738636096 47.53143473914717 49.78820804157608 HD_NO_RF This layer contains the residential heat demand scenario 'no refurbishment' for the area of Baden Wuerttemberg at a spatial resolution of 100m x 100m. heat demand residential buildings LoD2 INSPIRE building type building age no refurbishment EPSG:3035 CRS:84 7.415572827174343 10.465142738636096 47.53143473914717 49.78820804157608 HD_USUAL_RF This layer contains the residential heat demand scenario 'usual refurbishment' for the area of Baden Wuerttemberg at a spatial resolution of 100m x 100m. heat demand residential buildings LoD2 INSPIRE building type building age usual refurbishment EPSG:3035 CRS:84 7.415572827174343 10.465142738636096 47.53143473914717 49.78820804157608