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23 results for “digital surface model”
diFUME Digital Surface Model V0.2
<p>Description:</p> <p>Digital Surface Model (V0.2) of Basel for diFUME project. Terrain model (DTM) is calculated from the height model of the Basel-Stadt official survey (<a href="http://www.gva.bs.ch">http://www.gva.bs.ch</a>). The building digital surface model (DSM) combines the DTM product with the building heights derived from the 3D city model (<a href="http://www.gva.bs.ch">http://www.gva.bs.ch</a>). These products describe the height in meters above sea level. Tree crown heights (m above ground level) are derived by the airborne Lidar data (2018 campaign) made available by the civil engineering office of Basel-Stadt (<a href="https://www.tiefbauamt.bs.ch/">https://www.tiefbauamt.bs.ch/</a>).</p> <p> </p> <p>Data specifications:</p> <p>CRS: EPSG:32632 - WGS 84 / UTM zone 32N - Projected</p> <p>Spatial Extent: 392120.0,5266860.0 : 395160.0,5269840.0</p> <p>Temporal Extent: 2015 - 2019</p> <p>Units: meters</p> <p>Width: 3040</p> <p>Height: 2980</p> <p>Bands: 1</p> <p>Pixel Size: 1,-1</p> <p>Data type: Float32 - Thirty two bit floating point</p> <p>GDAL Driver Description: GTiff</p> <p>GDAL Driver Metadata: GeoTIFF</p>
Montserrat Digital Surface Model (1 metre) - March 2019 - Pleiades Photogrammetry (raw, not co-registered)
<p>This tiff file contains a Digital Surface Model (DSM) of the southern portion of Montserrat, Eastern Caribbean, including the Soufrière Hills Volcano. This is the raw DSM, generated via leverage of Pleiades tri-stereo imagery using the DSM-OPT software platform; it has not been co-registered. </p>
Belham River Valley Digital Surface Model (1 metre) - March 2019 - Pleiades Photogrammetry (co-registered)
<p>This tiff contains a Digital Surface Model (DSM) of the Belham River Valley in Montserrat, Eastern Caribbean. This was generated via leverage of Pleiades tri-stereo imagery throught the DSM-OPT software platform. This DSM has been co-registered to a LiDAR DSM (generated in 2010, vertical error 0.15 m) and found to have a vertical error of 2.3 m.</p>
Lesingey Round: digital surface model
Lesingey Round is a hillfort near Penzance in Cornwall, and likely dates to the Iron Age. The monument consists of a roughly circular enclosure surrounded by ramparts with a ditch on the outside. From the partially buried ditch, the ramparts stand over 4.5m high in places. In other areas the ramparts have been damaged. The site sits atop a prominent hill with panoramic views, and is covered by a 'crown' of trees that cover the site. In this model the trees have been digitally removed to allow for a different understanding of the site. This 3D survey was undertaken by the [Curatorial Research Centre](https://curatorialresearch.com) on behalf of Penwith Landscape Partnership (PLP). The site is owned and maintained by the [Cornish Ancient Sites Protection Network](https://cornishancientsites.com/) (CASPN). Source: Objaverse 1.0 / Sketchfab
Twmbarlwm Hillfort & Motte Digital Surface Model
Twmbarlwm (the bare-topped hill) is located at the southern end of the Mynydd Henllys ridge. It overlooks the Ebbw Valley and Risca in South Wales and has panoramic views in all directions. This is the digital surface model version of the drone derived data. The photo-realistic model with detailed annotations of features can be seen here https://skfb.ly/6yyxW The contrast and lighting in this model has been optimized to show the detail of the hillfort defences, the gaps in the hillfort defences which are later breaches through the rampart and the unfinished southern rampart which displays quarry hollows and dumps of spoil. Also visible are the fine parallel stripes in the southern half of the hillfort of plough grooves for undated possible tree or crop planting. The Norman period (late 11th c. AD) motte castle mound lies at the eastern end of the hillfort. Visit the Twmbarlwm Society webpage http://www.twmbarlwm.co.uk/ Source: Objaverse 1.0 / Sketchfab
Lesingey Round: textured digital surface model
Lesingey Round is a hillfort near Penzance in Cornwall, and likely dates to the Iron Age. The monument consists of a roughly circular enclosure surrounded by ramparts with a ditch on the outside. From the partially buried ditch, the ramparts stand over 4.5m high in places. In other areas the ramparts have been damaged. The site sits atop a prominent hill with panoramic views, and is covered by a 'crown' of trees that cover the site. In this model the trees have been digitally removed to allow for a different understanding of the site. This 3D survey was undertaken by the [Curatorial Research Centre](https://curatorialresearch.com) on behalf of Penwith Landscape Partnership (PLP). The site is owned and maintained by the [Cornish Ancient Sites Protection Network](https://cornishancientsites.com/) (CASPN). Source: Objaverse 1.0 / Sketchfab
Comparison among three different Digital Surface Models and their respective hydraulic outcomes in the flood-prone urban area of Navaluenga (Ávila, Spain)
<p>Three different Digital Surface Models (DSMs) generated from LiDAR data are presented. The LiDAR information has been considered as raw data (DSM3) and subjected to some transformations to better represent the urban environment (DSM1). DSM2 is an intermediate state between DSM1 and DSM3. </p> <p>On the other hand, a hydraulic model has been run for each DSM and for two return periods (25 and 500 years), obtaining in all cases the graphical outputs of depths, velocities, Froude numbers and hazard. </p> <p>The different DSMs are named DSM1, DSM2 and DSM3, which can be downloaded in TIN format. The hydraulic outputs associated with the different DSMs can be downloaded in raster format and are named as follows: the Digital Surface Model to which it refers, the return period considered and the type of hydraulic output (depth, velocity, Froude number and hazard).</p> <p>DSM1: Digital Surface Model 1 (TIN format).<br> dsm1_25depth: Depths obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format).<br> dsm1_25froud: Froude numbers obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format).<br> dsm1_25haz: Hazard obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format).<br> dsm1_25veloc: Velocities obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format). <br> dsm1_500depth: Depths obtained when considering the DSM1 and the flow associated with the 500-years return period (raster format).<br> dsm1_500froud: Froude numbers obtained by considering the DSM1 and the flow associated with the 500-years return period (raster format).<br> dsm1_500haz: Hazard obtained by considering the DSM1 and the flow associated with the 500-years return period (raster format).<br> dsm1_500veloc: Velocities obtained by considering the DSM1 and the flow associated with the 500-years return period (raster format).</p> <p>DSM2: Digital Surface Model 2 (TIN format).<br> dsm2_25depth: Depths obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format).<br> dsm2_25froud: Froude numbers obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format).<br> dsm2_25haz: Hazard obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format).<br> dsm2_25veloc: Velocities obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format). <br> dsm2_500depth: Depths obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).<br> dsm2_500froud: Froude numbers obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).<br> dsm2_500haz: Hazard obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).<br> dsm2_500veloc: Velocities obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).</p> <p>DSM3: Digital Surface Model 2 (TIN format).<br> dsm3_25depth: Depths obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format).<br> dsm3_25froud: Froude numbers obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format).<br> dsm3_25haz: Hazard obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format).<br> dsm3_25veloc: Velocities obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format). <br> dsm3_500depth: Depths obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).<br> dsm3_500froud: Froude numbers obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).<br> dsm3_500haz: Hazard obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).<br> dsm3_500veloc: Velocities obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).</p>
2m Digital Surface Model From Photogrammetric Data, Niwot Ridge LTER Project Area, Colorado
Citation: Manley, W.F., Parrish, E.G., and Lestak, L.R., 2009, High-Resolution Orthorectified Imagery and Digital Elevation Models for Study of Environmental Change at Niwot Ridge and Green Lakes Valley, Colorado: Niwot Ridge LTER, INSTAAR, University of Colorado at Boulder, digital media. This dataset is a Digital Surface Model (DSM) for the Niwot Ridge Long Term Ecological Research (LTER) project area at 2 m resolution. The DSM is derived from the first reflective surface that was created from 12 micron digital stereo aerial photography. Elevation points were automatically filtered to represent bare earth conditions and then interpolated to a 2 meter raster dataset. A shaded relief model was then generated. The DSM and shaded relief model covers a total area of 98 km2 and is available in Environmental Systems Research Institute's (ESRI's) GRID format for a total dataset size of 125 MB. They share a UTM zone 13 projection, NAD83 horizontal datum and NAVD88 vertical datum, with FGDC-compliant metadata. The DSM is available through an unrestricted public license, and can be obtained online or on DVD by request (see Distributor contact information below). Imagery available in this series includes orthorectified aerial photography for 1953, 1972, 1985, 1990, 1999, 2000, 2002, 2004, 2006 and 2008. Together, the digital elevation models and imagery will be of interest to land managers, scientists, and others for observation and analysis of natural features and ecosystems. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
2m Digital Surface Shaded Relief Model From Photogrammetric Data, Niwot Ridge LTER Project Area, Colorado
Citation: Manley, W.F., Parrish, E.G., and Lestak, L.R., 2009, High-Resolution Orthorectified Imagery and Digital Elevation Models for Study of Environmental Change at Niwot Ridge and Green Lakes Valley, Colorado: Niwot Ridge LTER, INSTAAR, University of Colorado at Boulder, digital media. This dataset is a Digital Surface Model (DSM) shaded relief for the Niwot Ridge Long Term Ecological Research (LTER) project area at 2 m resolution. The DSM is derived from the first reflective surface that was created from 12 micron digital stereo aerial photography. Elevation points were automatically filtered to represent bare earth conditions and then interpolated to a 2 meter raster dataset. A shaded relief model was then generated. The DSM and shaded relief model covers a total area of 98 km2 and is available in Environmental Systems Research Institute's (ESRI's) GRID format for a total dataset size of 125 MB. They share a UTM zone 13 projection, NAD83 horizontal datum and NAVD88 vertical datum, with FGDC-compliant metadata. The DSM products are available through an unrestricted public license, and can be obtained online or on DVD by request (see Distributor contact information below). Imagery available in this series includes orthorectified aerial photography for 1953, 1972, 1985, 1990, 1999, 2000, 2002, 2004, 2006 and 2008. Together, the digital elevation models and imagery will be of interest to land managers, scientists, and others for observation and analysis of natural features and ecosystems. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
Digital Surface Model (DSM) from 2005 LiDAR for the Green Lakes Valley, Colorado
This 1m Digital Surface Model (DSM) is derived from first-stop Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. The DSM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DSM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DSM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. cm RMSE at 1 sigma. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. A shaded relief model was also generated. A similar layer, the Digital Terrain Model (DTM), is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. A processing report and readme file are included with this data release. The DSM is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: This EML metadata file does not contain
Digital Surface Model (DSM) shaded relief from 2005 LiDAR for the Green Lakes Valley, Colorado
This 1m Digital Surface Model (DSM) shaded relief is derived from first-stop Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. The DSM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DSM shaded relief has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DSM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. cm RMSE at 1 sigma. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. This shaded relief model was also generated. A similar layer, the Digital Terrain Model (DTM), is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. A processing report and readme file are included with this data release. The DSM dataset is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: T
Bathymetric and surface digital model of the river-floodplain system corresponding to the Duero river reach between Toro and Zamora (Castilla y León).
<p>Digitally edited digital model to represent correctly and with hydraulic criteria the bridges, weirs, dips, roads and walls present in the area.</p>
Bathymetric and surface digital model of the urban reach of the Douro River through Zamora (Castilla y León)
<p>The RAR file is composed of all files related to the Digital Bathymetric Model (DBM) and the Digital Surface Model (DSM). Among these files there are: the original rasters files; the files digitally modified to correctly represent all the hydraulic characteristics of the Duero River and those urban characteristics of Zamora; the rasters that represent the error made in both models, calculated by geostatistics; the files related to the geostatistics process. Also, it also includes the integration of both models (DBM plus DSM) to form a High Resolution Urban Digital Model (HRDUM) of the Duero River in it passes through Zamora.</p>
ICAERUS UC5 - RURAL LOGISTICS sample dataset from STRUMICA, NORTH MACEDONIA. Photogrammetry Orthomosaic and Digital Surface Model (DSM).
<table> <tbody> <tr> <td><strong>FOLDER NAME </strong></td> <td><strong>DESCRIPTION</strong></td> </tr> <tr> <td>3D_Point_cloud</td> <td>Photogrammetry 3D point cloud in LAS format</td> </tr> <tr> <td>Digital_Surface_Model</td> <td>2.5D Digital surface elevation model in GeoJPG resampled by x5</td> </tr> <tr> <td>Orthomosaic-GeoJPG</td> <td>Orthomosaic in GeoJPG format resampled by x5</td> </tr> <tr> <td>Orthomosaic-KMZ_tiles</td> <td>Orthomosaic in GeoJPG format in Google KMZ tiles</td> </tr> <tr> <td>Orthomosaic-OpenStreetMaps</td> <td>Orthomosaic in OpenStreetMasps format</td> </tr> <tr> <td>Raw_Images</td> <td>Initial Images captured by DJI Mavic 3E drone</td> </tr> </tbody> </table>
ICAERUS UC5 - RURAL LOGISTICS sample dataset from STRUMICA, NORTH MACEDONIA. Photogrammetry Orthomosaic and Digital Surface Model (DSM).
<table> <tbody> <tr> <td><strong>FOLDER NAME </strong></td> <td><strong>DESCRIPTION</strong></td> </tr> <tr> <td>3D_Point_cloud</td> <td>Photogrammetry 3D point cloud in LAS format</td> </tr> <tr> <td>Digital_Surface_Model</td> <td>2.5D Digital surface elevation model in GeoJPG resampled by x5</td> </tr> <tr> <td>Orthomosaic-GeoJPG</td> <td>Orthomosaic in GeoJPG format resampled by x5</td> </tr> <tr> <td>Orthomosaic-KMZ_tiles</td> <td>Orthomosaic in GeoJPG format in Google KMZ tiles</td> </tr> <tr> <td>Orthomosaic-OpenStreetMaps</td> <td>Orthomosaic in OpenStreetMasps format</td> </tr> <tr> <td>Raw_Images</td> <td>Initial Images captured by DJI Mavic 3E drone</td> </tr> </tbody> </table>
Processing steps to generate a Digital Surface Model based on SPOT-7 tri-stereo images published in the study "An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar inundation areas at volcan Copahue (Argentina & Chile)" in the Journal of South American Earth Sciences https://doi.org/10.1016/j.jsames.2022.104138
<p>The Digital Surface Model (DSM) was created from SPOT-7 tri-stereo images for the Copahue volcano between the border of Argentina and Chile. Two versions of the DSM are provided: an unfiltered product and a final, filtered product. The final product has a spatial resolution of 5-m and was used for lahar inundation modeling for the Copahue volcano (Viotto, Toyos, and Bookhagen 2022, <a href="https://doi.org/10.1016/j.jsames.2022.104138">https://doi.org/10.1016/j.jsames.2022.104138</a> : An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at Volcán Copahue (Argentina & Chile). <em>Journal of South American Earth Sciences</em> ). The dataset provided should be cited together with the article. </p> <p><strong>DSM processing </strong></p> <p>The source images were given by a SPOT-7 snow- and cloud-free triplet (Nadir, Backward and Forward) of 1.5 m spatial resolution from 19 April 2018 (SPOT Image, Airbus Defence and Space GmbH, distributed by CONAE; Dataset ID: <em>SEN_SPOT7_20180419_142955500_000</em>, delivered by CONAE as <em>DS_SPOT7_20180419</em>).</p> <p>The data were processed with the suite of digital photogrammetry tools AMES Stereo Pipeline ASP (Beyer et al., 2018). The procedure for the generation of the DSM is summarized by following steps: </p> <ol> <li> <p>The orbital parameters (RCP models) were adjusted using the bundle adjustment tool with no ground control points, since they were unavailable.</p> </li> <li> <p>The scenes were map-projected onto the NASADEM (spatial resolution of 30 m) elevation dataset, assisted by the results of the orbital adjustment in Step 1.</p> </li> <li>The stereo correlation of the map-projected scenes including the results of the adjusted orbital parameters, was performed three times, using as first scene (i.e., primary image) the nadir (N), backward (B), and forward (F) images . In each run, the order of images to perform the stereo correlation was: N-F-B, F-N-B, and B-N-F. Thus, three point clouds were generated. Specific ASP correlator settings (other than defaults parameters; for details see the provided stereo-default file) were set in the following way: <em>Correlation Kernel</em>: 15 x 15 pixels; <em>Sub-pixel Refinement Kernel</em>: 21 x 21 pixels; <em>Subpixel Refinement Mode</em>: 2 (Weighted Affine Adaptive Window Correlator EM)</li> <li> <p>The three point clouds were merged into one point cloud with a regular grid of 5 m (unfiltered product, known as <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em>).</p> </li> </ol> <p>The quality of the final point cloud was assessed by comparing the unfiltered DSM with a spatial resolution of 12-m against the WorldDEM<sup>TM</sup> elevation dataset (Collins et al., 2015). The WorldDEM was provided by Airbus Defence and Space GmbH under license for the scope of the Viotto et al., 2022 study. The comparison of the pixel-to-pixel heights above the ellipsoid (WGS84) between the two datasets resulted in a mean difference of 0.67 m and a standard deviation of +/- 4.82 m. </p> <p>Comprehensive details on the methodologies evaluated to create the dataset with ASP, can be found in the corresponding master's thesis “Topografía digital y modelado de lahares en el Volcán Copahue, Argentina-Chile” from S. Viotto (link: https://rdu.unc.edu.ar/handle/11086/15384). Recommended literature about processing DEMs from SPOT imagery is given by Mueting et al., 2021 (<a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330">https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330</a>). </p> <p><strong>Creation of the Final, Filtered DSM product</strong></p> <p>The corrections and improvements applied to the unfiltered product to create the final, filtered DSM (named DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif) are summarized by following steps. </p> <p> </p> <ol> <li> <p><em>Water Bodies Delineation</em></p> </li> </ol> <p>The delineation of the water bodies was based on a mask created from the free access water bodies datasets provided by the Instituto Geográfico Nacional of Argentina (<a href="https://www.ign.gob.ar/NuestrasActividades/InformacionGeoespacial/CapasSIG">https://www.ign.gob.ar/ NuestrasActividades/InformacionGeoespacia l/CapasSIG</a>) and by the Ministerio de Bienes Nacionales in Chile ( <a href="https://www.ide.cl/index.php/aguas-continentales/item/1508-catastro-de-lagos">https://www.ide.cl/index.php /aguas-continentales/item/1508-catastro-de-lagos</a>). A total of 45 lakes within the area of interest were considered. Lakes with areas below or equal to 25 m2 were smoothed with a median filter in the last step. Lakes with areas above this threshold were filled in with a constant value and their borders were smoothed with a median filter to provide smooth shorelines.</p> <p><em>2 . Void Filling</em></p> <p>Voids (other than water bodies) were filled with the tool “Close Gaps” from Saga GIS software. </p> <p><em>3. Smoothing</em></p> <p>Finally, the elevation dataset was smoothed with a median filter using a 3 x 3 pixel window, excluding water bodies filled in the step 1. </p> <p><strong>Final Remarks and Suggestion</strong></p> <p>The quality assessment of the final version by visual inspection of the hillshades suggested an improvement of the signal to noise ratio. However, the void filling process may be improved.</p> <p><br> </p> <p><strong>Dataset Description</strong></p> <table align="center"> <caption> </caption> <tbody> <tr> <td>Digital Surface Models</td> <td> <p>No Data Value = -9999</p> <p>Format = float 32 bit</p> <p>File Format = GeoTiff</p> <p>Vertical Datum: WGS84</p> <p>Projection information: EPSG 32719 (UTM19S)</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>) </p> <p>Versions: </p> <ul> <li> <p>Unfiltered product: without corrections <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em></p> </li> <li> <p>Final, filtered product: smoothed and void filled <em>DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</em></p> </li> </ul> </td> </tr> <tr> <td>Water Bodies Mask</td> <td> <p>No Lake Value = 0</p> <p>Lakes Values = 1 to 45</p> <p>File Format= GeoTiff</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>)</p> <p>Projection information : EPSG 32719 (UTM19S)</p> <p><em>WB_mask_5m_UTM19S.tif</em></p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p><strong>Repository structure</strong></p> <p>|__ 01_Scripts</p> <p> |+ run21_CopahueDSM_AMES_sviotto.sh</p> <p> |+ stereo.default</p> <p>|__ 02_DSMs</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_raw.tif</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</p> <p> |+ WB_mask_5m_UTM19S.tif</p> <p><strong>References</strong></p> <p>Beyer, R. A., Alexandrov, O., & 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. <a href="https://doi.org/10.1029/2018EA000409">https://doi.org/10.1029/2018EA000409</a></p> <p>Collins, J., Riegler, G., Schrader, H., Tinz, M., 2015. Applying terrain and hydrological editing to TanDEM-X data to create a consumer-ready worlddem product. Int. Arch. Photogram. Rem. Sens. Spatial Inf. Sci. 40 (7), 1149. https://doi.org/10.5194/isprsarchives-XL-7-W3-1149-2015.</p> <p>Mueting, A., Bookhagen, B., & Strecker, M. R. (2021). Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina. <em>Journal of Geophysical Research: Earth Surface</em>, 126, e2021JF006330. <a href="https://doi.org/10.1029/2021JF006330">https://doi.org/10.1029/2021JF006330</a></p> <p>Viotto, S., Toyos, G., & Bookhagen, B. (2022). An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at volcán copahue (Argentina & Chile). Journal of South American Earth Sciences, 104138. https://doi.org/10.1016/j.jsames.2022.104138</p> <p> </p> <p> </p>
Orthoimages and digital surface models of the largest Argentine Islands in the Antarctic by UAV photogrammetry
<p>These data contain photogrammetrical data collected by unmanned aerial vehicle (UAV) from February to March 2018 in the Argentine Islands, Wilhelm Archipelago, West Antarctica. The data include processed data (orthoimages and digital surface models) with the Structure-fom-Motion photogrammetrical software Agisoft Metashape. Data are cropped by the outlines of islands.</p> <p>Data are organized by the name of the surveyed island.</p> <p>The coordinate system used is UTM Zone 20S based on WGS84.</p> <p>The data are related to the article "High-resolution orthophoto map and digital surface models of the largest Argentine Islands (the Antarctic) from unmanned aerial vehicle photogrammetry", Lamsters, K., Karušs, J., Krievāns, M., Ješkins, J., 2020. Journal of Maps. https://doi.org/10.1080/17445647.2020.1748130</p>
G-LiHT Digital Surface Model V001
Goddard’s LiDAR, Hyperspectral, and Thermal Imagery ([G-LiHT](https://gliht.gsfc.nasa.gov/)) mission is a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico.The purpose of G-LiHT’s Digital Surface Model data product (GLDSMT) is to provide LiDAR-derived visualizations of elevation above bare earth. GLDSMT data is offered in multiple formats, including Digital Surface Model, Mean, Aspect, Rugosity, and Slope.GLDSMT data are processed as multiple raster data products (GeoTIFFs) at a nominal 1 meter spatial resolution over locally defined areas. A low resolution browse is also provided showing the digital surface model with a color map applied in PNG format.
SnowEx21 Prairie Station Digital Surface Models from UAV-LiDAR V001
This dataset consists of Digital Surface Models (DSMs) derived from UAV-LiDAR acquired during the SnowEx 2021 field campaign at the Central Agricultural Research Center in central Montana (USA). The DSMs are at 0.3 m resolution and consist of one snow-off and seven snow-on flights.
SMAPVEX19-22 Millbrook Lidar Derived Digital Surface Model V001
These digital surface model (DSM) data consist of surface elevations derived from source lidar measurements collected in August 2022 in the vicinity of Millbrook, NY during the SMAPVEX19-22 campaign. The location was selected due to its forested land cover, as SMAPVEX19-22 aims to validate satellite derived soil moisture estimates in forested areas. The August collection period was selected to characterize ‘leaf-on’ conditions. DSM data represents the highest elevation of features on the Earth’s surface, which may include bare-earth, vegetation, and human-made objects.
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
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.