WMS This Web Map Service provides access to land coverage products within the Earth Observation Center (EOC). DLR EOC Germany Global Urban Footprint GUF CORINE CORINE_1990 CORINE_2000 CORINE_2006 Land cover Global SnowPack GSP Geoservice Manager Earth Observation Center (EOC), DLR Geospatial Service Manager Postal

Münchener Straße 20

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 Map Service provides access to land coverage products within the Earth Observation Center (EOC). EPSG:3031 EPSG:3034 EPSG:3035 EPSG:3038 EPSG:3039 EPSG:3040 EPSG:3041 EPSG:3042 EPSG:3043 EPSG:3044 EPSG:3045 EPSG:3046 EPSG:3047 EPSG:3048 EPSG:3049 EPSG:3050 EPSG:3051 EPSG:3857 EPSG:900913 EPSG:3995 EPSG:4258 EPSG:4326 EPSG:25832 EPSG:25833 EPSG:32661 EPSG:32761 EPSG:31466 EPSG:31467 EPSG:31468 EPSG:31469 EPSG:32601 EPSG:32602 EPSG:32603 EPSG:32604 EPSG:32605 EPSG:32606 EPSG:32607 EPSG:32608 EPSG:32609 EPSG:32610 EPSG:32611 EPSG:32612 EPSG:32613 EPSG:32614 EPSG:32615 EPSG:32616 EPSG:32617 EPSG:32618 EPSG:32619 EPSG:32620 EPSG:32621 EPSG:32622 EPSG:32623 EPSG:32624 EPSG:32625 EPSG:32626 EPSG:32627 EPSG:32628 EPSG:32629 EPSG:32630 EPSG:32631 EPSG:32632 EPSG:32633 EPSG:32634 EPSG:32635 EPSG:32636 EPSG:32637 EPSG:32638 EPSG:32639 EPSG:32640 EPSG:32641 EPSG:32642 EPSG:32643 EPSG:32644 EPSG:32645 EPSG:32646 EPSG:32647 EPSG:32648 EPSG:32649 EPSG:32650 EPSG:32651 EPSG:32652 EPSG:32653 EPSG:32654 EPSG:32655 EPSG:32656 EPSG:32657 EPSG:32658 EPSG:32659 EPSG:32660 EPSG:32701 EPSG:32702 EPSG:32703 EPSG:32704 EPSG:32705 EPSG:32706 EPSG:32707 EPSG:32708 EPSG:32709 EPSG:32710 EPSG:32711 EPSG:32712 EPSG:32713 EPSG:32714 EPSG:32715 EPSG:32716 EPSG:32717 EPSG:32718 EPSG:32719 EPSG:32720 EPSG:32721 EPSG:32722 EPSG:32723 EPSG:32724 EPSG:32725 EPSG:32726 EPSG:32727 EPSG:32728 EPSG:32729 EPSG:32730 EPSG:32731 EPSG:32732 EPSG:32733 EPSG:32734 EPSG:32735 EPSG:32736 EPSG:32737 EPSG:32738 EPSG:32739 EPSG:32740 EPSG:32741 EPSG:32742 EPSG:32743 EPSG:32744 EPSG:32745 EPSG:32746 EPSG:32747 EPSG:32748 EPSG:32749 EPSG:32750 EPSG:32751 EPSG:32752 EPSG:32753 EPSG:32754 EPSG:32755 EPSG:32756 EPSG:32757 EPSG:32758 EPSG:32759 EPSG:32760 CRS:84 -180.0 180.002616238467 -90.0 90.00000000000001 BIOCLIS_ARI_DE_P1D Describes the increased health risk posed by air pollutants features ari_view EPSG:4326 CRS:84 5.866312994124358 15.041914156675006 47.27011141054802 55.05884836691795 2026-01-01T00:00:00.000Z/2026-04-02T00:00:00.000Z/P1D BIOCLIS_NO2_DE_P1D Stickstoff-Dioxid (NO2) - Konzentration in microgram/m³ features no2_view EPSG:4326 CRS:84 5.866312994124358 15.041914156675006 47.27011141054802 55.05884836691795 2026-01-01T00:00:00.000Z/2026-04-02T00:00:00.000Z/P1D BIOCLIS_O3_DE_P1D Ozon (O3) - Konzentration in microgram/m³ features o3_view EPSG:4326 CRS:84 5.866312994124358 15.041914156675006 47.27011141054802 55.05884836691795 2026-01-01T00:00:00.000Z/2026-04-02T00:00:00.000Z/P1D BIOCLIS_PM10_DE_P1D Fine dust with particle diameter <10µm features pm10_view EPSG:4326 CRS:84 5.866312994124358 15.041914156675006 47.27011141054802 55.05884836691795 2026-01-01T00:00:00.000Z/2026-04-02T00:00:00.000Z/P1D BIOCLIS_PM25_DE_P1D Fine dust with particle diameter <2.5µm features pm25_view EPSG:4326 CRS:84 5.866312994124358 15.041914156675006 47.27011141054802 55.05884836691795 2026-01-01T00:00:00.000Z/2026-04-02T00:00:00.000Z/P1D BIOCLIS_SO2_DE_P1D The data set describes the sulfur dioxide (SO2) concentration in micrograms/m3. features so2_view EPSG:4326 CRS:84 5.866312994124358 15.041914156675006 47.27011141054802 55.05884836691795 BIOCLIS_UTCI_DE_P1D Describes thermal stress on the human body depending on environmental conditions. features utci_view EPSG:4326 CRS:84 5.866312994124358 15.041914156675006 47.27011141054802 55.05884836691795 2026-01-01T00:00:00.000Z/2026-04-02T00:00:00.000Z/P1D CORINE_LAND_COVER_1990_1000x1000_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_1990 Germany Land cover EPSG:3044 CRS:84 5.530694646228771 15.995047805309904 47.045037940006345 55.20855566751543 text/xml CORINE_LAND_COVER_1990_1000x1000_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_1990 Germany Land cover EPSG:3035 CRS:84 5.42024168738056 15.89226444527976 47.08447610240508 55.2153954795507 text/xml CORINE_LAND_COVER_1990_100x100_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_1990 Germany Land cover EPSG:3044 CRS:84 5.5342950809400575 15.980146339650538 47.048330537704224 55.20316453259274 text/xml CORINE_LAND_COVER_1990_100x100_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_1990 Land cover EPSG:3035 CRS:84 5.420546937708305 15.884070741969376 47.0847763723909 55.21272012224854 text/xml CORINE_LAND_COVER_1990_250x250_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_1990 Land cover EPSG:3044 CRS:84 5.531084345449721 15.982629689808396 47.045544010719155 55.20406339036345 text/xml CORINE_LAND_COVER_1990_250x250_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_1990 Land cover EPSG:3035 CRS:84 5.420496066043751 15.88413596170849 47.08477637239088 55.21316943018539 text/xml CORINE_LAND_COVER_2000_1000x1000_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2000 Land cover EPSG:3044 CRS:84 5.530694646228771 15.995047805309904 47.045037940006345 55.20855566751543 text/xml CORINE_LAND_COVER_2000_1000x1000_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2000 Land cover EPSG:3035 CRS:84 5.42024168738056 15.89226444527976 47.08447610240508 55.2153954795507 text/xml CORINE_LAND_COVER_2000_100x100_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2000 Land cover EPSG:3044 CRS:84 5.531162272253405 15.980146339650538 47.045645124280014 55.2031649193252 text/xml CORINE_LAND_COVER_2000_100x100_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE_2000 CORINE Land cover EPSG:3035 CRS:84 5.420546937708305 15.884070741969376 47.0847763723909 55.21272012224854 text/xml CORINE_LAND_COVER_2000_250x250_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2000 Land cover EPSG:3044 CRS:84 5.531084345449721 15.982629689808396 47.045544010719155 55.20406339036345 text/xml CORINE_LAND_COVER_2000_250x250_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2000 Land cover EPSG:3035 CRS:84 5.420496066043747 15.884135961708491 47.0847763723909 55.21316943018542 text/xml CORINE_LAND_COVER_2006_1000x1000_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2006 Land cover EPSG:3044 CRS:84 5.542338522743184 15.600263026892197 47.13246410246824 55.07372491101967 text/xml CORINE_LAND_COVER_2006_1000x1000_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2006 Land cover EPSG:3035 CRS:84 5.4510372036779176 15.514883088149034 47.16075039345486 55.08138686865046 text/xml CORINE_LAND_COVER_2006_100x100_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2006 Land cover EPSG:3044 CRS:84 5.5425704100090885 15.588981909508547 47.13291251625102 55.07102599022314 text/xml CORINE_LAND_COVER_2006_100x100_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2006 Land cover EPSG:3035 CRS:84 5.4510372036779176 15.508657019069291 47.16097630685251 55.081398919115614 text/xml CORINE_LAND_COVER_2006_250x250_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2006 Land cover EPSG:3044 CRS:84 5.5425317648178645 15.592152678826443 47.13278447287694 55.071476182384636 text/xml CORINE_LAND_COVER_2006_250x250_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2006 Land cover EPSG:3035 CRS:84 5.4510372036779176 15.510991804132184 47.16089161923299 55.08139440933098 text/xml CORINE_LAND_COVER_CHANGE_2000_100x100_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2006 Land cover EPSG:3044 CRS:84 5.559106356062301 15.560902596745297 47.32207569567077 55.06024373065345 text/xml CORINE_LAND_COVER_CHANGE_2000_100x100_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2006 Land cover EPSG:3035 CRS:84 5.468133544492798 15.478824034229683 47.3416203743293 55.06794341456626 text/xml CORINE_LAND_COVER_CHANGE_2006_100x100_ETRS89 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2006 Land cover EPSG:3044 CRS:84 5.570134448808754 15.535376293205498 47.250620665815916 54.93083806207906 text/xml CORINE_LAND_COVER_CHANGE_2006_100x100_LAEA 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 and the delivery of regular updates to register also the land cover and land use changes over time. 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. The first CLC data base CLC1990, which was finalized in the 1990s, consistently provided land use information comprising 44 classes, out of which 37 classes are relevant in Germany. The first two updates for Europe were based on the reference years 2000 and 2006. For Germany, DLR-DFD was responsible for the creation of CLC2000 and CLC2006 on behalf of the Federal Environment Agency. In addition to the updated land cover, change datasets were also parts of the project. For deriving a meaningful CLC2000 change product, it became necessary to re-interprete parts of the satellite data of 1990 and to create a revised product, called CLC1990 (rev). WCS GeoTIFF CORINE CORINE_2006 Land cover EPSG:3035 CRS:84 5.482405707253025 15.455390898307265 47.2789770391258 54.93945259912168 text/xml CROPTYPES_DE_P1Y The layers depict 18 crop types for Germany since 2018 based on Sentinel-1 and Sentinel-2 data with a resolution of 10m. DLR EOC EPSG:4326 CRS:84 5.25505226972244 16.44182029833741 46.70234194068808 55.8887694602763 2017-01-01T00:00:00.000Z/2024-12-31T00:00:00.000Z/P1Y ESA_LAND_OCEAN_MAP Land-ocean map derived from ESA CCI Land Cover Dataset. DLR EOC GWP MODIS ESA CCI Landcover Land-ocean map EPSG:4326 CRS:84 -180.0 179.99997696000003 -89.99998848 90.00000000000001 FCCL_DE_P1M The Forest Canopy Cover Loss (FCCL) shows the forest canopy cover loss in Germany in monthly resolution between September 2017 and September 2024 at 10 m spatial resolution. FCCL_DE_P1M WCS GeoTIFF EPSG:3035 CRS:84 5.230971659340296 15.694865911359667 47.06431450392907 55.169891337305664 FCCL_DE_P1M_CHANGES The Forest Canopy Cover Loss (FCCL) monthly observed changes displays how often an observation exceeded a threshold. It is also counted in pixels not labeled as FCCL. FCCL_DE_P1M_CHANGES WCS GeoTIFF EPSG:3035 CRS:84 5.230971659340296 15.694865911359667 47.06431450392907 55.169891337305664 FCCL_DE_P1M_GAPS Der Prozentsatz der Lücken in der Waldbedeckung (FCCL) zeigt den Prozentsatz der Lücken (d.h. eine Beobachtung, die einen Schwellenwert nicht überschreitet) in Pixeln, die als FCCL gekennzeichnet sind. FCCL_DE_P1M_GAPS WCS GeoTIFF EPSG:3035 CRS:84 5.230971659340296 15.694865911359667 47.06431450392907 55.169891337305664 FCCL_DE_P1M_GEM The layer shows FCCL results aggregated at municipality level. FCCL is quantified separately for deciduous, coniferous, and unclassified forests and the total of all forest types for each month as well as aggregated to annual totals. DLR EOC Forest Disturbance Germany Multispectral Sentinel-2 Landsat Canopy Cover Loss EPSG:3035 CRS:84 5.473023880259562 15.490107590788723 47.17124621679096 55.06781130732295 FCCL_DE_P1M_KRS The layer shows FCCL results aggregated at district level. FCCL is quantified separately for deciduous, coniferous, and unclassified forests and the total of all forest types for each month as well as aggregated to annual totals. DLR EOC Forest Disturbance Germany Multispectral Sentinel-2 Landsat Canopy Cover Loss EPSG:3035 CRS:84 5.473023880259562 15.490107590788723 47.17124621679096 55.06781130732295 FCCL_DE_P1M_LAN The layer shows FCCL results aggregated at federal state level. FCCL is quantified separately for deciduous, coniferous, and unclassified forests and the total of all forest types for each month as well as aggregated to annual totals. DLR EOC Forest Disturbance Germany Multispectral Sentinel-2 Landsat Canopy Cover Loss EPSG:3035 CRS:84 5.473023880259562 15.490107590788723 47.17124621679096 55.06781130732295 FCCL_DE_P1M_MASK Die monatliche Ergebnismaske für den Verlust der Waldbedeckung (Forest Canopy Cover Loss, FCCL) zeigt eine auf Entscheidungsbäumen basierende Klassifizierung der FCCL-Schicht in intakten Wald, (konsistenten) FCCL und zeitliche Veränderungen in Nadel-, Laub- und nicht klassifizierten Wäldern. FCCL_DE_P1M_MASK WCS GeoTIFF EPSG:3035 CRS:84 5.230971659340296 15.694865911359667 47.06431450392907 55.169891337305664 FCCL_DE_P1M_VEC This layer shows forest canopy cover losses in Germany caused by abiotoc (e.g. storm, fire, hail) and biotoc (e.g. insect infestation, funghi) as well as anthropogenic (e.g. planned harvest, salvage logging, sanitary cuts) drivers at 10 m spatial resolution and at monthly intervals. DLR EOC Forest Disturbance Germany Multispectral Sentinel-2 Landsat Canopy Cover Loss EPSG:3035 CRS:84 5.489923112833678 15.48276975743808 47.183276440616794 55.02323029301928 FOREST_AREAS_DISTRICTS_PRY_P1Y The products shows forest areas in Paraguay per district in ha. DLR EOC GeoForPy Forest Forest Cover Deforestation Paraguay Landsat-8 Sentinel-2 Time Series EPSG:32721 CRS:84 -62.77549224812465 -57.144044187409015 -25.355697730553207 -19.21749378646427 FOREST_COVER_PRY_1986_2020_P1Y The products depicts per-pixel forest cover for Paraguay in 30 m spatial resolution from 1986 till 2020. DLR EOC GeoForPy Forest Forest Cover Deforestation Paraguay Landsat-8 Sentinel-2 Time Series EPSG:32721 CRS:84 -62.77638749149846 -57.14377600015042 -25.355977047140737 -19.217257950131053 FOREST_COVER_S2_PRY DLR EOC GeoForPy Forest Forest Cover Deforestation Paraguay Landsat-8 Sentinel-2 Time Series EPSG:32721 CRS:84 -62.89458286131733 -57.14304636612077 -25.462772398555895 -19.20248473003372 FOREST_FHD_S2_PRY DLR EOC GeoForPy Forest Forest Cover Deforestation Paraguay Landsat-8 Sentinel-2 Time Series EPSG:32721 CRS:84 -62.89458286131733 -57.14304636612077 -25.462772398555895 -19.20248473003372 FOREST_FRAGMENTATION_PRY_2000 The product depicts the forest fragmentation in Paraguay for 2020. DLR EOC GeoForPy Forest Forest Cover Deforestation Paraguay Landsat-8 Sentinel-2 Time Series EPSG:32721 CRS:84 -62.76916529806209 -57.15577620878149 -25.277930644861694 -19.217622759873596 FOREST_FRAGMENTATION_PRY_2010 The product depicts the forest fragmentation in Paraguay. DLR EOC GeoForPy Forest Forest Cover Deforestation Paraguay Landsat-8 Sentinel-2 Time Series EPSG:32721 CRS:84 -62.76709203223988 -57.15577620878149 -25.277930644861694 -19.21768295412251 FOREST_FRAGMENTATION_PRY_2020 The product depicts the forest fragmentation in Paraguay. DLR EOC GeoForPy Forest Forest Cover Deforestation Paraguay Landsat-8 Sentinel-2 Time Series EPSG:32721 CRS:84 -62.765056906550214 -57.15806063058204 -25.27874076436783 -19.21774312697062 FOREST_PAI_S2_PRY DLR EOC GeoForPy Forest Forest Cover Deforestation Paraguay Landsat-8 Sentinel-2 Time Series EPSG:32721 CRS:84 -62.89458286131733 -57.14304636612077 -25.462772398555895 -19.20248473003372 FOREST_RH95_S2_PRY DLR EOC GeoForPy Forest Forest Cover Deforestation Paraguay Landsat-8 Sentinel-2 Time Series EPSG:32721 CRS:84 -62.89458286131733 -57.14304636612077 -25.462772398555895 -19.20248473003372 FOREST_STRUCTURE_DE_AGBD_P1Y This map shows the Above-ground biomass density (AGBD) in Germany for the years 2017 to 2023 DLR EOC LAX Land Sentinel-1 Sentinel-2 GEDI Forest Structure Yearly Germany Above-Ground Biomass Density EPSG:4326 CRS:84 5.867615772811891 15.041211454240443 47.27006890259651 55.05819292132753 2017-01-01T00:00:00.000Z/2023-01-01T00:00:00.000Z/P1Y image/png text/xml text/html FOREST_STRUCTURE_DE_COVER_P1Y This map shows the canopy cover in Germany for the years 2017 to 2023 DLR EOC LAX Land Sentinel-1 Sentinel-2 GEDI Forest Structure Yearly Germany Canopy Cover EPSG:4326 CRS:84 5.867615772811891 15.041211454240443 47.27006890259651 55.05819292132753 2017-01-01T00:00:00.000Z/2023-01-01T00:00:00.000Z/P1Y image/png text/xml text/html FOREST_STRUCTURE_DE_RH95_P1Y This map shows the canopy height in Germany for the years 2017 to 2023 DLR EOC LAX Land Sentinel-1 Sentinel-2 GEDI Forest Structure Yearly Germany Canopy Height EPSG:4326 CRS:84 5.867615772811891 15.041211454240443 47.27006890259651 55.05819292132753 2017-01-01T00:00:00.000Z/2023-01-01T00:00:00.000Z/P1Y image/png text/xml text/html GL_MOW_DE_P1Y_FC The layer shows the date of first mowing event in. DLR EOC EPSG:4326 CRS:84 5.763545147588102 15.152746853982658 46.793671616436775 55.94573292084947 2018-01-01T00:00:00.000Z/2024-12-31T23:59:59.000Z/P1Y GL_MOW_DE_P1Y_FREQ The layer shows the number of times grassland is mown per year. DLR EOC EPSG:4326 CRS:84 5.763545147588102 15.152746853982658 46.793671616436775 55.945732921 2018-01-01T00:00:00.000Z/2024-12-31T23:59:59.000Z/P1Y GSP_SCD WCS ImageMosaic index Global SnowPack EPSG:4326 CRS:84 -180.0 180.002616238467 -66.177818006519 90.0 2000-01-01T00:00:00.000Z/2015-01-01T00:00:00.000Z/P1Y GSP_SCDE_MEAN The arithmetic mean of the snow cover duration for early season, which extends from autumn to midwinter (SCDEmean) from 2001 until the current year. DLR EOC Land Global Snowpack Snow Cover Duration Early Season SCDE Arithmethic Mean EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2024-09-10T07:54:22.192Z/2024-09-10T07:54:22.192Z/P1Y GSP_SCDE_P1Y The snow cover duration for early season, which extends from autumn to midwinter (SCDE). DLR EOC Land Global Snowpack Snow Cover Duration Early Season SCDE EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2000-09-01T00:00:00.000Z/2024-07-14T23:59:59.999Z/P1Y GSP_SCDL_MEAN The arithmetic mean of the snow cover duration for late season, which extends over the period from mid-winter to the end of summer (SCDLmean) from 2001 until the current year. DLR EOC Land Global Snowpack Snow Cover Duration Late Season SCDL Arithmethic Mean EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2024-09-10T07:54:24.277Z/2024-09-10T07:54:24.277Z/P1Y GSP_SCDL_P1Y The snow cover duration for late season, which extends over the period from mid-winter to the end of summer (SCDL). DLR EOC Land Global Snowpack Snow Cover Duration Late Season SCDL EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2001-01-15T00:00:00.000Z/2025-02-28T23:59:59.999Z/P1Y GSP_SCD_MEAN The arithmetic mean of the snow cover duration for the entire hydrological year (SCDmean) from 2001 until the current year. DLR EOC Land Global Snowpack Snow Cover Duration SCD Arithmethic Mean EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2024-09-10T07:54:19.927Z/2024-09-10T07:54:19.927Z/P1Y GSP_SCD_P1Y The snow cover duration for the entire hydrological year (SCD). DLR EOC Land Global Snowpack Snow Cover Duration SCD EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2000-09-01T00:00:00.000Z/2025-02-28T23:59:59.999Z/P1Y GSP_SCE_NRT_P1D GSP - Global Snowpack Daily - SCE NRT DLR EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2024-08-01T00:00:00.000Z/2025-12-29T00:00:00.000Z/P1D GSP_SCE_P1D The snow cover extent (SCE) is the result of the Global SnowPack processor's interpolation steps and all data gaps have been filled. DLR EOC Land Global Snowpack daily Snow Cover Extent SCE EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2000-02-24T00:00:00.000Z/2025-09-30T00:00:00.000Z/P1D GSP_XCC10A1_P1D The XCC10A1 files show the time distance to the preceding day on which no gap-filling took place. However, these can only be used as a proxy for the overall accuracy, since gaps within the polar night are very likely to have snow cover, but at lower latitudes, the accuracy can drop drastically after just a few days. DLR EOC Land Global Snowpack daily Snow Cover Extent Near Real-Time SCE-NRT EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2000-02-24T00:00:00.000Z/2025-09-30T00:00:00.000Z/P1D GUF04_DLR_v1_Mosaic This layer represents the Global Urban Footprint® (GUF®) in it's 0.4 arcsecond / ~ 12m resolution version optimized for web service access. The datasets shows two land cover categories: Built-up areas (vertical structures only) are represented with value 255 and non-build-up surfaces with value 0. Areas of no coverage by the satellites are coded as value 128. For small-scale visualisation, reduced resolution overviews have been generated with an interpolation algorithm, that computes the average value of all contribution pixels. See the link to the metadata for more information. GUF® and Global Urban Footprint® are protected as trademarks. A non-exclusive, spatially and temporally unlimited, non-transferable, non-sublicensable right to use GUF is granted free of charge for a) scientific purposes on the high resolution version of GUF® (0.4 arcseconds), b) non-commercial purposes on the low resolution version of the GUF® (2.8 arcseconds). This license does not grant any commercial use of GUF® or products generated or derived by GUF®. GUF04_DLR_v1_Mosaic Land Cover Land Urbanization Global Mapping Settlement Patterns TerraSAR-X TanDEM-X Texture GUF Global Urban Footprint EPSG:4326 CRS:84 -180.000331 180.00011744680816 -65.00011177876183 85.000001 image/png text/xml GUF28_DLR_v1_Mosaic This layer represents the Global Urban Footprint® (GUF®) in it's 2.8 arcsecond / ~ 84m resolution version optimized for web service access. The datasets shows two land cover categories: Built-up areas (vertical structures only) are represented with value 255 and non-build-up surfaces with value 0. Areas of no coverage by the satellites are coded as value 128. For small-scale visualisation, reduced resolution overviews have been generated with an interpolation algorithm, that computes the average value of all contribution pixels. See the link to the metadata for more information. GUF® and Global Urban Footprint® are protected as trademarks. A non-exclusive, spatially and temporally unlimited, non-transferable, non-sublicensable right to use GUF is granted free of charge for a) scientific purposes on the high resolution version of GUF® (0.4 arcseconds), b) non-commercial purposes on the low resolution version of the GUF® (2.8 arcseconds). This license does not grant any commercial use of GUF® or products generated or derived by GUF®. Land Cover Land Urbanization Global Mapping Settlement Patterns TerraSAR-X TanDEM-X Texture GUF Global Urban Footprint EPSG:4326 CRS:84 -180.000331 180.0011174455005 -64.99988955598766 85.000001 text/xml GWP_P1M This monthly layer contains information on how often a pixel was detected as open surface water with pixel values between 0 and 31. DLR EOC GWP MODIS Monthly EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2003-01-01T00:00:00.000Z/2024-12-01T00:00:00.000Z/P1M image/png text/plain text/html GWP_P1Y This yearly layer contains information on how often a pixel was detected as open surface water with pixel values between 0 and 365 (366 for leap years). DLR EOC GWP MODIS Yearly EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2003-01-01T00:00:00.000Z/2024-01-01T00:00:00.000Z/P1Y image/png text/plain text/html HEDGEROWS_BY_2019_2021 The layer shows vectors of hedgerow objects in Bavaria. features hedgerows_by_2019_2021 EPSG:25832 CRS:84 8.97865598095515 14.013990278949569 47.182763478509145 50.560294131955594 1.0 ICELINES_S1_P1M IceLines Monthly is an automated calving front monitoring service providing monthly ice shelf front time series of major Antarctic ice shelves. IceLines glacier Antartica calving front ice shelf front time series Sentinel-1 monthly EPSG:3031 CRS:84 -180.0 180.0 -90.0 -58.059795502013344 ICELINES_S1_P1Y IceLines Yearly is an automated calving front monitoring service providing yearly ice shelf front time series of major Antarctic ice shelves. IceLines glacier Antartica calving front ice shelf front time series Sentinel-1 yearly EPSG:3031 CRS:84 -180.0 180.0 -90.0 -58.073163049930464 ICELINES_SHELFNAMES The layer depicts the names of each ice shelf. IceLines glacier Antartica calving front ice shelf front time series Sentinel-1 shelfnames EPSG:3031 CRS:84 -180.0 180.0 -90.0 -59.06630873498738 1.6E7 IDC_Score Input Data Consistency for Landsat data landsat quality consistency EPSG:4326 CRS:84 -180.010255681217 180.010255681217 -60.0102457565648 78.0100585990529 LCC_DE_2015 This layer contains a land cover classification of Germany which was created using Sentinel-2 imagery and LUCAS in-situ reference data (https://ec.europa.eu/eurostat/web/lucas). It contains seven land cover types: (1) artificial land, (2) open soil, (3) high seasonal vegetation, (4) high perennial vegetation, (5) low seasonal vegetation, (6) low perennial vegetation and (7) water with a spatial resolution of 10m x 10m. DLR EOC Germany Land cover map Sentinel-2 EPSG:3035 CRS:84 4.730999535505982 16.432222328775413 47.014802320405316 55.25836025427186 N2N_NOISE_AI_DE_2017 This dataset includes a road traffic noise estimation using ensemble learning and multimodal geodata. NOISE EPSG:4326 CRS:84 5.38987987325346 15.573542540854344 47.12283676623768 55.02821859586835 N2N_NOISE_DE_2017 This dataset includes a road traffic noise indicator mapped according to the European Noise Directive (2002/49/EC). NOISE EPSG:3035 CRS:84 5.389879873253458 15.573542540854344 47.12283681293146 55.11194621255036 NOAA_AVHRR_SST_P1M "AVHRR - Monthly Sea Surface Temperature (SST)" is an AVHRR (Advanced Very High Resolution Radiometer) subset from 1993 to 2014 integrated to facilitate valuable time series exploitation of historic data. This subset represents the Monthly Average of Sea Surface Temperature in degrees celsius. DLR AVHRR EOC NOAA SST MONTHLY Sea Surface Temperature Monthly EPSG:4326 CRS:84 -22.5595999595764 -5.44067902556616 26.2172400082324 48.1549000212745 1993-03-01T00:00:00.000Z/2014-08-01T00:00:00.000Z/P1M PROTECTED_AREAS_FOREST_PRY The products shows protected areas in Paraguay, which receive protection because of their natural values. DLR EOC GeoForPy Forest Forest Cover Deforestation Paraguay Landsat-8 Sentinel-2 Time Series EPSG:32721 CRS:84 -62.41493205390733 -58.083427865546525 -24.50414965619315 -19.226626466584403 SAR4TEC_EURASIA_EAST_ASCE Sar4Tectonics data for eurasia (Ascending) DLR EOC Sar4Tectonics Sentinel-1 Ascending Eurasia EPSG:4326 CRS:84 -8.643509 144.533 13.51874 51.99475 SAR4TEC_EURASIA_EAST_DESC Sar4Tectonics data for eurasia (Descending) DLR EOC Sar4Tectonics Sentinel-1 Descending Eurasia EPSG:4326 CRS:84 -9.492298 144.2898 13.45345 57.98615 SCMAP_SC_LS Exposed Soil Coverage v1.0 processed by Soil Composite Mapping Processor (SCMaP) DLR EOC Land Landsat Soil Map SCMaP Soil Composite Mapping Processor Soil Classification Exposed Soil Coverage Soil Coverage EPSG:4326 CRS:84 5.86625014202331 15.0418059196273 47.2701400336255 55.056529110945 1984-01-01T00:00:00.000Z/1989-12-31T23:59:59.999Z/PT1S,1990-01-01T00:00:00.000Z/1994-12-31T23:59:59.999Z/PT1S,1995-01-01T00:00:00.000Z/1999-12-31T23:59:59.999Z/PT1S,2000-01-01T00:00:00.000Z/2004-12-31T23:59:59.999Z/PT1S,2005-01-01T00:00:00.000Z/2009-12-31T23:59:59.999Z/PT1S,2010-01-01T00:00:00.000Z/2014-12-31T23:59:59.999Z/PT1S SCMAP_SC_LS_1984-2014 Exposed Soil Coverage v1.0 for 1984-2014 processed by Soil Composite Mapping Processor (SCMaP) DLR EOC Land Landsat Soil Map SCMaP Soil Composite Mapping Processor Soil Classification Exposed Soil Coverage Soil Coverage EPSG:4326 CRS:84 5.86625014202319 15.0418059196272 47.2701400336262 55.0565291109457 1984-01-01T00:00:00.000Z/2014-12-31T23:59:59.999Z/PT1S SCMAP_SF_LS Exposed Soil Frequency v1.0 processed by Soil Composite Mapping Processor (SCMaP) DLR EOC Land Landsat Soil Map SCMaP Soil Composite Mapping Processor Soil Classification Exposed Soil Coverage Soil Frequency EPSG:4326 CRS:84 5.86625014202326 15.0418059196272 47.2701400336262 55.0565291109457 1984-01-01T00:00:00.000Z/1989-12-31T23:59:59.999Z/PT1S,1990-01-01T00:00:00.000Z/1994-12-31T23:59:59.999Z/PT1S,1995-01-01T00:00:00.000Z/1999-12-31T23:59:59.999Z/PT1S,2000-01-01T00:00:00.000Z/2004-12-31T23:59:59.999Z/PT1S,2005-01-01T00:00:00.000Z/2009-12-31T23:59:59.999Z/PT1S,2010-01-01T00:00:00.000Z/2014-12-31T23:59:59.999Z/PT1S SCMAP_SF_LS_1984-2014 Exposed Soil Frequency v1.0 for 1984-2014 processed by Soil Composite Mapping Processor (SCMaP) DLR EOC Land Landsat Soil Map SCMaP Soil Composite Mapping Processor Soil Classification Exposed Soil Coverage Soil Frequency EPSG:4326 CRS:84 5.86625014202319 15.0418059196272 47.2701400336262 55.0565291109457 1984-01-01T00:00:00.000Z/2014-12-31T23:59:59.999Z/PT1S SCMAP_SN_LS Normalized Reflectance Soil Composite v1.0 processed by Soil Composite Mapping Processor (SCMaP) DLR EOC Land Landsat Soil Map SCMaP Soil Composite Mapping Processor Normalized Reflectance Soil Composite Reflectance EPSG:4326 CRS:84 5.86625014202338 15.0418059196274 47.2701400336255 55.056529110945 1984-01-01T00:00:00.000Z/1989-12-31T23:59:59.999Z/PT1S,1990-01-01T00:00:00.000Z/1994-12-31T23:59:59.999Z/PT1S,1995-01-01T00:00:00.000Z/1999-12-31T23:59:59.999Z/PT1S,2000-01-01T00:00:00.000Z/2004-12-31T23:59:59.999Z/PT1S,2005-01-01T00:00:00.000Z/2009-12-31T23:59:59.999Z/PT1S,2010-01-01T00:00:00.000Z/2014-12-31T23:59:59.999Z/PT1S SCMAP_SN_LS_1984-2014 Normalized Reflectance Soil Composite v1.0 for 1984-2014 processed by Soil Composite Mapping Processor (SCMaP) DLR EOC Land Landsat Soil Map SCMaP Soil Composite Mapping Processor Normalized Reflectance Soil Composite Reflectance EPSG:4326 CRS:84 5.86625014202319 15.0418059196272 47.2701400336262 55.0565291109457 1984-01-01T00:00:00.000Z/2014-12-31T23:59:59.999Z/PT1S SCMAP_SR_LS Reflectance Composite v1.0 processed by Soil Composite Mapping Processor (SCMaP) DLR EOC Land Landsat Soil Map SCMaP Soil Composite Mapping Processor Normalized Reflectance Soil Composite Reflectance EPSG:4326 CRS:84 5.86625014202338 15.0418059196274 47.2701400336255 55.056529110945 1984-01-01T00:00:00.000Z/1989-12-31T23:59:59.999Z/PT1S,1990-01-01T00:00:00.000Z/1994-12-31T23:59:59.999Z/PT1S,1995-01-01T00:00:00.000Z/1999-12-31T23:59:59.999Z/PT1S,2000-01-01T00:00:00.000Z/2004-12-31T23:59:59.999Z/PT1S,2005-01-01T00:00:00.000Z/2009-12-31T23:59:59.999Z/PT1S,2010-01-01T00:00:00.000Z/2014-12-31T23:59:59.999Z/PT1S SCMAP_SR_LS_1984-2014 Reflectance Composite v1.0 for 1984-2014 processed by Soil Composite Mapping Processor (SCMaP) DLR EOC Land Landsat Soil Map SCMaP Soil Composite Mapping Processor Normalized Reflectance Soil Composite Reflectance EPSG:4326 CRS:84 5.86625014202319 15.0418059196272 47.2701400336262 55.0565291109457 1984-01-01T00:00:00.000Z/2014-12-31T23:59:59.999Z/PT1S SMAP_EURASIA_EAST_ASCE EPSG:4326 CRS:84 106.8689 112.2154042074719 33.711037072310404 44.8625 SOILSUITE_MASK_AFR_P4Y The MASK product aggregates simple landcover classes that occur during the time period between 2018 - 2021 (Sentinel-2). The three-class Mask contains: (1) Bare surface occurrences, (2) Permanent vegetation, (3) Other surfaces (e.g. water bodies, urban areas, roads). DLR EOC Land SCMaP Soil Sentinel-2 Africa Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Mask EPSG:4326 CRS:84 28.746089091824686 50.3056559106932 -7.215551366812188 16.0612327424534 text/xml SOILSUITE_MASK_EUR_P5Y The MASK product aggregates simple landcover classes that occur during the time period between 2018 - 2022 (Sentinel-2). The three-class Mask contains: (1) Bare surface occurrences, (2) Permanent vegetation, (3) Other surfaces (e.g. water bodies, urban areas, roads). DLR EOC Land SCMaP Soil Sentinel-2 Europe Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Mask EPSG:3035 CRS:84 45.11997737153057 48.3031470022221 39.46846653914031 41.893378728158574 SOILSUITE_MREF-STD_AFR_P4Y The Reflectance Composite (Std Dev) contains the standard deviation per band for all valid Sentinel-2 observations between 2018 - 2021, scaled from 0 to 10.000. The valid observations include vegetation, bare surfaces and other surfaces and it excludes clouds, haze, cloud shadows and snow. The product quantifies the spectral dynamic of all landcover types occurring in the images. As an example, it shows a higher standard deviation in agricultural areas compared to natural grasslands. DLR EOC Land SCMaP Soil Sentinel-2 Africa Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Reflectance Composite – Std Dev EPSG:4326 CRS:84 28.746089091824686 50.3056559106932 -7.215551366812188 16.0612327424534 text/xml SOILSUITE_MREF-STD_EUR_P5Y The Reflectance Composite (Std Dev) contains the standard deviation per band for all valid Sentinel-2 observations between 2018 - 2022, scaled from 0 to 10.000. The valid observations include vegetation, bare surfaces and other surfaces and it excludes clouds, haze, cloud shadows and snow. The product quantifies the spectral dynamic of all landcover types occurring in the images. As an example, it shows a higher standard deviation in agricultural areas compared to natural grasslands. DLR EOC Land SCMaP Soil Sentinel-2 Europe Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Reflectance Composite – Std Dev EPSG:3035 CRS:84 -34.84229818529844 74.35811444109153 28.083928457702 73.01747580668338 text/xml SOILSUITE_MREF_AFR_P4Y The Reflectance Composte (Mean) contains reflectance values per band, scaled between 0 and 10.000. It represents the mean reflectance of all valid Sentinel-2 observations between 2018 - 2021. Valid observations include vegetation, bare and other surfaces and exclude clouds, haze, cloud shadows and snow. DLR EOC Land SCMaP Soil Sentinel-2 Africa Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Reflectance Composite – Mean EPSG:4326 CRS:84 28.746089091824686 50.3056559106932 -7.215551366812188 16.0612327424534 2018-03-01T00:00:00.000Z/2021-12-31T00:00:00.000Z/PT1S text/xml SOILSUITE_MREF_EUR_P5Y The Reflectance Composte (Mean) contains reflectance values per band, scaled between 0 and 10.000. It represents the mean reflectance of all valid Sentinel-2 observations between 2018 - 2022. Valid observations include vegetation, bare and other surfaces and exclude clouds, haze, cloud shadows and snow. DLR EOC Land SCMaP Soil Sentinel-2 Europe Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Reflectance Composite – Mean EPSG:3035 CRS:84 -34.84229818529844 74.35811444109153 28.083928457702 73.01747580668338 text/xml SOILSUITE_SFREQ-BSC_AFR_P4Y The Bare Surface Count is defined as the number of occurrences detected as bare surface between 2018 - 2021. It is not normalized to the total number of valid Sentinel-2 observations. The value reveals the dependence of the pixel position across the ground track that can lead to nearly double observations in overlapping orbits. DLR EOC Land SCMaP Soil Sentinel-2 Africa Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Bare Surface Count EPSG:4326 CRS:84 28.746089091824686 50.3056559106932 -7.215551366812188 16.0612327424534 text/xml SOILSUITE_SFREQ-BSC_EUR_P5Y The Bare Surface Count is defined as the number of occurrences detected as bare surface between 2018 - 2022. It is not normalized to the total number of valid Sentinel-2 observations. The value reveals the dependence of the pixel position across the ground track that can lead to nearly double observations in overlapping orbits. DLR EOC Land SCMaP Soil Sentinel-2 Europe Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Bare Surface Count EPSG:4326 CRS:84 -29.177180913776336 49.42179460501849 32.37687195501771 73.10277281336056 2018-03-01T00:00:00.000Z/2022-12-31T00:00:00.000Z/PT1S text/xml SOILSUITE_SFREQ-BSF_AFR_P4Y The Bare Surface Frequency is scaled between 0 and 1 and quantifies the ratio of bare surface occurrences over the total number of valid Sentinel-2 observations in the observed time period between 2018 - 2021. DLR EOC Land SCMaP Soil Sentinel-2 Africa Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Bare Surface Frequency EPSG:4326 CRS:84 28.746089091824686 50.3056559106932 -7.215551366812188 16.0612327424534 text/xml SOILSUITE_SFREQ-BSF_EUR_P5Y The Bare Surface Frequency is scaled between 0 and 1 and quantifies the ratio of bare surface occurrences over the total number of valid Sentinel-2 observations in the observed time period between 2018 - 2022. DLR EOC Land SCMaP Soil Sentinel-2 Europe Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Bare Surface Frequency EPSG:4326 CRS:84 -29.177180913776336 49.42179460501849 32.37687195501771 73.10277281336056 2018-03-01T00:00:00.000Z/2022-12-31T00:00:00.000Z/PT1S text/xml SOILSUITE_SFREQ-VPC_AFR_P4Y This Valid Pixel Count contains the total number of valid Sentinel-2 observations in the time period between 2018 - 2021 excluding cloud, haze, cloud shadow, snow, etc.. DLR EOC Land SCMaP Soil Sentinel-2 Africa Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Valid Pixel Count EPSG:4326 CRS:84 28.746089091824686 50.3056559106932 -7.215551366812188 16.0612327424534 text/xml SOILSUITE_SFREQ-VPC_EUR_P5Y This Valid Pixel Count contains the total number of valid Sentinel-2 observations in the time period between 2018 - 2022 excluding cloud, haze, cloud shadow, snow, etc.. DLR EOC Land SCMaP Soil Sentinel-2 Europe Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Valid Pixel Count EPSG:4326 CRS:84 -29.177180913776336 49.42179460501849 32.37687195501771 73.10277281336056 2018-03-01T00:00:00.000Z/2022-12-31T00:00:00.000Z/PT1S text/xml SOILSUITE_SRC-CI95_AFR_P4Y The Bare Surface Reflectance Composite (Std Dev) contains the standard deviation of all Sentinel-2 bare surface reflectance values occuring between 2018 - 2021. It is scaled between 0 and 10.000 for each band and excludes urban areas, water bodies, clouds, haze, cloud shadows and snow. This product quantifies e.g. the spectral dynamic of soils, which might differ according to their physical and chemical properties and thus, can be taken as an additional characteristic of the soil. DLR EOC Land SCMaP Soil Sentinel-2 Africa Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Bare Surface Reflectance Composite – 95% Confidence EPSG:4326 CRS:84 28.746089091824686 50.3056559106932 -7.215551366812188 16.0612327424534 text/xml SOILSUITE_SRC-CI95_EUR_P5Y The Bare Surface Reflectance Composite (Std Dev) contains the standard deviation of all Sentinel-2 bare surface reflectance values occuring between 2018 - 2022. It is scaled between 0 and 10.000 for each band and excludes urban areas, water bodies, clouds, haze, cloud shadows and snow. This product quantifies e.g. the spectral dynamic of soils, which might differ according to their physical and chemical properties and thus, can be taken as an additional characteristic of the soil. DLR EOC Land SCMaP Soil Sentinel-2 Europe Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Bare Surface Reflectance Composite – 95% Confidence EPSG:3035 CRS:84 -34.84229818529844 74.35811444109153 28.083928457702 73.01747580668338 text/xml SOILSUITE_SRC-STD_AFR_P4Y The Bare Surface Reflectance Composite (Std Dev) contains the standard deviation of all Sentinel-2 bare surface reflectance values occuring between 2018 - 2021. It is scaled between 0 and 10.000 for each band and excludes urban areas, water bodies, clouds, haze, cloud shadows and snow. This product quantifies e.g. the spectral dynamic of soils, which might differ according to their physical and chemical properties and thus, can be taken as an additional characteristic of the soil. DLR EOC Land SCMaP Soil Sentinel-2 Africa Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Bare Surface Reflectance Composite – Std Dev EPSG:4326 CRS:84 28.746089091824686 50.3056559106932 -7.215551366812188 16.0612327424534 text/xml SOILSUITE_SRC-STD_EUR_P5Y The Bare Surface Reflectance Composite (Std Dev) contains the standard deviation of all Sentinel-2 bare surface reflectance values occuring between 2018 - 2022. It is scaled between 0 and 10.000 for each band and excludes urban areas, water bodies, clouds, haze, cloud shadows and snow. This product quantifies e.g. the spectral dynamic of soils, which might differ according to their physical and chemical properties and thus, can be taken as an additional characteristic of the soil. DLR EOC Land SCMaP Soil Sentinel-2 Europe Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Bare Surface Reflectance Composite – Std Dev EPSG:3035 CRS:84 -34.84229818529844 74.35811444109153 28.083928457702 73.01747580668338 text/xml SOILSUITE_SRC_AFR_P4Y The Bare Surface Reflectance Composite (Mean) contains reflectance values scaled between 0 and 10.000. It represents the mean reflectance of all Sentinel-2 bare surface occurrences between 2018 - 2021 excluding urban areas, water bodies, clouds, haze, cloud shadows and snow. This product is one of the main inputs for spectral as well as digital soil mapping approaches. DLR EOC Land SCMaP Soil Sentinel-2 Africa Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Bare Surface Reflectance Composite – Mean EPSG:4326 CRS:84 28.746089091824686 50.3056559106932 -7.215551366812188 16.0612327424534 text/xml SOILSUITE_SRC_EUR_P5Y The Bare Surface Reflectance Composite (Mean) contains reflectance values scaled between 0 and 10.000. It represents the mean reflectance of all Sentinel-2 bare surface occurrences between 2018 - 2022 excluding urban areas, water bodies, clouds, haze, cloud shadows and snow. This product is one of the main inputs for spectral as well as digital soil mapping approaches. DLR EOC Land SCMaP Soil Sentinel-2 Europe Temporal Composites Soil Coverage Soil Composite Mapping Processor Reflectance Composite Surface Reflectance Composite Bare Soil Coverage Bare Soil Frequency Bare Surface Reflectance Composite – Mean EPSG:3035 CRS:84 -34.84229818529844 74.35811444109153 28.083928457702 73.01747580668338 text/xml TDM_FNF50 This layer contains the TanDEM-X Forest/Non-Forest Map (FNF) map which has been generated by processing and mosaicking more than 500,000 TanDEM-X bistatic images acquired from 2011 until 2015. The map has a spatial resolution of 50 x 50m. Forested and non-forested areas are depicted in green and white, respectively. Water bodies are depicted in blue and black is used for identifying urban areas and invalid pixels. FNF50 Global FNF Map EPSG:4326 CRS:84 -180.0005 180.00049999999572 -58.00024999999985 79.00025 text/xml TDM_FNF50_COV This layer contains the FNF coverage map which indicates the number of mosaicked acquisitions for a specific ground area. FNF50 Coverage Map EPSG:4326 CRS:84 -180.0005 180.00050000000005 -58.00025000000002 79.00025 text/xml TDM_FNF50_SPC This layer contains the TanDEM-X FNF Super Pixels Count (SPC) map. Together with the acquisition date of the last super pixel, the total number of detected super pixels for the considered pixel is provided. The values in the super pixel count map range from 0 to 10. 0 indicates no super pixel. 10 represents 10 or more detected super pixels. FNF50 Super Pixels Count Map EPSG:4326 CRS:84 -180.0005 180.00050000000005 -58.00025000000002 79.00025 text/xml TDM_FNF50_SPD This layer contains the TanDEM-X FNF Super Pixels Date map. The map provides the date of the most recent super pixel, if present. In this sense, the presence of a recent super pixel reasonably allows one to exclude possible regrowth. Where no superpixel has been detected, the date of the first mosaicked image is provided. The values in the super pixel date map refer to the date of last occurrence of a super pixel. The dates refer to year and month. The conversion matrix for the values is included in the products description document. FNF50 Super Pixels Date Map EPSG:4326 CRS:84 -180.0005 180.00050000000005 -58.00025000000002 79.00025 text/xml TIMELINE_AVHRR_L3_P1M_LSTD_COUNT TIMELINE Monthly Composite of Count of valid pixels in the respective period DLR EOC TIMELINE AVHRR L3 Timeseries for global change analysis LSTD Land Surface Temperature (Day) Count of valid pixels EPSG:4326 CRS:84 -56.51695840749218 72.90771505554093 24.286441261786095 58.95876067653004 1982-02-01T00:00:00.000Z/2022-12-31T23:59:59.000Z/P1M TIMELINE_AVHRR_L3_P1M_LSTD_MAX TIMELINE Monthly Composite of Max Land Surface Temperature of the respective period (during day in K) (AVHRR) DLR EOC TIMELINE AVHRR L3 Timeseries for global change analysis LSTD Land Surface Temperature (Day) Monthly Max EPSG:4326 CRS:84 -56.51695840749218 72.90771505554093 24.286441261786095 58.95876067653004 1982-02-01T00:00:00.000Z/2022-12-31T23:59:59.000Z/P1M TIMELINE_AVHRR_L3_P1M_LSTD_MEAN TIMELINE Monthly Composite of Mean Land Surface Temperature of the respective period (during day in K) (AVHRR) DLR EOC TIMELINE AVHRR L3 Timeseries for global change analysis LSTD Land Surface Temperature (Day) Monthly Mean EPSG:4326 CRS:84 -56.51695840749218 72.90771505554093 24.286441261786095 58.95876067653004 1982-02-01T00:00:00.000Z/2022-12-31T23:59:59.000Z/P1M TIMELINE_AVHRR_L3_P1M_LSTD_MIN TIMELINE Monthly Composite of Min Land Surface Temperature of the respective period (during day in K) (AVHRR) DLR EOC TIMELINE AVHRR L3 Timeseries for global change analysis LSTD Land Surface Temperature (Day) Monthly Min EPSG:4326 CRS:84 -56.51695840749218 72.90771505554093 24.286441261786095 58.95876067653004 1982-02-01T00:00:00.000Z/2022-12-31T23:59:59.000Z/P1M TIMELINE_AVHRR_L3_P1M_LSTD_STD TIMELINE Monthly Composite of Standard Deviation of Land Surface Temperature in the respective period (during day in K) (AVHRR) DLR EOC TIMELINE AVHRR L3 Timeseries for global change analysis LSTD Land Surface Temperature (Day) Monthly Standard Deviation of Land Surface Temperature EPSG:4326 CRS:84 -56.51695840749218 72.90771505554093 24.286441261786095 58.95876067653004 1982-02-01T00:00:00.000Z/2022-12-31T23:59:59.000Z/P1M TREE_CANOPY_COVER_LOSS_HA_ALLFOREST_P1Y This is a vector data set showing per-district statistics of all forests tree canopy cover loss in ha in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types. Forest Canopy Cover Loss Drought Landsat-8 Disturbance Index Time Series Sentinel-2 Deutschland EPSG:3035 CRS:84 5.473270757377095 15.489810232562935 47.171245454678136 55.06562940966963 TREE_CANOPY_COVER_LOSS_HA_CONIFEROUS_P1Y This is a vector data set showing per-district statistics of coniferous tree canopy cover loss in ha in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types. Forest Canopy Cover Loss Drought Landsat-8 Disturbance Index Time Series Sentinel-2 Deutschland coniferous EPSG:3035 CRS:84 5.473270757377095 15.489810232562935 47.171245454678136 55.06562940966963 TREE_CANOPY_COVER_LOSS_HA_DECIDUOUS_P1Y This is a vector data set showing per-district statistics of deciduous tree canopy cover loss in ha in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types. Forest Canopy Cover Loss Drought Landsat-8 Disturbance Index Time Series Sentinel-2 Deutschland hectarloss deciduous EPSG:3035 CRS:84 5.473270757377095 15.489810232562935 47.171245454678136 55.06562940966963 TREE_CANOPY_COVER_LOSS_P1M The products depicts per-pixel tree canopy cover loss at 10 m spatial resolution from January 2018 till April 2021. Forest Canopy Cover Loss Drought Landsat-8 Disturbance Index Time Series Sentinel-2 Deutschland EPSG:3035 CRS:84 4.960589178227888 16.114268243041412 47.04844742857647 55.26042551315777 TREE_CANOPY_COVER_LOSS_PERC_ALLFOREST_P1Y This is a vector data set showing per-district statistics of all forests tree canopy cover loss in % in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types. Forest Canopy Cover Loss Drought Landsat-8 Disturbance Index Time Series Sentinel-2 Deutschland EPSG:3035 CRS:84 5.473270757377095 15.489810232562935 47.171245454678136 55.06562940966963 TREE_CANOPY_COVER_LOSS_PERC_CONIFEROUS_P1Y This is a vector data set showing per-district statistics of coniferous tree canopy cover loss in % in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types. Forest Canopy Cover Loss Drought Landsat-8 Disturbance Index Time Series Sentinel-2 Deutschland coniferous EPSG:3035 CRS:84 5.473270757377095 15.489810232562935 47.171245454678136 55.06562940966963 TREE_CANOPY_COVER_LOSS_PERC_DECIDUOUS_P1Y This is a vector data set showing per-district statistics of deciduous tree canopy cover loss in % in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types. Forest Canopy Cover Loss Drought Landsat-8 Disturbance Index Time Series Sentinel-2 Deutschland hectarloss deciduous EPSG:3035 CRS:84 5.473270757377095 15.489810232562935 47.171245454678136 55.06562940966963 TREE_SPECIES_DE_2016 The Tree Species Germany product provides a map of dominant tree species across Germany for the year 2016 at a spatial resolution of 10 meters. The map depicts the distribution of ten tree species groups derived from multi-temporal optical Sentinel-2 data. DLR EOC forest tree species machine learning time-series Sentinel-2 Germany eoc-mid-0079-vm: EPSG:3035 CRS:84 5.357117533816744 15.586501370011273 47.18801333179403 55.20059302945526 image/png text/xml text/html TREE_SPECIES_DE_2022 The Tree Species Germany product provides a map of dominant tree species across Germany for the year 2022 at a spatial resolution of 10 meters. The map depicts the distribution of ten tree species groups derived from multi-temporal optical Sentinel-2 data, radar data from Sentinel-1, and a digital elevation model. DLR EOC forest tree species machine learning time-series Sentinel-1 Sentinel-2 Germany EPSG:3035 CRS:84 5.357117533816744 15.586501370011273 47.16807488910552 55.20059302945526 image/png text/xml text/html TS_LANDSAT_2015 TimeScan Global 2015 (Landsat) DLR EOC Landsat Global TimeScan EPSG:4326 CRS:84 -180.0 179.999999999998 -89.9999999999988 90.0 URBAN_DEG_DISC_DE_2018 This layer shows the classification into 5 categories of the degree of urbanization in Germany in 2018. URBAN_DEG_DISC_DE_2018 WCS ImageMosaic EPSG:4326 CRS:84 5.472240368312381 15.490696346402764 47.17051104712369 55.068596344747746 URBAN_DEG_PERC_DE_2018 This layer shows the probability of the degree of urbanization in Germany in % in 2018. URBAN_DEG_PERC_DE_2018 WCS ImageMosaic EPSG:4326 CRS:84 5.472240368312381 15.490696346402764 47.17051104712369 55.068596344747746 URMO_TAM_3K_BRUNSWICK The dataset depicts the inventory of traffic areas in the city of Brunswick, Germany. DLR EOC Arial Imagery Image Segmentation Traffic Area Map Parking Space Detection Multitemporal Fusion EPSG:3035 CRS:84 10.484114223312364 10.568968686619046 52.23992108244101 52.32188460260454 WSF3D_V02_BUILDINGAREA The WSF 3D Building Area product depicts detailed quantification of total area in m² at 90 m resolution at a global scale. building height building volume building area building density urbanization 3D global Sentinel-1 Sentinel-2 TanDEM-X DLR EOC EPSG:4326 CRS:84 -180.00149996666667 180.00227781111116 -56.000277822222216 84.00049995555557 WSF3D_V02_BUILDINGFRACTION The WSF 3D Building Fraction product depicts detailed quantification of fraction in % at 90 m resolution at a global scale. building height building volume building area building density urbanization 3D global Sentinel-1 Sentinel-2 TanDEM-X DLR EOC EPSG:4326 CRS:84 -180.00149996666667 180.00227781111116 -56.000277822222216 84.00049995555557 WSF3D_V02_BUILDINGHEIGHT The WSF 3D Building Height product depicts detailed quantification of average height in m at 90 m resolution at a global scale. building height building volume building area building density urbanization 3D global Sentinel-1 Sentinel-2 TanDEM-X DLR EOC EPSG:4326 CRS:84 -180.00149996666667 180.00227781111116 -56.000277822222216 84.00049995555557 WSF3D_V02_BUILDINGVOLUME The WSF 3D Building Fraction product depicts detailed quantification of total volume in m³ at 90 m resolution at a global scale. building height building volume building area building density urbanization 3D global Sentinel-1 Sentinel-2 TanDEM-X DLR EOC EPSG:4326 CRS:84 -180.00149996666667 180.00227781111116 -56.000277822222216 84.00049995555557 WSF_2015 World Settlement Footprint 2015 land urbanization global mapping settlement patterns landsat sentinel2 copernicus EPSG:4326 CRS:84 -180.01007601815968 180.01007601819816 -60.01006609352275 78.0100585990529 WSF_2019 World Settlement Footprint 2019 land urbanization global settlement extent mapping sentinel-1 sentinel-2 copernicus 2019 dlr EPSG:4326 CRS:84 -180.01007601815968 180.01007601819816 -60.01006609352275 78.0100585990529 WSF_Evolution World Settlement Footprint Evolution land urbanization global mapping settlement evolution settlement extent growth landsat big data EPSG:4326 CRS:84 -180.0102556812165 180.01025568124214 -60.01024575657463 78.0100585990529 ne_countries EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0