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107 results for “Digital Elevation Model”
UAV-based colour-infrared orthomosaics and digital elevation models of basalts and rock glaciers on Disko Island, West Greenland
<p><span>This data set contains multispectral surveys conducted with an unoccupied aerial vehicle over rock glaciers and steep mafic outcrops (intrusive and flood volcanics) near the coastline of Disko Island.</span></p> <ul> <li><span>Acquisition date: 07.08.2019 – 10.08.2019</span></li> <li><span>Location: Illukunnguaq, Disko Island, Greenland</span></li> <li><span>UAV: SenseFly eBee Plus</span></li> <li><span>Flight altitude above ground level: >100m</span></li> <li><span>Image Overlap forward/side: various</span></li> <li><span>Camera: Parrot Sequoia multispectral</span></li> <li><span>EPSG: 32622</span></li> <li><span>Center coordinates: 69.885277°N, -52.577724°E</span></li> <li><span>Flight mode: automatic flight plan</span></li> </ul> <p><span>Data products: </span></p> <ul> <li><span>Orthomosaic colour-infrared, 10-16 cm pixel resolution</span></li> <li><span>Colour-infrared spectral bands: 790nm, 660nm, 550nm</span></li> <li><span>DEM, 20-30cm pixel resolution</span></li> <li><span>Data coverage: approx. 5500 x 2500 m</span></li> <li><span>Elevation profile: 20-680m </span></li> <li><span>Processing in Agisoft Metashape</span></li> </ul> <p><span>Additional data supplement for article:<br>Barnes, E. (2020). Assessment of Drone-Borne Multispectral Mapping in the Exploration of Magmatic Ni-Cu Sulphides–an Example from Disko Island, West Greenland. <br><em>URN: urn:nbn:se:uu:diva-418858</em></span></p> <p>MULSEDRO field campaign was conducted under scientific survey licence (VU-00158-2019) within mineral exploration licence MEL 2018-16 by Blue Jay Mining PLC. This research has been supported by the project MULSEDRO, funded by HZDR-HIF & EITRawMaterials (project ID 16193) and the European Union.</p>
Uncertainty Analysis of Digital Elevation Models by Spatial Inference From Stable Terrain – Dataset
<p><strong>Dataset of <a href="https://doi.org/10.1109/jstars.2022.3188922">Hugonnet et al. (2022), Uncertainty Analysis of Digital Elevation Models by Spatial Inference From Stable Terrain</a>.</strong></p> <p>The data is composed of:</p> <ul> <li><strong>For the Mont-Blanc case study: </strong>the Pléiades reference DEM, the SPOT-6 DEM, the Pléiades–SPOT-6 elevation difference, and the forest mask generated from the ESA CCI landcover (delainey polygonization);</li> <li><strong>For the Northern Patagonian Icefield case study: </strong>the ASTER reference DEM, the SPOT-5 DEM, the ASTER–SPOT-5 elevation difference, and the quality of stereo-correlation of the ASTER DEM from MicMac.</li> </ul> <p>The filenames correspond to those used in the <strong>associated GitHub repository</strong>: <a href="https://github.com/rhugonnet/dem_error_study">https://github.com/rhugonnet/dem_error_study</a>. The shapefiles used for masking glaciers are available directly from the <strong>Randolph Glacier Inventory 6.0</strong> at <a href="https://www.glims.org/RGI/">https://www.glims.org/RGI/</a>.</p> <p>The date of the DEMs is in their original format: <strong>year-month-day for all but ASTER</strong> that has the original naming of <a href="https://lpdaac.usgs.gov/products/ast_l1av003/">AST L1A products</a>. <strong>Units are meters</strong> for the DEMs and elevation differences, <strong>and percentages</strong> for the quality of stereo-correlation.</p>
UAV-based orthomosaic and digital elevation model of a basalt outcrop on Disko Island, West Greenland
<p><span>This data set contains an RGB survey conducted with an unoccupied aerial vehicle (UAV) over a flat basaltic outcrop (intrusive and flood volcanics), surrounded by boreal vegetation (Salix species).</span></p> <ul> <li><span>Acquisition date: 13.08.2019</span></li> <li><span>Location: Qullissat (Qutdlikssat), Disko Island, Greenland</span></li> <li><span>UAV: DJI Mavic 1 Pro</span></li> <li><span>Flight altitude above ground level: 75 m</span></li> <li><span>Image Overlap forward/side: 70 % / 70 %</span></li> <li><span>Camera: RGB</span></li> <li><span>EPSG: 32622</span></li> <li><span>Center coordinates: 70.05330°N, -52.97780°E</span></li> <li><span>Flight mode: manual image acquisition</span></li> </ul> <p><span>Data products: </span></p> <ul> <li><span>Orthomosaic RGB 2.3 cm pixel resolution</span></li> <li><span>DEM 5cm pixel resolution</span></li> <li><span>Processing in Agisoft Metashape</span></li> <li><span>Data coverage: approx. 250 x 360 m</span></li> </ul> <p>Acknowledgements</p> <p><span>MULSEDRO field campaign was conducted under scientific survey licence (VU-00158-2019) within mineral exploration licence MEL 2018-16 by Blue Jay Mining PLC. This research has been supported by the project MULSEDRO, funded by HZDR-HIF & EITRawMaterials (project ID 16193) and the European Union.</span></p>
DATABASE OF THE DIGITAL ELEVATION MODELS OF THE SKEIÐARÁRSANDUR KETTLE-HOLES (S ICELAND), JUNE 2022 - PART I
<p>The database concerns kettle-holes of glacial flood origin. They are located at various outwash levels of Skeiðarársandur in S Iceland. The database contains 87 digital elevation models (DEM) with a minimum resolution of 0.05 m and additional files, e.g. field measurements data, frames selected from the video, errors calculation, point cloud, 3D view. These data document the process of obtaining the material using the photogrammetric ‘Structure from Motion’ method from fieldwork conducted in June 2022 through the processing stages in free, mainly open-source software. The data is prepared in the local Cartesian system and includes relative heights, where 0 m is the lowest point of the kettle-hole. The simple technique used, based on filming the landforms with a digital camera, enables mapping of depressions up to 1250 m<sup>2</sup> in the area and a maximum depth of up to 8 m with the assumed high accuracy.</p>
Digital Elevation Models of Hunga Volcano; pre- and post- 15 January 2022 eruption
<p>This dataset contains digital elevation models (DEM) of the Hunga Volcano complex. The first is a pre-2022 eruption elevation model. The second is a post-2022 eruption elevation model.</p><p>Hunga Volcano is a volcanic complex near the island of Tongatapu in the Kingdom of Tonga. The volcano rises from ~2,500 m depth, a caldera at its summit, and two islands, Hunga Tonga and Hunga-Ha'apai, at the on the rim of the caldera. An eruption during December 2014-January 2015 was centered between the islands and combined them into one larger structure named Hunga Tonga – Hunga Ha'apai (HTHH). HTHH erupted violently on 15th January 2022, sending large clouds of ash into the atmosphere, triggering a tsunami, and reducing the size of the islands of Hunga Tonga and Hunga Ha'apai.</p><p>As a result of this event, the NIWA-Nippon Foundation Tonga Eruption Seabed Mapping Project (TESMaP) is a multidisciplinary research plan involving geological, oceanographic and biological studies that centered around three objectives:</p><ol><li>To determine the impacts of volcanic ash on ocean productivity, species composition, and biogeochemical cycling in the water column.</li><li>To determine the immediate nature and extent of the impact of ash fall/turbidity flows on deep-sea sediments and benthic ecosystems.</li><li>To determine the recovery potential of the deep-sea ecosystem.</li></ol><p>This project involved two survey voyages of the volcano and its surrounding waters. The first was carried out from <i>RV Tangaroa</i> in April and May 2022 (Mackay et al., 2022) and the second was carried out by the <i>USV Maxlimer</i> in August 2022.</p><p>TESMaP was funded from a combination of sources including The Nippon Foundation, Japan; the Natural Environmental Research Council, UK, Japan Agency for Marine Earth Science and Technology, the Tangaroa Reference Group (TRG) for ship time and the NIWA Oceans Centre. Support was given by The Nippon Foundation Seabed 2030 project and by GEBCO Alumni.</p>
Digital Elevation Model (DEM) of the Duplin River and adjacent intertidal areas near Sapelo Island, Georgia
Topographic and bathymetric data were collected for the Duplin River and adjacent intertidal areas near Sapelo Island, Georgia, using high-precision multibeam SONAR equipment. The bathymetric survey was performed from 09-Dec-2009 to 12-Dec-2009. This study was conducted to create a base map of bathymetry, morphology and physical habitat of the Duplin River, which is a primary study site of the Georgia Coastal Ecosystems Long Term Ecological Research (GCE-LTER) project.
Digital Elevation Model (DEM) of Doboy Sound at the mouth of the Duplin River near Sapelo Island, Georgia
The purpose of this study was to map the bathymetry of Doboy Sound near the mouth of the Duplin River adjacent to Sapelo Island, Georgia. This study extends a previous bathymetry mapping project conducted in 2009. The primary objective of the Duplin River project in 2009 was to provide data in support of understanding the sediment and water exchange process between intertidal areas and tidal creeks of the Duplin River. The Center for Marine and Wetland Studies (CMWS) surveyed the Doboy Sound using the Simrad EM3002D Multibeam Echosounder (MBES) in April 2011. A digital elevation model (DEM) was then developed based on the depth survey data.
Corrected LIDAR-derived digital elevation model of the Duplin River salt marshes
LIDAR (light detection and ranging) data were acquired on March 9-10, 2009 by the National Center for Airborne Laser Mapping (NCALM) for the Duplin River (35 km2). A 1 m spatial resolution gridded digital elevation models (DEM) was produced from these data. The accuracy of the DEM was assessed using real time kinematic (RTK) GPS ground reference data and elevations were corrected following the method of Hladik and Alber (2012).
Hubbard Brook Experimental Forest: 1 meter LiDAR-derived and Hydro-enforced Digital Elevation Models, 2012
This data package contains a 1 m LiDAR-derived digital elevation model (DEM) and a 1 m hydro-enforced DEM across Hubbard Brook EF. The LiDAR was collected during leaf-off and snow-free conditions by Photo Science, Inc. in April 2012 for the White Mountain National Forest (WMNF). These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Digital elevation models derived from UAV overflights of the fifteen NPP study sites at Jornada Basin LTER in 2019
This data package contains digital elevation models (DEMs) of each of the 15 NPP study sites at the Jornada Basin LTER in southern New Mexico, USA. The models were derived from raw images collected during uncrewed aerial vehicle (UAV) overflight missions conducted in late summer and early autumn of 2019 (1 overflight day per site). For each site one or two missions were flown during an afternoon using a DJI Phantom 4 UAV, and between 450 and 1300 12.4 megapixel RGB images were captured. A subset of images captured at each site were loaded into Agisoft Metashape software to derive digital elevation models using a structure from motion method. These models include elevations of vegetation and other aboveground features. The raw images are not provided but can be made available via project PIs. This data package includes one centimeter resolution DEMs of all 15 sites as geotiff raster files. Other derived products from these UAV missions, including orthomosaic photos, digital terrain models, and sparse point clouds, are available in other EDI data packages (knb-lter-jrn.210543001, knb-lter-jrn.210543003, and knb-lter-jrn.210543004, respectively). This study is complete.
Digital Elevation Models (DEMs) and lava outlines from the 2023 Litla-Hrútur eruption, Iceland, from Pléiades satellite stereoimages
<p><strong>Introduction:</strong></p><p>On the 10th of July 2023, at 16:40, an eruption started in the Reykjanes Peninsula, Iceland, next to the mountain "Litla-Hrútur". As part of the response, the CIEST2 french initiative was activated (Gouhier et al., 2022). Once activated, Pléiades stereoimages were tasked and scheduled for fast delivery within the area of Interest. On the 20th of August 2023 an additional stereopair of images from Pléiades was acquired and processed after the eruption had stopped.</p><p>Once acquired and delivered, the Pléiades images were processed following the methods described in the section below. This repository contains the near-real time results of DEMs, difference maps compared to a pre-eruption DEM, and lava outlines digitized from the difference map and the orthoimage.</p><p> </p><p><strong>Methods</strong>:</p><p>The Pléiades stereoimages were processed using the Ames StereoPipeline (ASP, Shean et al., 2016, see ASP branch in repository), yielding a DEM in 2x2m GSD and an orthoimage in 0.5x0.5m GSD. The processing was done using as only input the stereoimages and their orientation information, as Rational Polynomial Coefficients (RPCs). The <i>parallel_stereo </i>routine performs all the steps needed in the correlation of the stereoimages, yielding a pointcloud which is then interpolated using the routine <i>point2dem</i>. Besides default parameters, the <i>parallel_stereo</i> parameters used for creation of the DEMs were the standard parameters, plus the following ones: </p><p><i>--stereo-algorithm asp_mgm --corr-tile-size 300 --corr-timeout 900 --cost-mode 3 --subpixel-mode 9 --corr-kernel 7 7 --subpixel-kernel 15 15</i></p><p>Once the DEM was created, DEM co-registration was applying in order to align and minimize positional biases between the pre-eruption DEM and the Pléiades DEMs. We followed the co-registration method of Nuth & Kääb (2011), implemented by David Shean's co-registration routines (<a href="https://github.com/dshean/demcoreg">https://github.com/dshean/demcoreg</a>, Shean et al., 2016). The co-registration involved a horizontal and vertical shift of the Pléiades DEMs, as well as a planar tilt correction. The horizontal offset obtained from the DEM co-registration was also applied to the Pléiades orthoimages.</p><p>The pre-eruption DEM used for this study is a survey done on the 27th of September 2022, data collected Birgir Óskarsson and Robert A. Askew (Icelandic Institute of Natural History) and processed by Sydney R. Gunnarsson and Joaquín M.C. Belart (National Land Survey of Iceland). Metadata of this dataset is available here: https://gatt.lmi.is/geonetwork/srv/eng/catalog.search#/metadata/c59da6cf-18ee-44af-a085-afbad0de029a</p><p>Lava outlines were manually digitized from the co-registered Pléiades orthoimages, The lava outlines are available as GeoPackages in the "GPKG" branch of the repository.</p><p>At the moment, the results from Pléiades are used by the Institute of Earth Sciences of the Univesity of Iceland (Jarðvisindustofnun Háskoli Íslands) to estimate lava volumes and effusion rate, following the methods described in Pedersen et al. (2022). Please contact the authors if these data are intended to be used for a similar purpose, in order to avoid conflict of interests or duplicate work. We encourage collaboration and data sharing for the purpose of the monitoring of the eruption and for research applications.</p><p><strong>Data naming convention:</strong></p><p>faf_YYYYMMDD_hhmmss_hhmmss_*align.tif: DEM obtained from the processing, co-registered to the reference pre-eruption DEM.</p><p>faf_YYYYMMDD_hhmmss_hhmmss_*align_diff.tif: Difference of elevation between the Pléiades DEM and the pre-eruption DEM.</p><p>faf_YYYYMMDD_hhmm.gpkg: Polygon containing the lava outlines, extracted from the Pléiades orthoimage and the map of elevation difference.</p><p>0_faf_YYYYMMDD_hhmmss_hhmmss_*fig.png: A figure showing the latest map of elevation difference, overlaid with a hillshade of the latest Pléiades DEM and the latest lava outlines, result of the processing of the Pléiades stereoimages. The figure was created using the tool imviewer.py from the GitHub repository https://github.com/dshean/imview (Shean et al., 2016).</p><p><strong>Data Specifications:</strong></p><ul><li>Cartographic projection: ISN93 / Lambert 1993 (EPSG:3057, <a href="http://https:/epsg.io/3057">https://epsg.io/3057</a>)</li><li>Origin of Elevation: meters above GRS80 ellipsoid (WGS84)</li><li>Raster data format: GeoTIFF</li><li>Raster compression system: LZW</li><li>Vector data format: GeoPackage (<a href="https://www.geopackage.org/">https://www.geopackage.org/</a>)</li><li>Pléiades dataset includes only DEMs because the Pléiades ortho imagery is for licensed use only. Please contact the authors for further information on this.</li></ul><p><strong>Acknowledgements</strong>: </p><p>Pléiades images from July 2023 were provided under the CIEST² initiative (CIEST2 is part of ForM@Ter (<a href="https://en.poleterresolide.fr/">https://en.poleterresolide.fr/</a>). Pléiades images from August 2023 were provided under the CEOS Volcano Supersite (https://ceos.org/ourwork/workinggroups/disasters/gsnl/). Image Pléiades©CNES2023, distribution AIRBUS DS.</p><p><strong>Dataset Attribution</strong>:</p><p>This dataset is licensed under a <a href="https://creativecommons.org/licenses/by-nc/4.0/">Creative Commons CC BY-NC 4.0 International License</a> (Attribution-NonCommercial).</p><p><strong>Citation:</strong></p><p>Please cite this repository as described below:</p><p>Joaquin M.C. Belart, Virginie Pinel, Hannah. I. Reynolds, Etienne Berthier, & Sydney R. Gunnarson. (2023). Digital Elevation Models (DEMs) and lava outlines from the 2023 Litla-Hrútur eruption, Iceland, from Pléiades satellite stereoimages (1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10133203</p>
Digital Elevation Model (DEM) of northern Brøggerhalvøya (Svalbard, Norway) with Ground Sampling Distance (GSD) of 50 cm
<p>HRSC is a multisensor pushbroom instrument with 9 CCD line sensors mounted in parallel that has been in orbit around Mars since January 2004 on ESA’s Mars Express spacecraft (Gwinner et al., 2016). It simultaneously obtains high-resolution stereo, multicolor, and multiphase images. Digital photogrammetric techniques are used to reconstruct the topography on the basis of five stereo channels, which provide five different views of the ground.</p> <p>An airborne version of the HRSC was used for the acquisition of stereo and color images in Svalbard. Since 1997, different airborne versions of HRSC have been developed. The principles of HRSC-AX data processing are described by Gwinner et al. (2006). The orientation data of the camera are reconstructed from a global positioning system inertial navigation system (GPS INS). HRSC-AX has been applied in diverse technical and scientific applications (e.g., Gwinner et al., 1999, 2000; Hauber et al., 2001; Otto et al., 2007) and has also been successfully used to investigate rock glacier activity (Roer and Nyenhuis, 2007). The flight campaign in July–August 2008 covered a total of seven regions in Svalbard: (1) Longyearbyen and the surroundings of Adventfjorden, (2) large parts of Adventdalen, (3) large parts of the Brøggerhalvøya (halvøya = peninsula) in western Spitsbergen (this dataset), (4) the Bockfjorden area in northern Spitsbergen, (5) the northeastern shore of the Palanderbukta and the margin of the adjacent ice cap in Nordaustlandet, (6) an area on Prins Karls Forland, and (7) the area of the abandoned Russian mining settlement of Pyramiden together with the nearby Ebbedalen. </p> <p>This dataset is a Digital Elevation Model (DEM) derived from HRSC-AX stereo images. The elevations recorded in the DEM are ellipsoid heights; i.e., they are not computed with respect to a geoid but to a mathematically defined reference surface, which is a<br>rotational ellipsoid with the equatorial A and B axes both having a radius of 6378.14 km and the polar<br>C axis having a radius of 6356.75 km. This results in an offset of about 36.5m with respect to geoid<br>heights; i.e., sea level in the HRSC-AX DEM is not at 0 m, but at ~36.5 m.</p> <p><strong>References</strong></p> <p>Gwinner, K., Hauber, E., Hoffmann, H., Scholten, F., Jaumann, R., Neukum, G.,<br>Coltelli, M., and Puglisi, G., 1999, The HRSC-A experiment on high reso-<br>lution imaging and DEM generation at the Aeolian Islands, in Proceedings<br>of the 13th International Conference on Applied Geologic Remote Sens-<br>ing: Ann Arbor, Michigan, ERIM International, v. I, p. 560–569.</p> <p>Gwinner, K., Hauber, E., Jaumann, R., and Neukum, G., 2000, High-resolution,<br>digital photogrammetric mapping: A tool for earth science: Eos<br>(Transactions, American Geophysical Union), v. 81, no. 44, p. 513–520,<br>doi:10.1029/00EO00364.</p> <p>Gwinner, K., Coltelli, M., Flohrer, J., Jaumann, R., Matz, K.-D., Marsella, M.,<br>Roatsch, T., Scholten, F., and Trauthan, F., 2006, The HRSC-AX Mt.<br>Etna Project: High-Resolution Orthoimages and 1 m DEM at Regional<br>Scale: International Archives of Photogrammetry and Remote Sensing,<br>v. XXXVI, Part 1, http://isprs.free.fr/documents/Papers/T05-23.pdf.</p> <p>Gwinner, K., Scholten, F., Spiegel, M., Schmidt, R., Giese, B., Oberst,<br>J., Heipke, C., Jaumann, R., and Neukum, G., 2009, Derivation and<br>validation of high-resolution digital elevation models from Mars Express<br>HRSC data: Photogrammetric Engineering and Remote Sensing, v. 75,<br>no. 9, p. 1127–1142.</p> <p>Gwinner, K., Jaumann, R., Hauber, E., et al., 2016, The High Resolution Stereo Camera (HRSC) of Mars Express and its<br>approach to science analysis and mapping for Mars and its satellites: Planetary and Space Science, v. 126, p. 93–138. http://dx.doi.org/10.1016/j.pss.2016.02.014</p> <p>Hauber, E., Slupetzky, H., Jaumann, R., Wewel, F., Gwinner, K., and Neukum,<br>G., 2001, Digital and automated high resolution stereo mapping of the<br>Sonnblick glacier: EARSeL eProceedings, v. 1, no. 1, p. 246–254.</p> <p>Jaumann, R., Neukum, G., Behnke, T., Duxbury, T.C., Eichentopf, K., Flohrer,<br>J., van Gasselt, S., Giese, B., Gwinner, K., Hauber, E., Hoffmann, H., Hoff-<br>meister, A., Köhler, U., Matz, K.-D., McCord, T.B., Mertens, V., Oberst,<br>J., Pischel, R., Reiss, D., Ress, E., Roatsch, T., Saiger, P., Scholten, F.,<br>Schwarz, G., Stephan, K., Wählisch, M., and the HRSC Co-Investigator<br>Team, 2007, The high-resolution stereo camera (HRSC) experiment on<br>Mars Express: instrument aspects and experiment conduct from interplan-<br>etary cruise through the nominal mission: Planetary and Space Science, v.<br>55, p. 928–952, doi:10.1016/j.pss.2006.12.003.</p> <p>Otto, J.-C., Kleinod, K., König, O., Krautblatter, M., Nyenhuis, M., Roer,<br>I., Schneider, M., Schreiner, B., and Dikau, R., 2007, HRSC-A data:<br>A new high-resolution data set with multipurpose applications in physi-<br>cal geography: Progress in Physical Geography, v. 31, no. 2, p. 179–197,<br>doi:10.1177/0309133307076479.</p> <p>Roer, I., and Nyenhuis, M., 2007, Rockglacier activity studies on a regional<br>scale: Comparison of geomorphological mapping and photogrammetric<br>monitoring: Earth Surface Processes and Landforms, v. 32, p. 1747–1758,<br>doi:10.1002/esp.1496.</p>
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>
Digital elevation model mosaic of the Hypanis region, Mars
<p><strong>This dataset accompanies the following papers:</strong></p> <p>Adler et al. (2019) Hypotheses for the origin of the Hypanis fan-shaped deposit at the edge of the Chryse escarpment, Mars: Is it a delta? Icarus, 319, 885-908. doi: https://doi.org/10.1016/j.icarus.2018.05.021</p> <p>Adler et al. (2022) Regional Geology of the Hypanis Valles System, Mars. JGR: Planets, doi: 10.1029/2021JE006994</p> <p><strong>Contents:</strong></p> <p>- DEM mosaic of the Hypanis Valles and deposit region constructed from CTX, HRSC, and MOLA elevation data (geotiff).</p> <p>- Coverage map of CTX, HRSC, and MOLA footprints used (shapefile).</p> <p>- Previews of DEM (greyscale and color) and of coverage map (png)</p> <p><strong>Description:</strong></p> <p>We constructed a regional elevation mosaic (~17 m/pixel) in Adler et al. (2019) archived here. This mosaic incorporates 10 CTX digital elevation models (DEMs) of high resolution, 3 HRSC digital elevation models of medium resolution, and 1 MOLA global DEM of low resolution. Individual CTX DEMs were generated from the stereopairs listed below. Some individual products were calibrated and formatted with the USGS Integrated Software for Imagers and Spectrometers (ISIS) and then Ames Stereo Pipeline. Other products were generated with SOCET SET. All products were controlled to MOLA shot elevation data.</p> <p><strong>Data incorporated:</strong></p> <p><strong>CTX stereopairs:</strong></p> <p><em>ID (nadir-most), ID (resolution [m/pix])</em></p> <p>P07_003631_1920, B09_013296_1920 (17.7 m/pixel)</p> <p>B17_016408_1913, G06_020443_1916 (18.5 m/pixel)</p> <p>J03_046104_1918, F05_037783_1918 (24.0 m/pixel)</p> <p>P08_004264_1912, B06_011951_1916 (17.7 m/pixel)</p> <p>G09_021788_1918, G11_022434_1918 (18.4 m/pixel)</p> <p>B17_016474_1915, B19_017186_1915 (20.2 m/pixel)</p> <p>D19_034816_1921, F01_036293_1920 (24.0 m/pixel)</p> <p>P13_006176_1918, F01_036293_1920 (18.2 m/pixel)</p> <p>D07_029845_1921, D07_029990_1921 (20.2 m/pixel)</p> <p>G21_026601_1918, P04_002774_1922 (20.2 m/pixel)</p> <p><strong>HRSC DA4:</strong></p> <p>H2134 (75 m/pixel)</p> <p>H2145 (50 m/pixel)</p> <p>H0894 (75 m/pixel)</p> <p><strong>MOLA Elevation:</strong></p> <p>128 ppd Elevation (463 m/pixel)</p> <p><strong>Funding:</strong></p> <p>The work to create individual CTX stereopair DEMs was funded by UK Space Agency (UK SA) grants ST/ K502388/1, ST/R002355/1, ST/L00643X/1, and ST/R001413/1. We thank the Science and Technology Facilities Council for supporting science relating to ExoMars Rover landing site selection activities. The work to create a mosaic using these products and others was supported by grants from the NASA Mars Odyssey Project under a subcontract to ASU administered by the Jet Propulsion Laboratory/California Institute of Technology.</p>
Digital Elevation Models of Tweedsmuir Glacier 1950-2018
<p>This dataset contains digital elevation models (DEMs) of Tweedsmuir Glacier, British Columbia, Canada between 1950 and 2018. DEMs from 1950, 1969, 1974, and 1987 were created using Structure-from-Motion photogrammetry in Agisoft Metashape by Meghan A. Sharp. DEMs from 2000, 2007, 2010, and 2018 were acquired from open-source satellite sources (see "Amplification of Surface Topography during Surges of Tweedsmuir Glacier" for sources). All DEMs have been co-registered to ArcticDEM (Porter et al., 2018) using Shean et al (2016)'s open-source tool <em>demcoreg</em>.</p> <p> </p>
Shape from Shading Digital Elevation Model for Oxia Planum Candidate Landing Site
<p>This data set contains the calibrated and map-projected HiRISE image ESP_037558_1985 and the matching Shape from Shading DEM using the method described in Hess et al., (2019a), and in more detail in Hess et al. (2022). The SfS DTM was part of the EPSC abstract Hess et al., (2019b). When using the data please reference Hess et al. (2022) for the method.</p> <p>ESP_037558_1985_30cm_o.cub: Image data in radiances, ISIS cube file, Equirectangular map projection at 0.25 m/pixel resolution.</p> <p>ESP_037558_1985_30cm_DEM.cub: Digital Elevation Model (DEM) with heights in meter, ISIS cube file, Equirectangular map projection at 0.25 m/pixel resolution.</p> <p>Cube files can be converted to other data formats using gdal (https://gdal.org/) or directly loaded in, e.g., ArcGIS or QGIS.</p> <p> </p> <p>Hess, M., Wohlfarth, K., Grumpe, A., Wöhler, C., Ruesch, O., and Wu, B.: ATMOSPHERICALLY COMPENSATED SHAPE FROM SHADING ON THE MARTIAN SURFACE: TOWARDS THE PERFECT DIGITAL TERRAIN MODEL OF MARS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1405–1411, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1405-2019, 2019a.</p> <p>Hess, Marcel. "High Resolution Digital Terrain Model for the Landing Site of the Rosalind Franklin (ExoMars) Rover." Proc. European Planetary Science Congress, EPSC-DPS2019-1533-4, Geneva, Switzerland, 2019b.</p> <p>Hess, M.; Tenthoff, M.; Wohlfarth, K.; Wöhler, C. Atmospheric Correction for High-Resolution Shape from Shading on Mars. <em>J. Imaging</em> <strong>2022</strong>, <em>8</em>, 158. https://doi.org/10.3390/jimaging8060158</p>
Identified Charcoal Hearths from "Slope Analysis of 'Digital Elevation Model for Blue Mountain Charcoal Research Project'"
<p>This is a GeoJSON file that lists all of the potential charcoal hearths along the Blue Mountain of eastern Pennsylvania. For a detailed description of how this data was produced, please see:</p> <p>Carter, Benjamin. (2018, May 29). Description of Methods for Identifying Charcoal Hearths along the Blue Mountain of Pennsylvania. (Version 0.1.0). Zenodo. http://doi.org/10.5281/zenodo.1255101</p> <p>These hearths were identified using this data:</p> <p>Carter, Benjamin. (2018). Slope Analysis of "Digital Elevation Model for Blue Mountain Charcoal Research Project" (Version 0.1.0). Zenodo. http://doi.org/10.5281/zenodo.1252977</p> <p>The above is derived from:</p> <p>Carter, Benjamin P. (2018). Digital Elevation Model for Blue Mountain Charcoal Research Project (Version 0.1.0). Zenodo. http://doi.org/10.5281/zenodo.1252441</p> <p> </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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