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107 results for “digital elevation models”
Gummern - Digital elevation model 0.5 m, created from Pléiades Neo tri-stereo satellite imagery
<h2>Abstract</h2> <p>Digital surface model, spatial resolution 0.5 m, produced from Pleiades Neo Tri-Stereo imagery & Ground control points for Pleiades Neo tri-stereo orientation.</p> <p>This depositry contains data generated within the European S34 project.</p> <h2>Metadata Information</h2> <table> <tbody> <tr> <td> <p><strong>Identification</strong></p> </td> </tr> <tr> <td> <p>Full Title</p> </td> <td> <p>Gummern_PleiadesNeo_DSM05m & Gummern_PleiadesNeo_GCPs</p> </td> </tr> <tr> <td> <p>Abstract</p> </td> <td> <p>Digital surface model, spatial resolution 0.5 m, produced from Pleiades Neo Tri-Stereo imagery & Ground control points for Pleiades Neo tri-stereo orientation</p> </td> </tr> <tr> <td> <p>Keywords</p> </td> <td> <p>surface model, Pleiades Neo, tri-stereo</p> </td> </tr> <tr> <td> <p>Pilot area</p> </td> <td> <p>Gummern</p> </td> </tr> <tr> <td> <p>Associated resources</p> </td> <td> <p>Gummern_PleiadesNeo_GCPs</p> </td> </tr> <tr> <td> <p>Language</p> </td> <td> <p>English</p> </td> </tr> <tr> <td> <p>URL</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Categories</p> </td> <td> <p>Elevation & GNSS</p> </td> </tr> <tr> <td> <p><strong>Temporal reference</strong></p> </td> </tr> <tr> <td> <p>Creation date (dd.mm.yyyy)</p> </td> <td> <p>1.10.2023 (27.10.2023 – GNSS)</p> </td> </tr> <tr> <td> <p>Revision date (dd.mm.yyyy)</p> </td> <td> <p>1.12.2023 (6.11.2023 – GNSS)</p> </td> </tr> <tr> <td> <p><strong>Quality and validity</strong></p> </td> </tr> <tr> <td> <p>Representation type</p> </td> <td> <p>Raster / Vector</p> </td> </tr> <tr> <td> <p>Fromat</p> </td> <td> <p>GeoTIFF / CSV</p> </td> </tr> <tr> <td> <p>Lineage</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Spatial resolution</p> </td> <td> <p>0.5m</p> </td> </tr> <tr> <td> <p>Positional accuracy</p> </td> <td> <p>0.30m (0.01m – GNSS)</p> </td> </tr> <tr> <td> <p>Maintenance information</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Coordinate system</p> </td> <td> <p>EPSG 25833</p> </td> </tr> <tr> <td> <p><strong>Constranits related to access and use</strong></p> </td> </tr> <tr> <td> <p>Use limitation</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Access constraint</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Public/Private</p> </td> <td> <p>Public</p> </td> </tr> <tr> <td> <p><strong>Responsible organisation</strong></p> </td> </tr> <tr> <td> <p>Responsible Contact</p> </td> <td> <p>Dejan Grigillo (dejan.grigillo@fgg.uni-lj.si)</p> </td> </tr> <tr> <td> <p>Responsible Party</p> </td> <td> <p>UL</p> </td> </tr> <tr> <td> <p><strong>Metadata on metadata</strong></p> </td> </tr> <tr> <td> <p>Contact</p> </td> <td> <p>Dejan Grigillo (dejan.grigillo@fgg.uni-lj.si)</p> </td> </tr> <tr> <td> <p>Metadata language</p> </td> <td> <p>English</p> </td> </tr> </tbody> </table>
Post-remediation evaluation of contaminated site using geophysical methods: Digital Elevation Model Olkusz (Poland) 20220629
<p>The Digital Elevation Model is based on 449 aerial photos taken by a Mavic PRO Unmanned Aerial Vehicle (UAV) fitted with an FC220 camera (focal<br> length: 35 mm; charge-coupled device: 5472 × 3078 pixels, DJI, Shenzhen, China) on 29 June 2022. The final product is a DEM with a 51.1 cm/pix raster field resolution. These products were mapped in the ellipsoid WGS 84 (EPSG:4326). </p> <p>This research was funded by National Science Centre, Poland MINIATURA-5 2021/05/X/ST10/00673 “Post-remediation evaluation of contaminated site using geophysical methods”</p>
Historical digital elevation models (DEMs) and orthoimage mosaics for North American Glacier Aerial Photography (NAGAP) program, version 1.0
<p>This data archive contains digital elevation models (DEMs) and orthoimages generated from scanned historical aerial photographs from the North American Glacier Aerial Photography program available from the NSF Arctic Data Center (ADC, arcticdata.io). </p> <p>The scanned images were preprocessed using the <a href="https://github.com/friedrichknuth/hipp">Historical Image Pre-Processing</a> v0.1 software. Photogrammetric processing was performed with the <a href="https://github.com/friedrichknuth/hsfm">Historical Structure from Motion</a> v0.1 software. </p> <p>All DEM and orthoimage products are provided in the UTM Zone 10N (EPSG:32610) projected coordinate system. Elevation values are in meters above the WGS84 ellipsoid. </p> <p>See <a href="https://www.sciencedirect.com/science/article/pii/S0034425722004850">manuscript</a> and <a href="https://ars.els-cdn.com/content/image/1-s2.0-S0034425722004850-mmc1.pdf">supplement</a> for processing details and further dataset description.</p> <p>This release contains data products for two study sites in Washington state, USA:</p> <p><strong>Mount Baker</strong><br> 1970-09-09<br> 1970-09-29<br> 1974-08-10<br> 1977-09-27<br> 1979-10-06<br> 1987-08-21<br> 1990-09-05<br> 1991-09-09<br> 1992-09-15<br> 1992-09-18</p> <p><strong>South Cascade</strong><br> 1967-09-21<br> 1970-09-29<br> 1974-08-10<br> 1977-10-03<br> 1979-08-20<br> 1979-10-06<br> 1984-08-14<br> 1986-09-05<br> 1987-08-21<br> 1990-09-05<br> 1991-09-09<br> 1992-07-28<br> 1992-09-15<br> 1992-09-18<br> 1992-10-06<br> 1994-09-06<br> 1996-09-10<br> 1997-09-23</p> <p>The 00_thumbnails.jpg provides a quicklook overview at both sites.</p> <p><strong>The DEM and ortho file names are structured as follows:</strong><br> hsfm_NAGAP_[site-name]_[date]_[type].tif</p> <p><strong>For example:</strong><br> hsfm_NAGAP_south-cascade_19670921_ortho.tif</p> <p><strong>Where:</strong><br> [site-name] = Either mount-baker or south-cascade<br> [date] = Image acquisition date in YYYYMMDD format<br> [type] = File type</p> <p><strong>For each DEM and ortho pair, we provide the following:</strong><br> _1m_dem.tif = Digital elevation model posted at 1 m resolution <br> _ortho.tif = Orthoimage mosaic posted at the median image ground sample distance, rounded up to the nearest second decimal place.<br> _metadata.tar.gz = Metadata tarball containing:<br> _ortho_footprints.geojson = Orthoimage mosaic footprint polygons provided in GeoJSON format (EPSG:4326)<br> _dem_footprints.geojson = DEM footprint polygons provided in GeoJSON format (EPSG:4326)<br> _cameras.csv = Image file names, positions, and orientations</p>
DATABASE OF THE DIGITAL ELEVATION MODELS OF THE SKEIÐARÁRSANDUR KETTLE-HOLES (S ICELAND), JUNE 2022 - Part II. VIDEO
<p>The database contains 83 video files in .MOV format, shot by a digital camera at 23.98 frames per second. The average length of videos is 100–600 seconds. They are documentation of fieldwork carried out in June 2022, aimed at preparing the footage to generate high-resolution digital elevation models (Part I) using the 'Structure from Motion' technique. The study covered kettle-holes of the glacial flood origin located at Skeiðarársandur in S Iceland.</p>
Digital Elevation Models, orthoimages and lava outlines of the 2021 Fagradalsfjall eruption: Results from near real-time photogrammetric monitoring
<p>This repository contains the data behind the work described in Pedersen et al (in review), specifically the Digital Elevation Models (DEMs), orthoimages and lava outlines created as part of the near-real time monitoring of the Fagradalsfjall 2021 eruption (SW-Iceland).</p> <p>The processing of the data is explained in detail in the Supplement S2 of Pedersen et al (2022).</p> <p>The data derived from Pléiades surveys includes only the DEMs and the lava outlines. The Pléiades-based orthoimages are subject to license. Please contact the authors for further information about this.</p> <p><strong>Convention for file naming:</strong></p> <p>Data: DEM, Ortho, Outline</p> <p>YYYYMMDD_HHMM: Date of acquisition</p> <p>Platform used: Helicopter (HEL), Pléiades (PLE), Hasselblad A6D (A6D)</p> <p>Origin of elevations in DEMs: meters above ellipsoid (zmae)</p> <p>Ground Sampling Distance: 2x2m (DEM) and 30x30cm (Ortho)</p> <p>Cartographic projection: isn93 (see cartographic specifications for further details)</p> <p> </p> <p><strong>Cartographic specifications:</strong></p> <p>Cartographic projection: ISN93/Lambert 1993 (EPSG: 3057, https://epsg.io/3057)</p> <p>Horizontal and vertical reference frame: The surveys after 18 April 2021 are in ISN2016/ISH2004, updated locally around the study area in April 2021 (after pre-eruptive deformations occurred). The rest of the surveys of late March and early April were created using several floating reference systems (see Supplement S3 for details), since no ground surveys were available during the first weeks of the data collection. The surveys of 23 March 2021, 31 March 2021 were re-procesed in Gouhier et al., 2022, using the survey done on 18 May 2021 as reference.</p> <p>Origin of elevations: Ellipsoid WGS84</p> <p>Raster data format: GeoTIFF</p> <p>Raster compression system: ZSTD (http://facebook.github.io/zstd/)</p> <p>Vector data format: GeoPackage (https://www.geopackage.org/)</p>
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>
30 meter digital elevation model (DEM) clipped to the Andrews Experimental Forest, 1996
Elevation Model for the HJ Andrews Experimental Forest (30 meter DEM). This dataset includes the raw DEM, and several value added products. The products are contour lines, aspect, percent slope, and a hill shade for relief mapping.
10 meter digital elevation model (DEM) clipped to the Andrews Experimental Forest, 1998
A Digital Elevation Model (DEM) is a digital data file containing an array of elevation information over a portion of the earth's surface. This array is developed using information extracted from digitized elevation contours from Primary Base Series (PBS) maps. FSTopo or PBS are 1:24,000 scale topographic maps. This dataset is a digital elevation model grid at a resolution of 10 meters by 10 meters. The data was originated from 1:24,000 scale topographic maps (primarily contours). The base data is in the form of an esri lattice file. Derived datasets include generated contours at 10, 25, and 50 meter intervals, degree slope, aspects, and a hillshade for topographic visualization.
Caribou Poker Creek Research Watershed GIS Data: Digital Elevation Model (DEM)
This file contains one of many raster grids of the Elevation Derivatives for National Applications (EDNA), a multi-layered database that provides systematic and consistent topographically-derived hydrologic derivatives. The filled DEM grid was created from the original elevation data by filling all of the depressions, or sinks, in the original DEM. To create this grid, an algorithm was used to loacted and fill all depressions or sinks where there was no flow from pixel to pixel. During this process, efforts were made to maintain natural sink features. Originator: U.S. Geological Survey. Publication_Date: 2006. Title: cpcrw_dem.tif. Edition: Stage I Data. Geospatial_Data_Presentation_Form: Remote-sensing image. Series_Information: Series_Name: Elevation Derivatives for National Applications (EDNA). Publication_Information: Publication_Place: USGS EROS, Sioux Falls, South Dakota. Publisher: U.S. Geological Survey.
Bonanza Creek Experimental Forest GIS Data: Digital Elevation Model (DEM)
This file contains one of many raster grids of the Elevation Derivatives for National Applications (EDNA), a multi-layered database that provides systematic and consistent topographically-derived hydrologic derivatives. The filled DEM grid was created from the original elevation data by filling all of the depressions, or sinks, in the original DEM. To create this grid, an algorithm was used to loacted and fill all depressions or sinks where there was no flow from pixel to pixel. During this process, efforts were made to maintain natural sink features. Originator: U.S. Geological Survey. Publication_Date: 2006. Title: bcef_dem.tif. Edition: Stage I Data. Geospatial_Data_Presentation_Form: Remote-sensing image. Series_Information: Series_Name: Elevation Derivatives for National Applications (EDNA). Publication_Information: Publication_Place: USGS EROS, Sioux Falls, South Dakota. Publisher: U.S. Geological Survey.
June - December 2009 RTK survey of salt marsh plant ground elevations to assess the accuracy of a LIDAR-derived digital elevation model.
Real time kinematic (RTK) GPS survey of ground elevations for six plant species (Spartina alterniflora, Juncus roemerianus, Batis maritima, Distichlis spicata, Salicornia virginica and Borrichia frutescens) and two non-vegetated cover classes (salt pan and intertidal mud) was carried out from June to December 2009 to assess the accuracy of a LIDAR-derived digital elevation model. In total, 1389 ground control points (GCP) were collected for the Duplin River (Sapelo Island) and Blackbeard Creek (Blackbeard Island) salt marshes.
Digital Elevation Model - Ipswich Watershed - Idrisi Raster File.
This datalayer is part of a group of layers used for research in the Ipswich River Watershed. This is Digital Elevation Model data for the study area, in a 30-meter grid. The source elevation tile data was provided on the MassGIS website www.state.ma.us/mgis/massgis.htm in ESRI-format shapefile format and imported into IDRISI software using the ShapeIdr command. The resulting vector elevation files were converted to raster format using successive Lineras macro commands. This has the effect of mosaicing the tiles as well. The raster image was filtered once using a low-pass (mean) filter, then masked to the Ipswich study area parameters (extent). This datalayer was produced as part of a research project concerning the Ipswich River Watershed.
Lidar digital elevation models and topographic change detection results from burned and unburned plots in the Sevilleta LTER.
These data were generated as part of a research project focused on montiroing sediment flux in dryland ecosystems following wildfire. In six separate small plots, three burned and three unburned, we conducted light detection and ranging (lidar) topographic surveys in 2016, 2017, and 2018 to document elevation changes and the volume of sediment deposition and erosion. At the down-wind edge of each plot, we used sediment catchers to trap sediment exiting the plots and thus estimate erosion volumes using in-situ equipment, which provided a secondary measurement of sediment efflux from all sites in addition to the lidar data. We used the geomorphic change detection software (https://gcd.riverscapes.xyz/) to produce maps of topographic change from the lidar digital elevation models for the 2016-2017 and 2017-2018 periods at all plots, burned and unburned. Results from this project may aid in understanding post-fire transport of sediment and nutrients from drylands following wildfire.
Digital Elevation Models of Hunga Volcano, Tonga, from the MAX2201 voyage, July-August 2022
<p>This dataset contains digital elevation models (DEM) of the Hunga Volcano complex, These DEM are from the MAX2201 voyage of the USV <i>Maxlimer</i> which surveyed the volcano July-August 2022.</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 (<strong>TESMaP</strong>) 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>(TAN2206) in April and May 2022 (Mackay et al., 2022) on the flanks of Hunga volcano and its surrounds; and the second was carried out over the summit of Hunga volcano by the <i>USV Maxlimer</i> (MAX2201) 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>
Colour Palettes for Digital Elevation Models
<p>We provide a collection of 18 colour palettes for the efficient visualisation of Digital Elevation Models (DEMs), for example in the form of heatmaps. More precisely, we propose a combination of palettes from our own production and palettes extracted from the GEneral Bathymetric Chart of the Oceans (GEBCO), including their most recent charts as well as first editions of their paper charts from 1910-1930, 1932-1966, 1958-1973 and 1973-1982. These colour palettes have been harmonised in order to span a wide range of elevations, extending from the lowest depth of 11 000 metres, found in the Challenger Deep of the Mariana Trench, to the greatest height of 9 000 metres, reached atop Mount Everest. Moreover, these 18 colour palettes are supplied in the following 5 colour spaces: RGB (Red, Green, Blue), RGB 01, Hexadecimal, HSL (Hue, Saturation, Lightness) and HSV (Hue, Saturation, Value). </p> <p><strong>Related article</strong>: Owein Thuillier, Nicolas Le Josse, Alexandru-Liviu Olteanu, Marc Sevaux, and Hervé Tanguy, Catalogue of coastal-based instances with bathymetric and topographic data. Earth System Science Data Discussions 2024, 1–48. doi:<a href="https://doi.org/10.5194/essd-2024-58" target="_blank" rel="noopener">10.5194/essd-2024-58</a>.</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>
Figure 1: Study area: A Digital Elevation Model of the North Island and the Manawatū-Whanganui dune field
<p>Figure 1 of article: Managing coastal sand drift in the Anthropocene: A case study of the Manawatū-Whanganui Dune Field, New Zealand, 1800s-2020s; authors: Sampath, Ruwan; Beattie, James; Freitas, Joana Gaspar; journal Environment & History [forthcoming]</p> <p>an article accepted in June 29, 2021</p> <p>https://zenodo.org/badge/DOI/10.5281/zenodo.5075980.svg</p>
Supplementary GIS data - Potential and implications of automated pre-processing of LiDAR-based digital elevation models for large-scale archaeological landscape analysis
<p>A supplementary dataset related to the paper discussing preparation of a digital elevation model derived from DMR 5G (LiDAR-based DEM of the Czech Republic) cleaned of modern artificial features. It includes data used as a clipping mask and data produced during the testing phase.</p> <p>Contents:</p> <ul> <li>..\clipping_buffers.gdb\ - Clipping buffers based on ZABAGED dataset used for masking the original data stored as ESRI geodatabase.</li> <li>..\drainages\ - Drainages with Strahler order higher than four (potential watercourses) for the original and filtered DEMs. <ul> <li>drainages_filtered - Drainges identified in the filtered DEM stored as GeoTIFF.</li> <li>drainages_original - Drainges identified in the original DEM stored as GeoTIFF. </li> </ul> </li> <li>..\LSC\ - Locations with significant land surface curvature for the original and filtered DEMs. <ul> <li>LSC_filtered - Significant LSC identified in the filtered DEM stored as GeoTIFF. </li> <li>LSC_original - Significant LSC identified in the original DEM stored as GeoTIFF. </li> </ul> </li> <li>..\visibility\ - Viewsheds computed over the original and filtered DEMs. <ul> <li>Libice\ - Sample viewsheds computed for the early medieval hillfort of Libice. <ul> <li>Libice_visibility_filtered - Viewshed based on the filtered DEM stored as GeoTIFF. </li> <li>Libice_visibility_original - Viewshed based on the original DEM stored as GeoTIFF. </li> <li>observer_points - Observer points used for calculating the viewsheds.</li> </ul> </li> <li>regular_grid\ - Cumulative viewsheds calculated for regularly spaced points in a 10 x 10 km grid with a visibility radius of 5 km and an observer height of 2 m; a total of 574 viewsheds. <ul> <li>visibility_filtered - Cumulative viewshed for the filtered DEM stored as GeoTIFF.</li> <li>visibility_original - Cumulative viewshed for the original DEM stored as GeoTIFF. </li> <li>visibility_test_buffers - Buffers used for the viewshed calculations stored as ESRI shapefile.</li> <li>visibility_test_observers - Observer points used for the viewshed calculations stored as ESRI shapefile.</li> </ul> </li> </ul> </li> </ul> <p> </p> <p>Preprint version of the related paper:</p> <p>Novák, David and Pružinec, Filip, Potential and Implications of Automated Pre-Processing of Lidar-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis. Available at SSRN: <a href="https://ssrn.com/abstract=4063514">https://ssrn.com/abstract=4063514</a></p>
Digital Elevation Model from Pléiades stereo images - Upper Tuolumne basin, California, 2017-08-13
<p><br> Digital Elevation Model (DEM) derived from a triplet of stereo images of the Pléiades satellite.<br> The images were acquired on 13th August 2017 and cover a part of the upper Tuolumne basin (California).<br> The DEM was calculated at a 3 m resolution with the Ames Stereo Pipeline software (Beyer et al., 2018).<br> Details about the processing of the images and the accuracy of the DEM are given in Deschamps-Berger et al. (2020).</p> <p> </p> <p>References<br> Beyer, R. A., Alexandrov, O., and McMichael, S. (2018). The Ames Stereo Pipeline: NASA’s open source software for deriving and processing terrain data. <em>Earth and Space Science</em>, 5, 537–548. https://doi.org/10.1029/2018EA00040</p> <p>Deschamps-Berger, C., Gascoin, S., Berthier,<br> E., Deems, J., Gutmann, E., Dehecq, A., Shean, D., and Dumont, M. (2020).<br> Snow depth mapping from stereo satellite imagery in mountainous terrain :<br> evaluation using airborne lidar data. <em>The Cryosphere</em>, (February):1–28. https://doi.org/10.5194/tc-14-2925-2020</p>
Digital Elevation Models from Planetary Flyby Images of Mercury and the Moon with Shape and Albedo from Shading
<p>Supplemantary material to Krüll, I., Wohlfarth, K., Tenthoff, M., Wöhler, C., Galluzzi, V., Wright, J., Benkhoff, J., and Zender, J.: Shape and Albedo from Shading with Planetary Flyby Images of Mercury and the Moon, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-247, https://doi.org/10.5194/epsc2024-247, 2024.</p> <p><strong>Abstract</strong></p> <p>Surface reconstruction of planetary bodies such as the Moon and Mercury is crucial for geomorphological analysis, reflectance normalization, thermal modeling, rover landing site planning, and outreach activities. Stereo algorithms and Shape-and-Albedo-from-Shading (SAfS) are well-established methods for planetary 3D reconstruction. SAfS refines the surface slopes of a stereo Digital Elevation Model (DEM) and typically yields 3D models at image resolution. This approach is well-validated for scientifically calibrated instruments that observe the planetary body under favorable conditions. This work applied the SAfS algorithm to more challenging planetary flyby images acquired with uncalibrated off-the-shelf cameras. We investigated three scenarios: a fly-by image of the Moon captured by a GoPro during the Artemis I mission, a fly-by image of Mercury which was obtained with a monitoring camera during BepiColombo’s third flyby, and a telescope image taken in Wetter, Germany. We qualitatively and quantitatively assessed the algorithm's performance. The results of the two flyby images indicate that, despite the challenging conditions, the SAfS algorithm could reconstruct the surface up to image resolution and increase the level of detail of the input DEM. The reconstructed DEM of the telescope image is the one with the lowest resolution. All in all, our flyby-derived DEMs are accurate. They provide excellent outreach products, as demonstrated by ESA's BepiColombo flyby movie: https://www.esa.int/Science_Exploration/Space_Science/BepiColombo/BepiColombo_s_third_Mercury_flyby_the_movie</p> <p><strong>Dataset<br></strong></p> <p>We applied the SAfS algorithm to different Regions of Interest (ROIs) in the flyby and telescope images. The ROIs are marked in Artemis_Flyby_ROIs.png, Bepicolombo_Flyby3_ROIs.png and Moon_Telescope_ROIs.png, respectively. For each ROI a DEM is provided centered on the latitude and longitude (0-360, positive east) in the filename. Furthermore a Red/ Blue Stereo anaglyph of the original image was created with the SAfS DEM (for this purpose the height has been exaggerated).</p> <p> </p>
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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)
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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.