The Copernicus DEM is a Digital Surface Model (DSM) which represents the bare-Earth surface and all above ground natural and built features. It is based on WorldDEM™ DSM that is derived from TanDEM-X and is infilled on a local basis with the following DEMs: ASTER, SRTM90, SRTM30, SRTM30plus, GMTED2010, TerraSAR-X Radargrammetric DEM, ALOS World 3D-30m. Copernicus Programme provides Copernicus DEM in 3 different instances: COP-DEM EEA-10, COP-DEM GLO-30 and COP-DEM GLO-90 where "COP-DEM GLO-90" tiles and most of the "COP-DEM GLO-30 " tiles are available worldwide with free license. Sentinel Hub provides two instances named COPERNICUS_90 which uses "COP-DEM GLO-90" and COPERNICUS_30 which uses "COP-DEM GLO-30 Public" and "COP-DEM GLO-90" in areas where "COP-DEM GLO-30 Public" tiles are not yet released to the public by Copernicus Programme. Copernicus DEM provides elevation data and can also be used for the orthorectification of satellite imagery (e.g Sentinel 1).

The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. We provide two instances of Copernicus DEM named GLO-30 Public and GLO-90. GLO-90 provides worldwide coverage at 90 meters. GLO-30 Public provides limited worldwide coverage at 30 meters because a small subset of tiles covering specific countries are not yet released to the public by the Copernicus Programme. Note that in both cases ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs and comes from Copernicus DEM 2021 release.

The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. This DEM is derived from an edited DSM named WorldDEM&trade, i.e. flattening of water bodies and consistent flow of rivers has been included. Editing of shore- and coastlines, special features such as airports and implausible terrain structures has also been applied. The WorldDEM product is based on the radar satellite data acquired during the TanDEM-X Mission, which is funded by a Public Private Partnership between the German State, represented by the German Aerospace Centre (DLR) and Airbus Defence and Space. More details are available in the dataset documentation. Earth Engine asset has been ingested from the DGED files. Note: See the code example for the recommended way of computing slope. Unlike most DEMs in Earth Engine, this is an image collection due to multiple resolutions of source files that make it impossible to mosaic them into a single asset, so the slope computations need a reprojection.

Here we provide a mosaic of the Copernicus DEM 30m for Europe and the corresponding hillshade derived from the GLO-30 public instance of the Copernicus DEM. The CRS is the same as the original Copernicus DEM CRS: EPSG:4326. Note that GLO-30 Public provides limited coverage at 30 meters because a small subset of tiles covering specific countries are not yet released to the public by the Copernicus Programme. Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs.

The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters.

The Copernicus DEM for Europe at 30 m in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/).

Processing steps: The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in https://gdal.org/drivers/raster/vrt.html format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized: gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt

The pixel values were scaled with 1000 (storing the pixels as integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using r.relief, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.

The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. This DSM is derived from an edited DSM named WorldDEM, where flattening of water bodies and consistent flow of rivers has been included. In addition, editing of shore- and coastlines, special features such as airports, and implausible terrain structures has also been applied.

The WorldDEM product is based on the radar satellite data acquired during the TanDEM-X Mission, which is funded by a Public Private Partnership between the German State, represented by the German Aerospace Centre (DLR) and Airbus Defence and Space. OpenTopography is providing access to the global GLO-90 Defence Gridded Elevation Data (DGED) 2023_1 version of the data hosted by ESA via the PRISM service. Details on the Copernicus DSM can be found on this ESA site.

• Previous to July 23rd 2024, OpenTopography was providing access to the Copernicus data through the public AWS S3 bucket established by Sinergise. As of July 23rd 2024, Opentopography is providing the DGED 2023_1 version of GLO-90 as downloaded directly from ESA
• The original gridded data from ESA is in geographic coordinates where the longitudinal cell spacing increases as a function of latitude for regions north of 50N and south of 50S. For more details see the Grid Spacing section of the Copernicus DEM handbook. In order to keep the pixel dimensions uniform, OpenTopography resamples data north of 50 degrees latitude and south of -50 degrees latitude in order to output a consistent 3 Arc-second product for data accessed through the web-interface or API. Users who need data north of 50N or south of 50S, and prefer to use the original, longitude-varying grid spacing can download cloud optimized geotiff (COG) versions of the tiles from our bulk download interface, or download the original data directly from ESA.
• The GLO-90 datasets are available on a free basis for the general public under the terms and conditions of the Copernicus license found here.

The Copernicus DEM is a Digital Surface Model (DSM) that represents the surface of the Earth including buildings, infrastructure and vegetation. The Copernicus DEM is provided in 3 different instances: EEA-10, GLO-30 and GLO-90. Data were acquired through the TanDEM-X mission between 2011 and 2015. The datasets were made available for use in 2019 and will be maintained until 2026.

Kolumbiens Wechselkurs gegenüber dem USD belief sich im 2023-05 auf 4,539.540 USD/COP. Dies stellt einen Anstieg im Vergleich zu den vorherigen Zahlen von 4,526.030 USD/COP für 2023-04 dar. Kolumbiens Wechselkurs gegenüber dem USD werden monatlich aktualisiert, mit einem Durchschnitt von 203.240 USD/COP von 1950-01 bis 2023-05, mit 881 Beobachtungen. Die Daten erreichten ein Allzeithoch in Höhe von 4,922.300 USD/COP im 2022-11 und ein Rekordtief in Höhe von 1.960 USD/COP im 1951-02. Kolumbiens Wechselkurs gegenüber dem USD Daten behalten den Aktiv-Status in CEIC und werden von CEIC Data gemeldet. Die Daten werden unter World Trend Pluss Global Economic Monitor – Table: Exchange Rate against USD: Period Avg: Monthly kategorisiert.

Geospatial data on urban river spaces used in CRiSp (City River Spaces) software and related packages. Contains vector data of the city boundary, spatial networks (street center lines, railway lines), the river (center line and surface), buildings surrounding the river, as well as a digital elevation model for River Dâmbovița in Bucharest. The dataset is derived from OpenStreetMap data (https://www.openstreetmap.org/copyright) and Copernicus GLO-30 DEM data (https://dataspace.copernicus.eu/explore-data/data-collections/copernicus-contributing-missions/collections-description/COP-DEM) and made available under the ODbL 1.0 open database license.

Spatial interpolation is critical in geographic information systems (GIS) and environmental science, particularly when dealing with high-dimensional and nonlinear data. Classical methods like Kriging and inverse distance weighting (IDW) often struggle with the complexities of irregular terrain and sparse datasets, and are inadequate for capturing the nonlinear characteristics of high-dimensional spatial data. In this paper, we introduce a novel interpolation method based on the Denoising Diffusion Probabilistic Model (DDPM), which incorporates ConvNeXt V2 blocks within a UNet architecture. To validate the performance of our model, we employ the Copernicus Digital Elevation Model (COP-DEM) dataset for simulation experiments. Experimental results demonstrate that the proposed DDPM method significantly outperforms classical interpolation techniques, particularly in scenarios with high-density control points, producing high-quality interpolation results with strong transferability. This approach shows considerable promise for spatial interpolation in high-dimensional, complex terrains, offering a more robust alternative to traditional methods. It not only addresses key challenges in interpolation accuracy but also opens up new possibilities for applying generative models in other spatial data processing domains, including environmental monitoring and geospatial modeling.

The dataset represents the work of multiple states and Federal agencies as part of the US Gap Analysis and LandFire programs. Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. The minimum mapping unit for this dataset is approximately 1 acre. Landcover classes are drawn from NatureServe's Ecological System concept. Five-hundred and fourty-four land cover classes composed of 12 cultural and 532 Natural/Semi-natural types are described. Land cover classes were mapped with a variety of techniques including decision tree classifiers, terrian modeling, inductive modeling, and unsupervised classification. The 67 USGS mapping zones were modeled independently of one another by multiple spatial analysis laboratories. Following completion of the national data set each individual land cover type was evaluated by NatureServe through individual working groups and two regional workshops attended by State, Federal, and Heritage Program ecologist. Where individual systems were identified with likely errors a description was recorded of the issue and a fix where available was described and initiated by NatureServe. All changes are available in supporting documentation and represent the opinion of multiple experts.

Foreign Exchange Rate: Month End: Deutsche Mark: Sell data was reported at 2,440.755 DEM/COP in Apr 2025. This records an increase from the previous number of 2,315.697 DEM/COP for Mar 2025. Foreign Exchange Rate: Month End: Deutsche Mark: Sell data is updated monthly, averaging 1,805.770 DEM/COP from Jan 2001 (Median) to Apr 2025, with 167 observations. The data reached an all-time high of 2,635.768 DEM/COP in Apr 2023 and a record low of 995.079 DEM/COP in Jan 2002. Foreign Exchange Rate: Month End: Deutsche Mark: Sell data remains active status in CEIC and is reported by Bank of the Republic of Colombia. The data is categorized under Global Database’s Colombia – Table CO.M009: Foreign Exchange Rate.

The application of InSAR deformation measurements is feasible in a geometry sensitive to deformation. Our sensitivity index is a static analysis of the lower bound of the sensitivity of Sentinel-1 to the downslope deformation of a potential landslide.

The full process is explained in the linked paper (https://doi.org/10.1016/j.jag.2022.102829). Provided here is a global data set of the sensitivity index derived from the Copernicus digital elevation model (COP-DEM_GLO-30, 2019_1).

Individual sheets of 1°×1° are identified by their lower left corner in WGS84. Sheets are combined in archives of 10°×10°, numbered by the truncated sheet indices (e.g. S49_00_W053.tiff is in S40_W050.zip). A sheet index is provided in S_v1.gpkg and as an interactive map. No data is provided over Armenia and Azerbaijan, as these areas were not included in the public Copernicus data. The underlying Python script (20210208_CopernicusSpherical.py) is provided with the data.

外汇汇率：月结：德国马克（德国货币单位）：卖出在04-01-2025达2,440.755DEM/COP，相较于03-01-2025的2,315.697DEM/COP有所增长。外汇汇率：月结：德国马克（德国货币单位）：卖出数据按月更新，01-01-2001至04-01-2025期间平均值为1,805.770DEM/COP，共167份观测结果。该数据的历史最高值出现于04-01-2023，达2,635.768DEM/COP，而历史最低值则出现于01-01-2002，为995.079DEM/COP。CEIC提供的外汇汇率：月结：德国马克（德国货币单位）：卖出数据处于定期更新的状态，数据来源于Banco de la República Colombia，数据归类于全球数据库的哥伦比亚 – Table CO.M009: Foreign Exchange Rate。

Unter Polizeizone versteht man ein Datenpaket, das die territoriale Abgrenzung der Polizeizonen beschreibt, so wie diese in den Königlichen Erlassen vom 28. April 2000 gemäß dem Gesetz vom 7. Dezember 1998 zur Organisation eines auf zwei Ebenen strukturierten integrierten Polizeidienstes definiert sind. Dieses Datenpaket besteht aus zwei Klassen. Die erste enthält die Kennungen, Namen und Geometrien der verschiedenen Zonen; die zweite ist eine Klasse ohne Geometrie und entspricht der Tabelle der belgischen Gemeinden, wobei für jede von ihnen die Polizeizone angegeben ist, von der sie abhängt. Das Datenpaket kann in Form von komprimierten Shapefile-Dateien frei heruntergeladen werden.

Politiebureaus op het grondgebied van de Stad BrusselMeer info: https://www.bruxelles.be/policehttps://be.brussels/en/aide-social-sante/aide-durgence-et-prevention/police