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24 results for “Digital terrain model”
Continental Europe Digital Terrain Model geomorphometry derivatives at 30 m, 100 m and 250 m
<p>Digital Terrain Model geomorphometry derivatives based on the DTM for Continental Europe using the <a href="https://epsg.io/3035">EPSG:3035</a> projection system. Processed using <a href="http://www.saga-gis.org/">SAGA GIS</a>, <a href="https://grass.osgeo.org/grass78/">GRASS 7 GIS</a> and <a href="https://gdal.org/programs/gdaldem.html">GDAL</a> at 3 standard spatial resolutions: 30-m, 100-m and 250-m. Derivatives include:</p> <ul> <li>devmean = deviation from mean value derived using <a href="http://www.saga-gis.org/saga_tool_doc/7.4.0/statistics_grid_1.html">SAGA GIS</a>,</li> <li>downlocal / down = downslope local and general curvature derived using <a href="http://www.saga-gis.org/saga_tool_doc/7.1.1/ta_morphometry_26.html">SAGA GIS</a>,</li> <li>hillshade = hillshading derived using using GDAL <a href="https://gdal.org/programs/gdaldem.html">gdaldem</a> functions,</li> <li>mnr = Module Melton Ruggedness Number derived using <a href="http://www.saga-gis.org/saga_tool_doc/2.2.4/ta_hydrology_23.html">SAGA GIS</a>,</li> <li>northerness/easterness = derived using <a href="https://grass.osgeo.org/grass78/manuals/addons/r.northerness.easterness.html">GRASS 7 GIS</a>,</li> <li>openp / openn = openness positive negative derived using <a href="http://www.saga-gis.org/saga_tool_doc/2.2.5/ta_lighting_5.html">SAGA GIS</a>,</li> <li>slope = slope in percent derived using GDAL <a href="https://gdal.org/programs/gdaldem.html">gdaldem</a> functions,</li> <li>topidx = a topographic index (wetness index) derived using <a href="https://grass.osgeo.org/grass76/manuals/r.topidx.html">GRASS 7 GIS</a>,</li> <li>tpi = Topographic Wetness Index derived using <a href="http://www.saga-gis.org/saga_tool_doc/2.1.3/ta_hydrology_20.html">SAGA GIS</a>,</li> <li>vbf = Multiresolution Index of Valley Bottom Flatness derived using <a href="http://www.saga-gis.org/saga_tool_doc/2.2.6/ta_morphometry_8.html">SAGA GIS</a>,</li> </ul> <p>Detailed processing steps can be found <a href="https://gitlab.com/geoharmonizer_inea/spatial-layers"><strong>here</strong></a>. Read more about the processing steps <a href="https://opendatascience.eu/building-continental-europe-digital-terrain-model-30-m-resolution-using-machine-learning"><strong>here</strong></a>.</p> <p>Derivatives were chosen aiming to support soil and vegetation mapping projects. The slope.percent map at 30-m has been converted from 0-100% scale to 0-200% (Byte format) to help decrease the file size.</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>
Ensemble Digital Terrain Model (EDTM) of the world
<p>Layers include: Ensemble Digital Terrain Model (EDTM) in 250-m resolution. Unit is in metre(m) and precision is in decimetre (dm). Maps are downscaled from 30-m resolution to 250-m in order to fit the size limit. We provide 30-m EDTM and its standard deviation as links:</p> <ul> <li><strong>30-m EDTM</strong></li> </ul> <p><a href="https://s3.eu-central-1.wasabisys.com/openlandmap/dtm/dtm.bareearth_ensemble_p10_30m_s_2018_go_epsg4326_v20230221.tif">https://s3.eu-central-1.wasabisys.com/openlandmap/dtm/dtm.bareearth_ensemble_p10_30m_s_2018_go_epsg4326_v20230221.tif</a></p> <ul> <li><strong>Standard deviation</strong></li> </ul> <p><a href="https://s3.eu-central-1.wasabisys.com/openlandmap/dtm/dtm.bareearth_ensemble_std_30m_s_2018_go_epsg4326_v20230221.tif"><strong>https://s3.eu-central-1.wasabisys.com/openlandmap/dtm/dtm.bareearth_ensemble_std_30m_s_2018_go_epsg4326_v20230221.tif </strong></a></p> <p>Derived using <a href="https://www.eorc.jaxa.jp/ALOS/en/dataset/aw3d30/aw3d30_e.htm">ALOS AW3D</a>, <a href="https://spacedata.copernicus.eu/collections/copernicus-digital-elevation-model">GLO-30</a>, <a href="http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/">MERITDEM</a>, and national DTMs. We derived a lower 10% quantile from all maps. In order to create bare earth data, we used <a href="https://glad.umd.edu/dataset/gedi/">canopy height</a> (canopy height > 2m) and standard deviation (sd > 6m) to mask building and forest in AW3D and GLO-30. Practical processing is written <a href="https://gitlab.opengeohub.org/yu-feng.ho/faen-artifact/-/blob/main/ensemble_dtm.ipynb">here</a> in Python.</p> <p>To access and visualize maps use: <a href="http://www.openlandmap.org/">OpenLandMap.org</a></p> <p>If you discover a bug, artifact or inconsistency, or if you have a question please use some of the following channels:</p> <ul> <li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/-/issues">https://gitlab.com/openlandmap/global-layers/-/issues</a> </li> <li>General questions and comments: <a href="https://disqus.com/home/forums/landgis/">https://disqus.com/home/forums/landgis/</a></li> </ul> <p>All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL in Cloud Optimised GeoTiff (COG). File naming convention:</p> <ul> <li>dtm.bareearth = variable: digital terrain model (m), bare earth</li> <li>ensemble = determination method: ensemble of mutli-source dsm and dtm</li> <li>p10/std = aggregation/statistics method: 10th percentile / standard deviation</li> <li>250m = spatial resolution / block support: 250 m,</li> <li>s = vertical reference: at surface,</li> <li>go = bounding box: global land without Antarctica</li> <li>epsg.4326 = ESPG code: epsg.4326</li> <li>v20230221 = version code: creation date 20230221</li> </ul>
Digital terrain models derived from UAV overflights of the fifteen NPP study sites at Jornada Basin LTER in 2019
This data package contains digital terrain models (DTMs) 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 DTMs using a structure from motion method. These models do not include the elevations of aboveground features such as vegetation and large rocks. The raw images are not provided but can be made available via project PIs. This data package includes one centimeter resolution DTMs of all 15 sites as geotiff raster files. Other derived products from these UAV missions, including orthomosaic photos, digital elevation models, and sparse point clouds, are available in other EDI data packages (knb-lter-jrn.210543001, knb-lter-jrn.210543002, and knb-lter-jrn.210543004, respectively). This study is complete.
Multi-temporal digital terrain models of the NBS experiment in OAL-Austria
<p>Multi-temporal digital terrain models of the NBS experiment in OAL-Austria with a spatial resolution of 10cm, derived from 3D point clouds acquired with a terrestrial laser scanner (Riegl-VZ2000i); Projection: EPSG 31254</p> <p>The TLS-monitoring is intended for assessing the stability of the embankment at the NBS field demonstrator in OAL-Austria. The digital terrain models were acquired after applying the ground classification filter proposed by Axelsson (2000)</p>
Digital Terrain Model of Edeta's land
<p>Here you can find the Digital Terrain Model -DTM- used to create visibility and network paths. Our DTM has been built merging several sheets -666, 667, 668, 694, 695, 696, 720, 721, 722- of the Digital Terrain Model known as DTM05 that can be downloaded from the Centro Nacional de Información Geográfica -CNIG- "[Centro de Descargas](<a href="https://centrodedescargas.cnig.es/CentroDescargas/locale?request_locale=en">https://centrodedescargas.cnig.es/CentroDescargas/locale?request_locale=en</a>)" -download hub-, the Spanish Government official provider of Geographic Information. The original product is described as a Digital Terrain Model 1st Coverage with 5 m grid spacing. The nine sheets were merged and cropped to a final DTM of 7600 by 5600 with the following corner coordinates:</p> <p><br> Upper Left ( 680000.000, 4403000.000)<br> Lower Left ( 680000.000, 4375000.000)<br> Upper Right ( 718000.000, 4403000.000)<br> Lower Right ( 718000.000, 4375000.000)<br> Center ( 699000.000, 4389000.000)</p>
Multi-temporal digital terrain models of the active deep-seated Vögelsberg landslide (OAL-Austria)
<p>Multi-temporal digital terrain models of the active deep-seated Vögelsberg landslide in OAL Austria (Lat: 47.272°, Lon: 11.597°) with a spatial resolution of 50cm. Raster were derived from classified 3D point clouds acquired with a Riegl VUX-1LR unmanned aerial vehicle laser scanner on August 3<sup>rd</sup> 2018, August 14<sup>th</sup> 2019 and November 6<sup>th</sup> 2020 (Projection: EPSG 31254). Ground classification after Axelsson (2000). Data was used to assess topographic changes at the toe of the active deep-seated Vögelsberg landslide in OAL-Austria.</p>
High Resolution Digital Terrain Models of Mercury
<p>Supplementary material of the article:<br> Tenthoff, M.; Wohlfarth, K.; Wöhler, C. High Resolution Digital Terrain Models of Mercury. <em>Remote Sens.</em> <strong>2020</strong>, <em>12</em>, 3989.</p> <p><br> Abstract:<br> We refined our Shape from Shading (SfS) algorithm, which has previously been used to<br> create digital terrain models (DTMs) of the Lunar and the Martian surface, to generate high-resolution<br> DTMs of Mercury from MESSENGER imagery. To adapt the reconstruction procedure to the specific<br> conditions of Mercury and the available imagery, we introduced two methodic innovations. First, we<br> extended the SfS algorithm to enable the 3D-reconstruction from image mosaics. Because most mosaic<br> tiles were acquired at different times and under various illumination conditions, the brightness of<br> adjacent tiles may vary. Brightness variations that are not fully captured by the reflectance model may<br> yield discontinuities at tile borders. We found that the relaxation of the constraint for a continuous<br> albedo map improves the topographic results of an extensive region removing discontinuities at<br> tile borders. The second innovation enables the generation of accurate DTMs from images with<br> substantial albedo variations, such as hollows. We employed an iterative procedure that initializes the<br> SfS algorithm with the albedo map that was obtained by the previous iteration step. This approach<br> converges and yields a reasonable albedo map and topography. With these approaches, we generated<br> DTMs of several science targets such as the Rachmaninoff basin, Praxiteles crater, fault lines, and<br> several hollows. To evaluate the results, we compared our DTMs with stereo DTMs and laser altimeter<br> data. In contrast to coarse laser altimetry tracks and stereo algorithms, which tend to be affected by<br> interpolation artifacts, SfS can generate DTMs almost at image resolution. The root mean squared<br> errors (RMSE) at our target sites are below the size of the lateral image resolution. For some targets,<br> we could achieve an effective resolution of less than 10 m/pixel, which is the best resolution of<br> Mercury to date. We critically discuss the limitations of the evaluation methodology.<br> <br> </p>
Old model (Digital terrain model)
[Scientific Project](http://www.icac.cat/recerca/projectes-de-recerca/projecte/20942/) [Archaeological report 2016](https://www.researchgate.net/publication/311705780_Archaeological_report_-2016-_of_excavation_in_the_visigothic_settlement_of_Valencia_la_Vella_Riba-roja_del_Turia_Valencian_Country_Spain?_iepl%5BviewId%5D=XzB9abVr2fOR1kpvvnyc8cX4&_iepl%5Bcontexts%5D%5B0%5D=projectUpdatesLog&_iepl%5BtargetEntityId%5D=PB%3A311705780&_iepl%5BinteractionType%5D=publicationTitle) Source: Objaverse 1.0 / Sketchfab
2m Digital Terrain Model Combining LIDAR and Stereo-Enhanced 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 Terrain Model (DTM) for the Niwot Ridge Long Term Ecological Research (LTER) project area at 2 m resolution, and is well suited for hydrologic modeling and other analyses of bare-earth terrain. The DTM is derived from the first reflective surface or a Digital Surface Model (DSM) that was created from 12 micron digital stereo aerial photography. Elevation points were both automatically filtered and hand-adjusted to better represent bare earth conditions. Green Lakes Valley LiDAR (Light Detection and Ranging) point data were appended to the filtered and edited data. Breakline information (ie. ridge tops, lake edges, and streams) was added. A final 2 meter gridded DTM and shaded relief model was then generated. The DTM is useful for terrain analysis and derivation of layers such as slope angle, aspect, shaded relief images, and contours. The DTM 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 DTM 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 geospat
2m Digital Terrain Shaded Relief Model Combining LIDAR and Stereo-Enhanced 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 Terrain Shaded Relief Model (DTM) for the Niwot Ridge Long Term Ecological Research (LTER) project area at 2 m resolution, and is well suited for visualization of bare-earth terrain. The DTM is derived from the first reflective surface or a Digital Surface Model (DSM) that was created from 12 micron digital stereo aerial photography. Elevation points were both automatically filtered and hand-adjusted to better represent bare earth conditions. Green Lakes Valley LiDAR (Light Detection and Ranging) point data were appended to the filtered and edited data. Breakline information (ie. ridge tops, lake edges, and streams) was added. A final 2 meter gridded DTM and shaded relief model was then generated. The DTM is useful for terrain analysis and derivation of layers such as slope angle, aspect, shaded relief images, and contours. The DTM 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 DTM 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 pr
Digital Terrain Model (DTM) from 2005 LiDAR for the Green Lakes Valley, Colorado
This 1m Digital Terrain Model (DTM) is derived from bare-ground Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. This dataset is better suited for derived layers such as slope angle, aspect, and contours. The DTM 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 DTM 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 DTM 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. 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 Surface Model (DSM), is a first-stop elevation layer. A processing report and readme file are included with this data release. The DTM 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 importan
Digital Terrain Model (DTM) shaded relief from 2005 LiDAR for the Green Lakes Valley, Colorado
This 1m Digital Terrain Model (DTM) 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 DTM shaded relief 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 DTM 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 DTM 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 Surface Model (DSM), is a first-stop elevation layer. A processing report and readme file are included with this data release. The DTM 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: This EML metadata file does not contain important geospatial data pr
Snow-Off Digital Terrain Model (DTM) shaded relief from 2010 LiDAR Niwot Ridge LTER Project Area, Colorado
Citation: Anderson, S.P., Qinghua, G., and Parrish, E.G., 2012, Snow-on and snow-off LiDAR point cloud data and digital elevation models for study of topography, snow, ecosystems, and environmental change at Boulder Creek Critical Zone Observatory, Colorado: Boulder Creek CZO, INSTAAR, University of Colorado at Boulder, digital media. This 1m Digital Terrain Model (DTM) shaded relief is a snow-off DTM derived from bare-ground Light Detection and Ranging (LiDAR) point cloud data from August 2010 for the Boulder Creek Critical Zone Observatory (CZO), near Boulder Colorado. This dataset is better suited for derived layers such as slope angle, aspect, and contours. The DTM was created from 1,375 LiDAR point cloud tiles subsampled from 10 points/m2 to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the Boulder Creek CZO and NCALM, both funded by the National Science Foundation (NSF). The DTM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 598.92 km^2. The LiDAR point cloud data was acquired with an Optech Gemini Airborne Laser Terrain Mapper (ALTM) and mounted in a Piper Twin PA-31 Chieftain with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from four GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DTM surface was created by mosaicing and then kriging 0.5 x 1 km LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy is at least, but usually better than, 11 cm RMSE at 1 sigma and vertical accuracy is 5-30 cm RMSE at 1 sigma. The layer is available in IMAGINE format approx. 4 GB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum, with FGDC-compliant metadata. A shaded relief model was also generated. A similar la
Bathymetric and terrain digital model (representative of the geomorphological reference condition) of the river-floodplain system corresponding to the Douro reach between Toro and Zamora (Castilla y León).
<p>Digitally edited digital model to represent the previous geomorphological situation in the Toro-Zamora section.</p>
Digital elevation models of terrain and landslide body used for simulation of Liegang landslide (V1)
Open the record for dataset details and reuse information.
Kathmandu, Nepal. Digital Terrain Model.
<p>Kathmandu, Nepal. Digital Terrain Model.</p>
Snow-Off Digital Terrain Model (DTM) from 2010 LiDAR for the Boulder Creek Critical Zone Observatory (CZO), Colorado
This 1m Digital Terrain Model (DTM) is a snow-off DTM derived from bare-ground Light Detection and Ranging (LiDAR) point cloud data from August 2010 for the Boulder Creek Critical Zone Observatory (CZO), near Boulder Colorado. This dataset is better suited for derived layers such as slope angle, aspect, and contours. The DTM was created from 1,375 LiDAR point cloud tiles subsampled from 10 points/m2 to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the Boulder Creek CZO and NCALM, both funded by the National Science Foundation (NSF). The DTM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 598.92 km^2. The LiDAR point cloud data was acquired with an Optech Gemini Airborne Laser Terrain Mapper (ALTM) and mounted in a Piper Twin PA-31 Chieftain with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from four GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DTM surface was created by mosaicing and then kriging 0.5 x 1 km LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy is at least, but usually better than, 11 cm RMSE at 1 sigma and vertical accuracy is 5-30 cm RMSE at 1 sigma. The layer is available in IMAGINE format approx. 4 GB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum, with FGDC-compliant metadata. A shaded relief model was also generated. A similar layer, the Digital Surface Model (DSM), is a first-stop elevation layer. Accessory layers consist of index map layers for point cloud tiles and flight lines, each with detailed attribute information such as acquisition date and tile file name. The DTM is available through an unrestricted public license. Other LiDAR DSMs, DTMs, and point cloud data ava
G-LiHT Digital Terrain Model V001
Goddard’s LiDAR, Hyperspectral, and Thermal Imager ([G-LiHT](https://gliht.gsfc.nasa.gov/)) mission utilizes 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 Terrain Model data product (GLDTMT) is to provide LiDAR-derived bare earth elevation, aspect and slope on the EGM96 Geopotential Model. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and that the collection will continue to grow as aerial campaigns are flown and processed.GLDTMT data are processed as a raster data product (GeoTIFF) at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the digital terrain with a color map applied in JPEG format.
G-LiHT Digital Terrain Model KML V001
Goddard’s LiDAR, Hyperspectral, and Thermal Imager ([G-LiHT](https://gliht.gsfc.nasa.gov/)) mission utilizes 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 Terrain Model Keyhole Markup Language (KML) data product (GLDTMK) is to provide LiDAR-derived bare earth elevation, aspect and slope on the EGM96 Geopotential Model. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and the collection will continue to grow as aerial campaigns are flown and processed. GLDTMK data are processed as a Google Earth overlay KML file at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the digital terrain with a color map applied in JPEG format.
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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)
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.