Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
4
datasets available to search
ShareScore release 0.9.0
Dataset results
4 results for “Copernicus DEM”
Copernicus Digital Elevation Model (DEM) for Europe at 3 arc seconds (ca. 90 meter) resolution derived from Copernicus Global 30 meter DEM dataset
<p>Overview:<br> 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.</p> <p>The Copernicus DEM for Europe at 3 arcsec (0:00:03 = 0.00083333333 ~ 90 meter) 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/).</p> <p>Processing steps:<br> The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in <a href="https://gdal.org/drivers/raster/vrt.html">VRT</a> 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:</p> <p><code>gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt </code></p> <p>In order to reduce the spatial resolution to 3 arc seconds, weighted resampling was performed in GRASS GIS (using <code>r.resamp.stats -w</code> and 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 <code>r.relief</code>, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.</p> <p>Projection + EPSG code:<br> Latitude-Longitude/WGS84 (EPSG: 4326)</p> <p>Spatial extent:<br> north: 82:00:30N<br> south: 18N<br> west: 32:00:30W<br> east: 70E</p> <p>Spatial resolution:<br> 3 arc seconds (approx. 90 m)</p> <p>Pixel values:<br> meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.)</p> <p>Software used:<br> GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief)</p> <p>Original dataset license:<br> <a href="https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf">https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf</a></p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p>
Copernicus Digital Elevation Model (DEM) for Europe at 30 arc seconds (ca. 1000 meter) resolution derived from Copernicus Global 30 meter DEM dataset
<p>Overview:<br> 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.</p> <p>The Copernicus DEM for Europe at 30 arcsec (0:00:30 = 0.0083333333 ~ 1000 meter) 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/).</p> <p>Processing steps:<br> The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in <a href="https://gdal.org/drivers/raster/vrt.html">VRT</a> 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:</p> <p><code>gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt </code></p> <p>In order to reduce the spatial resolution to 30 arc seconds, weighted resampling was performed in GRASS GIS (using <code>r.resamp.stats -w</code> and 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 <code>r.relief</code>, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.</p> <p>Projection + EPSG code:<br> Latitude-Longitude/WGS84 (EPSG: 4326)</p> <p>Spatial extent:<br> north: 82:00:30N<br> south: 18N<br> west: 32:00:30W<br> east: 70E</p> <p>Spatial resolution:<br> 30 arc seconds (approx. 1000 m)</p> <p>Pixel values:<br> meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.)</p> <p>Software used:<br> GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief)</p> <p>Original dataset license:<br> <a href="https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf">https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf</a></p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p> <p> </p>
Copernicus Digital Elevation Model (DEM) for Europe at 1000 meter resolution (EU-LAEA) derived from Copernicus Global 30 meter DEM dataset
<p>Overview:<br> 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.</p> <p>The Copernicus DEM for Europe at 1000 meter resolution (EU-LAEA projection) 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/).</p> <p>Processing steps:<br> The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in <a href="https://gdal.org/drivers/raster/vrt.html">VRT</a> 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:</p> <p><code>gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt </code></p> <p>In order to reproject the data to EU-LAEA projection while reducing the spatial resolution to 1000 m, bilinear resampling was performed in GRASS GIS (using <code>r.proj</code> and 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 <code>r.relief</code>, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.</p> <p>Projection + EPSG code:<br> ETRS89-extended / LAEA Europe (EPSG: 3035)</p> <p>Spatial extent:<br> north: 6874000<br> south: -485000<br> west: 869000<br> east: 8712000</p> <p>Spatial resolution:<br> 1000 m</p> <p>Pixel values:<br> meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.)</p> <p>Software used:<br> GDAL 3.2.2 and GRASS GIS 8.0.0 (r.proj; r.relief)</p> <p>Original dataset license:<br> <a href="https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf">https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf</a></p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p>
Copernicus Digital Elevation Model (DEM) for Europe at 100 meter resolution (EU-LAEA) derived from Copernicus Global 30 meter DEM dataset
<p>Overview:<br> 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.</p> <p>The Copernicus DEM for Europe at 100 meter resolution (EU-LAEA projection) 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/).</p> <p>Processing steps:<br> The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in <a href="https://gdal.org/drivers/raster/vrt.html">VRT</a> 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:</p> <p><code>gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt </code></p> <p>In order to reproject the data to EU-LAEA projection while reducing the spatial resolution to 100 m, bilinear resampling was performed in GRASS GIS (using <code>r.proj</code> and 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 <code>r.relief</code>, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.</p> <p>Projection + EPSG code:<br> ETRS89-extended / LAEA Europe (EPSG: 3035)</p> <p>Spatial extent:<br> north: 6874000<br> south: -485000<br> west: 869000<br> east: 8712000</p> <p>Spatial resolution:<br> 100 m</p> <p>Pixel values:<br> meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.)</p> <p>Software used:<br> GDAL 3.2.2 and GRASS GIS 8.0.0 (r.proj; r.relief)</p> <p>Original dataset license:<br> <a href="https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf">https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf</a></p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.