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.
9
datasets available to search
ShareScore release 0.9.0
Dataset results
9 results for “Digital Elevation Map”
Local digital elevation model for the Ayeyarwady Delta in Myanmar (AD-DEM) derived from digitised spot and contour heights of topographic maps
<p><strong>Title:</strong></p> <p>Local digital elevation model for the Ayeyarwady Delta in Myanmar (AD-DEM) derived from digitised spot and contour heights of topographic maps</p> <p><strong>Citation:</strong></p> <p>Seeger, K.; Minderhoud, P. S. J., Peffeköver, A., Vogel, A., Brückner, H., Kraas, F., Nay Win Oo, Brill, D. (2023): Local digital elevation model for the Ayeyarwady Delta in Myanmar (AD-DEM) derived from digitised spot and contour heights of topographic maps. Zenodo, <a href="https://doi.org/10.5281/zenodo.7875965">https://doi.org/10.5281/zenodo.7875965</a>.</p> <p><strong>Supplement to:</strong></p> <p>Seeger, K., Minderhoud, P. S. J., Peffeköver, A., Vogel, A., Brückner, H., Kraas, F., Nay Win Oo, and Brill, D. (2023): Assessing land elevation in the Ayeyarwady Delta (Myanmar) and its relevance for studying sea level rise and delta flooding. EGUsphere [preprint], <a href="https://doi.org/10.5194/egusphere-2022-1425">https://doi.org/10.5194/egusphere-2022-1425</a>.</p> <p><strong>Abstract:</strong></p> <p>The local digital elevation model (DEM) of the Ayeyarwady Delta, referred to as AD-DEM, was generated based on elevation data of topographic maps at scale of 1:50,000 published in 2014 while source data was compiled between 2000 and 2004. Empirical Bayesian Kriging with empirical data transformation and exponential modelling was applied to interpolate ~5100 elevation points (spot heights) and ~13600 elevation points extracted from contour data of the topographic maps. Elevation values higher than 10 m were excluded from interpolation and the SRTM water body mask created in 2000 was applied to the processed AD-DEM. The AD-DEM was transformed from its original vertical reference of local mean sea level at Kyaikkhami tide gauge to continuous mean sea level based on the mean dynamic topography data (CNES-CLS18 dataset of Mulet et al. (2021; <a href="https://doi.org/10.5194/os-17-789-2021">https://doi.org/10.5194/os-17-789-2021</a>) that we transposed to EGM96) in order to account for sea level variations along the Myanmar coast.</p> <p>The AD-DEM contains itself some uncertainty due to the lack of evenly distributed spot heights in areas of the upper delta, for which a separate shapefile is provided. However, we highlight to consider the AD-DEM as being the currently best available model against the background of the lacking possibility of ground truthing and being independent from satellite-based measurements.</p> <p>For further information on data processing, including DEM interpolation, determination of local mean sea level and vertical datum conversions, as well as DEM performance, see the corresponding paper and supplementary material.</p> <p>File name: ADDEM_Con250m_lesseq10_MDT_AD_MMR2000_masked_maskedSRTM.tif</p> <p>File format: GEOTIFF file</p> <p>Spatial reference: MMR2000_46N</p> <p>Vertical reference: local continuous mean sea level, i.e., mean dynamic topography (CNES-CLS18 dataset of Mulet et al. (2021; <a href="https://doi.org/10.5194/os-17-789-2021">https://doi.org/10.5194/os-17-789-2021</a>) transposed to EGM96</p> <p>Cell size: 750 × 750 m</p> <p>File name: DataPoorAreas_MMR2000.shp</p> <p>File format: ESRI Shapefile</p> <p>Spatial reference: MMR2000_46N</p>
A 30-meter terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine
<p>This dataset contains the China terrace map at 30 m resolution in 2018. The map values and their corresponding classes are as follows:</p> <p><em>0: Non-terrace 1: Terrace 255: No data</em></p> <p>The 30 m China terrace map can also be viewed online at <a href="https://cbw.users.earthengine.app/view/chinaterracemap">https://cbw.users.earthengine.app/view/chinaterracemap</a></p> <p><strong>Citations:</strong></p> <p>When using this dataset, please cite both the dataset and the following data description article:</p> <p><em>Cao, B., Yu, L., Naipal, V., Ciais, P., Li, W., Zhao, Y., Wei, W., Chen, D., Liu, Z., and Gong, P.: A 30 m terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine, Earth Syst. Sci. Data, 13, 2437–2456, https://doi.org/10.5194/essd-13-2437-2021, 2021.</em></p> <p> </p>
Radarsat Antarctic Mapping Project Digital Elevation Model, Version 2
The high-resolution Radarsat Antarctic Mapping Project (RAMP) Digital Elevation Model (DEM) combines topographic data from a variety of sources to provide consistent coverage of all of Antarctica.
Digital SAR Mosaic and Elevation Map of the Greenland Ice Sheet, Version 1
The Digital SAR Mosaic and Elevation Map of the Greenland Ice Sheet combines the most detailed synthetic aperture radar (SAR) image mosaic available with the best current digital elevation model. The mosaic image shows both the location of the ice edge and the distribution of melt-related 'scatterers' on the surface. These scatterers include ice lenses and complex layered structure in the percolation zone and bare ice of the ablation zone. Other melt-related features that can be seen include lake and surface meltwater stream channels at lower elevations, as well as ice-marginal lakes.This characterization of the ice sheet provides a reference against which future change can be measured. Changing conditions resulting from climatic variation should show up as changes in the ice margin and shifts in the hydrologic zones. It is hoped that the standard reference provided by this data set can facilitate activities aimed at change detection and promote other work aimed at understanding the processes operating on the ice sheet.The image data are derived from SAR image swaths acquired by the ERS-1 satellite during August of 1992. The mosaic was assembled at the Jet Propulsion Laboratory (JPL) and Goddard Space Flight Center (GSFC). Its component images are a copyrighted product of the European Space Agency. The mosaic, a value-added derived product, is available to individuals and non-profit organizations for research oriented purposes only. The Danish geodetic and cadastral agency Kort-og Matrikelstyrelsen (KMS) compiled the elevation data provided with the product from a number of sources, including field surveys, aerial photographs, and the ERS-1 radar altimeter.
USGS National Map 3DEP 1 Arc-second Digital Elevation Models (DEMs): Full Coverage for U.S. Interstate Highway System
<p>This is an archive of the USGS National Map 3DEP 1 Arc-second Digital Elevation Models (DEMs). While it should be reasonably complete (provided via DVD by USGS), coverage has only been verified to provide full coverage for the U.S. Interstate Highway System (see notes below).</p> <p>Original description:</p> <blockquote> <p>This is a tiled collection of the 3D Elevation Program (3DEP) and is 1 arc-second (approximately 30 m) resolution.The elevations in this Digital Elevation Model (DEM) represent the topographic bare-earth surface. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. [...] The seamless 1 arc-second DEM layers are derived from diverse source data that are processed to a common coordinate system and unit of vertical measure. These data are distributed in geographic coordinates in units of decimal degrees, and in conformance with the North American Datum of 1983 (NAD 83). All elevation values are in meters and, over the continental United States, are referenced to the North American Vertical Datum of 1988 (NAVD88). The seamless 1 arc-second DEM layer provides coverage of the conterminous United States, Hawaii, Puerto Rico, other territorial islands, and much of Alaska and Canada. The seamless 1 arc-second DEM is available as pre-staged products tiled in 1 degree blocks in Erdas .img, ESRI arc-grid, and grid float formats. The seamless 1 arc-second DEM layer is updated continually as new data become available.</p> </blockquote> <p>The archived data here were acquired from two sources:</p> <ul> <li>DVD purchased from USGS on (DATE), as per process described in README.pdf The list of files stemming from the DVD are listed in "manifest_USGS_DVD.txt"</li> <li>manual download of missing grid cells from <a href="https://apps.nationalmap.gov/downloader/#/">https://apps.nationalmap.gov/downloader</a>/ on (DATE), as per procedure described in README.pdf, files are listed in "manifest_missingrasters.txt"</li> </ul> <p> </p>
DS1 DIGITAL ELEVATION MAPS OF COMET 19P/BORRELLY V1.0
This data set contains both the USGS and DLR versions of the digital elevation model of the surface areas of comet 19P/Borrelly 1 (1904 Y2) that were visible and illuminated during the Deep Space 1 encounter. The model was computed using the parallax, caused by the spacecraft's motion, between the highest resolution images. The USGS data set also includes the surface normal directions at each location.
MEaSUREs Greenland Ice Mapping Project (GIMP) Digital Elevation Model V001
This data set consists of an enhanced resolution digital elevation model (DEM) for the Greenland Ice Sheet. It was constructed by combining ASTER and SPOT 5 DEMs over the ice sheet periphery and margin with AVHRR photoclinometry for the interior and far north, and calibrating the data to approximate mean ICESat/GLAS elevations from 2003 to 2009. See <a href="http://nsidc.org/data/measures/gimp">Greenland Ice Mapping Project (GIMP)</a> for related data.
MEaSUREs Greenland Ice Mapping Project (GrIMP) Digital Elevation Model from GeoEye and WorldView Imagery V002
This data set consists of an enhanced resolution digital elevation model (DEM) for the Greenland Ice Sheet, derived from sub-meter resolution, panchromatic stereoscopic imagery collected by the GeoEye-1, WorldView-1, -2, and -3 satellites operated by Maxar Technologies. The DEM was created from in-track image pairs (i.e., both images collected minutes apart along the same orbital pass) and cross-track images (i.e., from different orbits) within the in-track imaging geometry and maximum time separation criteria. The DEM is registered to ATLAS/ICESat-2 L3A Land Ice Height, Version 5 (ATL06, V5) data collected in the summers of 2019 and 2020. See <a href="http://nsidc.org/data/measures/gimp">Greenland Ice Mapping Project (GrIMP)</a> for related data
DS1 DIGITAL ELEVATION MAPS OF COMET 19P/BORRELLY V1.0
This data set contains both the USGS and DLR versions of the digital elevation model of the surface areas of comet 19P/Borrelly 1 (1904 Y2) that were visible and illuminated during the Deep Space 1 encounter. The model was computed using the parallax, caused by the spacecraft's motion, between the highest resolution images. The USGS data set also includes the surface normal directions at each location.
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.