The High Resolution Digital Elevation Model (HRDEM) product is derived from airborne LiDAR data (mainly in the south) and satellite images in the north. The complete coverage of the Canadian territory is gradually being established. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived data. For DTM datasets, derived data available are slope, aspect, shaded relief, color relief and color shaded relief maps and for DSM datasets, derived data available are shaded relief, color relief and color shaded relief maps. The productive forest line is used to separate the northern and the southern parts of the country. This line is approximate and may change based on requirements. In the southern part of the country (south of the productive forest line), DTM and DSM datasets are generated from airborne LiDAR data. They are offered at a 1 m or 2 m resolution and projected to the UTM NAD83 (CSRS) coordinate system and the corresponding zones. The datasets at a 1 m resolution cover an area of 10 km x 10 km while datasets at a 2 m resolution cover an area of 20 km by 20 km. In the northern part of the country (north of the productive forest line), due to the low density of vegetation and infrastructure, only DSM datasets are generally generated. Most of these datasets have optical digital images as their source data. They are generated at a 2 m resolution using the Polar Stereographic North coordinate system referenced to WGS84 horizontal datum or UTM NAD83 (CSRS) coordinate system. Each dataset covers an area of 50 km by 50 km. For some locations in the north, DSM and DTM datasets can also be generated from airborne LiDAR data. In this case, these products will be generated with the same specifications as those generated from airborne LiDAR in the southern part of the country. The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013), which is now the reference standard for heights across Canada. Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The tiles are aligned within each project. The product High Resolution Digital Elevation Model (HRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan. Collaboration is a key factor to the success of the National Elevation Data Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.

Goddard’s LiDAR, Hyperspectral, and Thermal Imagery (G-LiHT) mission (https://gliht.gsfc.nasa.gov/) 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 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.

This is a legacy product that is no longer supported. It may not meet current government standards.

The Canadian Digital Surface Model (CDSM) is part of Natural Resources Canada's altimetry system designed to better meet the users' needs for elevation data and products. The 0.75-second (~20 m) CDSM consists of a derived product from the original 1-second (30 m) Shuttle Radar Topographic Mission (SRTM) digital surface model (DSM). In these data, the elevations are captured at the top of buildings, trees, structures, and other objects rather than at ground level.

A CDSM mosaic can be obtained for a pre-defined or user-defined extent. The coverage and resolution of a mosaic varies according to the extent of the requested area.

Derived products such as slope, shaded relief and colour shaded relief maps can also be generated on demand by using the Geospatial-Data Extraction tool. Data can then be saved in many formats.

The pre-packaged GeoTiff datasets are based on the National Topographic System of Canada (NTS) at the 1:50 000 scale; the NTS index file is available in the Resources section in many formats.

The 1 Second DSM Version 1.0 is a gridded Digital Surface Model (DSM) representing the radar reflective surface (bare earth, vegetation and built structures) as observed by the Shuttle Radar Topographic Mission (SRTM) in February 2000. It was derived primarily from the 1 second SRTM Level 2 provided by DIGO, supported by the Geodata 9 Second DEM in void areas and the SRTM surface water database. Stripes and voids have been removed from the 1 second SRTM data to provide an enhanced and complete DSM for Australia and near-shore islands. The grid spacing is 1 second in longitude and latitude (approximately 30 metres).The DSM covers all of continental Australia and near coastal islands land areas including all islands defined by the available SRTM 1 second elevation and Surface Waterbodies Data Base datasets. © Commonwealth of Australia (Geoscience Australia).

This digital dataset was created as part of a U.S. Geological Survey study, done in cooperation with the Monterey County Water Resource Agency, to conduct a hydrologic resource assessment and develop an integrated numerical hydrologic model of the hydrologic system of Salinas Valley, CA. As part of this larger study, the USGS developed this digital dataset of geologic data and three-dimensional hydrogeologic framework models, referred to here as the Salinas Valley Geological Framework (SVGF), that define the elevation, thickness, extent, and lithology-based texture variations of nine hydrogeologic units in Salinas Valley, CA. The digital dataset includes a geospatial database that contains two main elements as GIS feature datasets: (1) input data to the 3D framework and textural models, within a feature dataset called “ModelInput”; and (2) interpolated elevation, thicknesses, and textural variability of the hydrogeologic units stored as arrays of polygonal cells, within a feature dataset called “ModelGrids”. The model input data in this data release include stratigraphic and lithologic information from water, monitoring, and oil and gas wells, as well as data from selected published cross sections, point data derived from geologic maps and geophysical data, and data sampled from parts of previous framework models. Input surface and subsurface data have been reduced to points that define the elevation of the top of each hydrogeologic units at x,y locations; these point data, stored in a GIS feature class named “ModelInputData”, serve as digital input to the framework models. The location of wells used a sources of subsurface stratigraphic and lithologic information are stored within the GIS feature class “ModelInputData”, but are also provided as separate point feature classes in the geospatial database. Faults that offset hydrogeologic units are provided as a separate line feature class. Borehole data are also released as a set of tables, each of which may be joined or related to well location through a unique well identifier present in each table. Tables are in Excel and ascii comma-separated value (CSV) format and include separate but related tables for well location, stratigraphic information of the depths to top and base of hydrogeologic units intercepted downhole, downhole lithologic information reported at 10-foot intervals, and information on how lithologic descriptors were classed as sediment texture. Two types of geologic frameworks were constructed and released within a GIS feature dataset called “ModelGrids”: a hydrostratigraphic framework where the elevation, thickness, and spatial extent of the nine hydrogeologic units were defined based on interpolation of the input data, and (2) a textural model for each hydrogeologic unit based on interpolation of classed downhole lithologic data. Each framework is stored as an array of polygonal cells: essentially a “flattened”, two-dimensional representation of a digital 3D geologic framework. The elevation and thickness of the hydrogeologic units are contained within a single polygon feature class SVGF_3DHFM, which contains a mesh of polygons that represent model cells that have multiple attributes including XY location, elevation and thickness of each hydrogeologic unit. Textural information for each hydrogeologic unit are stored in a second array of polygonal cells called SVGF_TextureModel. The spatial data are accompanied by non-spatial tables that describe the sources of geologic information, a glossary of terms, a description of model units that describes the nine hydrogeologic units modeled in this study. A data dictionary defines the structure of the dataset, defines all fields in all spatial data attributer tables and all columns in all nonspatial tables, and duplicates the Entity and Attribute information contained in the metadata file. Spatial data are also presented as shapefiles. Downhole data from boreholes are released as a set of tables related by a unique well identifier, tables are in Excel and ascii comma-separated value (CSV) format.

This collection is a legacy product that is no longer supported. It may not meet current government standards. The Canadian Digital Elevation Model (CDEM) is part of Natural Resources Canada's altimetry system designed to better meet the users' needs for elevation data and products. The CDEM stems from the existing Canadian Digital Elevation Data (CDED). In these data, elevations can be either ground or reflective surface elevations. A CDEM mosaic can be obtained for a pre-defined or user-defined extent. The coverage and resolution of a mosaic varies according to latitude and to the extent of the requested area. Derived products such as slope, shaded relief and colour shaded relief maps can also be generated on demand by using the Geospatial-Data Extraction tool. Data can then be saved in many formats. The pre-packaged GeoTiff datasets are based on the National Topographic System of Canada (NTS) at the 1:250 000 scale; the NTS index file is available in the Resources section in many formats.

In 2011 AAM was commissioned by the Commonwealth to fly an airborne laser scanning survey (LiDAR) of Christmas Island. The survey was carried out using a fixed wing aircraft between the 24th and 26th of August 2011. All data was captured within approximately 2 hours of low tide. During this period tides ranged from 0.5m to 1.2m. AAM classified the raw LiDAR points into the following classes using a single algorithm across the project area: 0 Unclassified - Created, never classified 1 Default - Unclassified 2 Ground - Bare ground 3 Low vegetation - 0 – 0.3m (essentially sensor 'noise') 4 Medium vegetation - 0.3 – 2m 5 High vegetation - 2m > 6 Buildings, structures - Buildings, houses, sheds, silos etc. 7 Low / high points - Spurious high/low point returns (unusable) 8 Model key points - Reserved for ‘model key points’ only 9 Water - Any point in water 10 Bridge - Any bridge or overpass 11 not used - Reserved for future definition 12 Overlap points - Flight line overlap points The raw LiDAR points in the .las format were provided to Geoscience Australia along with 1km ESRI grid tiles generated by interpolation from the points. The tiles were then joined to create a DEM (TIFF) that covers the full extent of Christmas Island. Each cell, 1m x 1m, in the grid contains the height in metres of the ground surface. As a guide, the DEM data is vertically accurate to 15cm and horizontally accurate to 30cm. Manual checking and editing was carried out by AAM to improve accuracy. Positional accuracy has been checked by Geoscience Australia and was found to match the ground surface well. The DEM data is complete for the full extent of Christmas Island. Disclaimer

Site data contained in the ScrIntrvls_AllSrcRefs_AllWellsRev.csv dataset define the top and bottom altitudes of well screens in 64,763 irrigation wells completed in the Mississippi River Valley alluvial aquifer (MRVA) that constitute a production zone in the Mississippi Alluvial Plain (MAP) extending across the midwestern and southern United States from Illinois to Louisiana. Each well entry contains an Enumerated Domain Value of the Attribute Label SrcRefNo to identify the state environmental agency that contributed to the database, and enumerated values are associated with specific state agencies by using the Enumerated Domain Value Definition. Screen-top and -bottom altitudes and land surface are referenced (corrected) to the National Elevation Dataset (NED) 10-meter digital elevation model (DEM; https://nationalmap.gov/elevation.html). The dataset identifies 50,103 screen-bottom altitudes and 50,457 screen-top altitudes that were used in subsequent geostatistical estimation after spatial analytics filtered out duplicate-coordinate wells, geographic and stratigraphic outliers, and incongruities of screen-top and -bottom altitudes compared with DEM land-surface altitude and the published digital surface of the bottom altitude of the MRVA (https://doi.org/10.3133/sim3426). Well entries are indexed in the dataset to identify use in four regional geostatistical models that collectively encompass the MAP extent and provide gridded estimates of screen-top and-bottom altitudes and estimation uncertainty (estimation variance) associated with each gridded altitude estimate. Digital surfaces of screen-top and -bottom estimates and estimation variances are represented as raster datasets that were converted to netCDF format and conform with the previously published National Hydrologic Grid (https://doi.org/10.5066/F7P84B24) at one-kilometer resolution. This dataset contains high-quality map images for gridded estimates of MRVA screen-top and -bottom altitude and for corresponding gridded estimation variances saved in the Tagged Image File (.tif) format.

The Canadian Digital Elevation Model (CDEM) is part of Natural Resources Canada's altimetry system designed to better meet the users' needs for elevation data and products.

The CDEM stems from the existing Canadian Digital Elevation Data (CDED). In these data, elevations can be either ground or reflective surface elevations.

A CDEM mosaic can be obtained for a pre-defined or user-defined extent. The coverage and resolution of a mosaic varies according to latitude and to the extent of the requested area.

Derived products such as slope, shaded relief and colour shaded relief maps can also be generated on demand by using the Geospatial-Data Extraction tool. Data can then be saved in many formats.

The pre-packaged GeoTif datasets are based on the National Topographic System of Canada (NTS) at the 1:250 000 scale; the NTS index file is available in the Resources section in many formats.

This digital data release contains gridded elevation surfaces for twenty-six (26) subsurface horizons, a grid of the estimated thickness of strata eroded during the Cenozoic, and fault traces at the level of the Precambrian surface from a previously published 3D geologic model of the Anadarko Basin Province (Higley and others, 2014). In the original release of the 3D model, elevation surfaces were exported to a Zmap interchange file format, potentially limiting access to the data for users without access to specialized software. In this digital data release, elevation surfaces are provided in more readily accessible formats and modeled horizons are given more thorough stratigraphic descriptions than provided in the original model documentation. Within the AnadarkoBasin_Higley geodatabase, the GeologicMap feature dataset contains a line feature class (ContactsAndFaults) containing fault traces at the level of the Precambrian surface, a polyline representing the approximate Anadarko Basin boundary, and model area boundary digitized from the original publication; a polygon feature dataset (MapUnitPolys) with the approximate Anadarko Basin boundary and the model area boundary; and raster datasets for the 26 subsurface horizons and a single thickness grid representing the estimated eroded thickness of strata. Nonspatial tables define the data sources used (DataSources), define terms used in the dataset (Glossary), and provide a description of the modeled surfaces (DescriptionOfMapUnits) that provides the user with far greater stratigraphic detail than the original publication. Separate file folders contain the vector data in shapefile format, the raster data in ASCII and GeoTiff file formats, and the tables as comma-separated values file format. In addition, a tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and the accompanying nonspatial tables (EntityAndAttributes). Elevation surfaces exported from the 3D model in Zmap interchange file format and additional datasets are available through the original publication (Higley and others, 2014: https://pubs.usgs.gov/dds/dds-069/dds-069-ee/).

Access API Access 5m DEM Service Access NSW Elevation Service Access ELVIS PlatformNSW Elevation and Depth Theme Please Note WGS 84 service aligned to GDA94 This dataset has spatial reference [WGS …Show full description Access API Access 5m DEM Service Access NSW Elevation Service Access ELVIS PlatformNSW Elevation and Depth Theme Please Note WGS 84 service aligned to GDA94 This dataset has spatial reference [WGS 84 ≈ GDA94] which may result in misalignments when viewed in GDA2020 environments. A similar service with a ‘multiCRS’ suffix is available which can support GDA2020, GDA94 and WGS 84 ≈ GDA2020 environments. In due course, and allowing time for user feedback and testing, it is intended that the original service name will adopt the new multiCRS functionally.Elevation and Depth is the measurement of the Earth’s surface above or below a vertical datum to obtain the height of the land. Data is collected using a range of sensors including: laser, sonar, radar and optical. Technical methodologies are used to derive spot heights, raster surfaces, contours, triangulated irregular networks and digital elevation models. Datasets that form the Elevation and Depth theme include: Historical Contours (2m Urban, 10m and 20m) Current 2m Contours (State wide) Spot Heights Relative Heights Point cloud (LiDAR and Photogrammetrically derived) (available for download from Geoscience Australia ELVIS Platform) Digital Elevation Model (available for download from Geoscience Australia ELVIS Platform)Point Clouds - The point cloud data set consists of point clouds captured from LiDAR (Light Detection and Ranging) and derived from airborne imagery using photogrammetric techniques. Spatial Services Point Cloud data is available for on demand download from Geoscience Australia ELVIS Platform. Digital Elevation Models - Digital Elevation Models (DEM) are derived from Spatial Services’ (SS) point cloud data. The DEM is a bare earth representation of the earth’s surface where all the above ground feature has been removed. Spatial Services have a number of different Digital Elevation Models Digital Elevation Model derived from LiDARAre 1m or 2m resolution and is not hydrologically enforced (breaklines) or hydrologically conditioned (identification andanalysis of sinks). Digital Elevation Model derived Photogrammetry Data is 5m resolution. Areas of no data caused by steep slopes, shadow and vegetation have been interpolated or filled-in with another data source and will not be as accurate as the bare open ground areas. The data is not hydrologically enforced (breaklines) or hydrologically conditioned (identification and analysis of sinks).Spatial Services Digital Elevation Model data is available for on demand download from. Geoscience Australia ELVIS Platform as 2km x 2km tiles. You can also access the NSW 5 Metre Digital Elevation Model Service in the Spatial Collaboration Portal: Elevation and Depth provides an accurate representation of the Earth’s surface enabling evidence-based decision making, 3D modelling, planning and earth surface representation. Elevation and Depth underpins: · Safe hydrographic· Aeronautical and road navigation· Climate science, including climate change adaptation· Emergency management and natural hazard risk assessment· Environmental, including water management· Engineering projects and infrastructure development· Definition of maritime and administrative boundaries· Natural resource exploration Update frequencies vary for each dataset. Individual current status can be found under each Spatial data profile. The objective is to maintain elevation datasets to meet the FDSI requirements of key data users. Current programs include:· Aerial LiDAR capture program across NSW.· DEM and Point Cloud generation from photogrammetric techniques. Longer term programs include:· Update of contour data using updated DEM data generated from LiDAR and Photogrammetry.· Hydrological enforcement using improved surface models. MetadataType Esri Map ServiceUpdate Frequency As required Contact Details Contact us via the Spatial Services Customer Hub Relationship to Themes and Datasets Elevation and Depth Theme of the Foundation Spatial Data FrameworkAccuracy The dataset maintains a positional relationship to, and alignment with, the drainage and topographic digital datasets. these data sets were captured primarily by digitising from the best available aerial photography at scales and accuracies, ranging from 1:500 to 1:250 000 according to the National Mapping Council of Australia, Standards of Map Accuracy (1975). Therefore, the position of the feature instance will be within 0.5mm at map scale for 90% of the well-defined points. That is, 1:500 = 0.25m, 1:2000 = 1m, 1:4000 = 2m, 1:25000 = 12.5m, 1:50000 = 25m and 1:100000 = 50m. A program of positional upgrade (accuracy improvement) is currently underway.Spatial Reference System (dataset) Geocentric Datum of Australia 1994 (GDA94), Australian Height Datum (AHD) Spatial Reference System    (web service) EPSG 4326: WGS 84 Geographic 2D WGS 84 Equivalent ToGDA94 Spatial Extent Full State Standards and Specifications AS/NZS ISO 19115 - ANZLIC Metadata Profile Version 1.1AS/NZS ISO 19131:2008 Geographic Information - Data product specificationsOGC compliant Web Map Services (WMS) and Web Feature Services (WFS) Metadata for the relevant Spatial Services datasets complies with AS/NZS ISO 19115-2, ANZLIC Metadata Profile v1.1 and ISO 19139 Intergovernmental Committee on Surveying and Mapping (ICSM): Guidelines for Digital Elevation Data DCS Spatial Services Elevation Data Products Specification and Description (LiDAR) DCS Spatial Services Elevation Data Products Specification and Description (Airborne Photogrammetry)Distributors Service Delivery, DCS Spatial Services 346 Panorama Ave Bathurst NSW 2795Dataset Producers and Contributors Administrative Spatial Programs, DCS Spatial Services 346 Panorama Ave Bathurst NSW 2795

This digital dataset compiles a 3-layer geologic model of the conterminous United States by mapping the altitude of three surfaces: land surface, top of bedrock, and top of basement. These surfaces are mapped through the compilation and synthesis of published stratigraphic horizons from numerous topical studies. The mapped surfaces create a 3-layer geologic model with three geomaterials-based subdivisions: unconsolidated to weakly consolidated sediment; layered consolidated rock strata that constitute bedrock, and crystalline basement, consisting of either igneous, metamorphic, or highly deformed rocks. Compilation of subsurface data from published reports involved standard techniques within a geographic information system (GIS) including digitizing contour lines, gridding the contoured data, sampling the resultant grids at regular intervals, and attribution of the dataset. However, data compilation and synthesis is highly dependent on the definition of the informal terms “bedrock” and “basement”, terms which may describe different ages or types of rock in different places. The digital dataset consists of a single polygon feature class which contains an array of square polygonal cells that are 2.5 km m in x and y dimensions. These polygonal cells multiple attributes including x-y _location, altitude of the three mapped layers at each x-y _location, the published data source from which each surface altitude was compiled, and an attribute that allows for spatially varying definitions of the bedrock and basement units. The spatial data are linked through unique identifiers to non-spatial tables that describe the sources of geologic information and a glossary of terms used to describe bedrock and basement type.

This digital dataset contains the surface water data used for both the Salinas Valley Watershed Model (SVWM) and the Lower Salinas Valley Hydrologic Models (Salinas Valley Integrated Hydrologic Model (SVIHM) and Salinas Valley Operational Model (SVOM)). The surface water dataset includes two regions of the Salinas River Watershed; the upper region is primarily within San Luis Obispo County, California and lower region of the Salinas River Watershed is contained within Monterey County, California. Subcatchments within the Salinas River watershed were delineated using the U.S. Geological Survey (USGS) 10m digital elevation model (DEM), USGS National Hydrography Dataset Best Resolution (NHD) watershed boundaries, and the NHD stream data (U.S. Geological Survey, 2019). For each defined subcatchment, a pourpoint was defined that connects the watershed outflow to the tributary streams or ephemeral stream channels defined for the Salinas River in the lower and upper Salinas Valley Watershed. For the stream network of the lower Salinas River Watershed, NHD defined streams were used to initially define the network. The lower Salinas River Watershed stream network was refined to account for diversion canals and undefined ephemeral channels that drain into the Lower Salinas Valley in cooperation with Monterey County. For the lower Salinas Valley, the stream network and subcatchment data were defined simultaneously. For the upper Salinas Valley the pourpoints were defined based upon where previously defined subcatchments intersected with the stream network defined by the Paso Robles Basin Model (Fugro West, Inc and Cleath Associates, 2002; Fugro West, Inc, ETIC Engineering, Inc, and Cleath and Associates, 2005). The stream network spatial data were not provided from San Luis Obispo County as a vector shape, and the USGS did not develop the Paso Robles Basin Model (PRBM), therefore a shapefile of locations where the PRBM grid contained a stream reach was used as a proxy for linear features of the stream network in the upper Salinas River Watershed. This data set includes the following files: - Shapefiles for stream network, both lower and upper watersheds - Streamflow gage data and location - Ungaged tributary inflow points, both lower and upper watersheds

This data set includes the results of digital image correlation analysis applied to nine experiments (Table 1) on magma-tectonic interaction performed at the Helmholtz Laboratory for Tectonic Modelling (HelTec) of the GFZ German Research Centre for Geosciences in Potsdam in the framework of EPOS transnational access activities in 2017. The models use silicone oil (PDMS G30M, Rudolf et al., 2016) and Quartz sand (G12, Rosenau et al., 2018) to simulate pre-, syn- and post-tectonic intrusion of granitic magma into upper crustal shear zones of simple shear and transtensional (15° obliquity) kinematics. Three reference experiments (simple shear, transtension, intrusion) are also reported. Detailed descriptions of the experiments can be found in Michail et al. (submitted) to which this data set is supplement. The models have been monitored by means of digital image correlation (DIC) analysis including Particle Image Velocimetry (PIV; Adam et al., 2005) and Structure from Motion photogrammetry (SfM; Donnadieu et al., 2003; Westoby et al., 2012). DIC analysis yields quantitative model surface deformation information by means of 3D surface topography and displacements from which surface strain has been calculated. The data presented here are visualized as surface deformation maps and movies, as well as digital elevation and intrusion models. The results of a shape analysis of the model plutons is provided, too.

This digital GIS dataset and accompanying nonspatial files synthesize model outputs from a regional-scale volumetric 3-D geologic model that portrays the generalized subsurface geology of the Powder River Basin and Williston Basin regions from a wide variety of input data sources. The study area includes the Hartville Uplift, Laramie Range, Bighorn Mountains, Powder River Basin, and Williston Basin. The model data released here consist of the stratigraphic contact elevation of major Phanerozoic sedimentary units that broadly define the geometry of the subsurface, the elevation of Tertiary intrusive and Precambrian basement rocks, and point data that illustrate an estimation of the three-dimensional geometry of fault surfaces. The presence of folds and unconformities are implied by the 3D geometry of the stratigraphic units, but these are not included as discrete features in this data release. The 3D geologic model was constructed from a wide variety of publicly available surface and subsurface geologic data; none of these input data are part of this Data Release, but data sources are thoroughly documented such that a user could obtain these data from other sources if desired. The PowderRiverWilliston3D geodatabase contains 40 subsurface horizons in raster format that represent the tops of modeled subsurface units, and a feature dataset “GeologicModel”. The GeologicModel feature dataset contains a feature class of 30 estimated faults served in elevation grid format (FaultPoints), a feature class illustrating the spatial extent of 22 fault blocks (FaultBlockFootprints), and a feature class containing a polygon delineating the study areas (ModelBoundary). Nonspatial tables define the data sources used (DataSources), define terms used in the dataset (Glossary), and provide a description of the modeled surfaces (DescriptionOfModelUnits). Separate file folders contain the vector data in shapefile format, the raster data in ASCII format, and the tables as comma-separated values. In addition, a tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and the accompanying nonspatial tables (EntityAndAttributes). An included READ_ME file documents the process of manipulating and interpreting publicly available surface and subsurface geologic data to create the model. It additionally contains critical information about model units, and uncertainty regarding their ability to predict true ground conditions. Accompanying this data release is the “PowderRiverWillistonInputSummaryTable.csv”, which tabulates the global settings for each fault block, the stratigraphic horizons modeled in each fault block, the types and quantity of data inputs for each stratigraphic horizon, and then the settings associated with each data input.

This digital GIS dataset and accompanying nonspatial files synthesize the model outputs from a regional-scale volumetric 3-D geologic model that portrays the generalized subsurface geology of western South Dakota from a wide variety of input data sources.The study area includes all of western South Dakota from west of the Missouri River to the Black Hills uplift and Wyoming border. The model data released here consist of the stratigraphic contact elevation of major Phanerozoic sedimentary units that broadly define the geometry of the subsurface, the elevation of Tertiary intrusive and Precambrian basement rocks, and point data representing the three-dimensional geometry of fault surfaces. the presence of folds and unconformities are implied by the 3D geometry of the stratigraphic units, but these are not included as discrete features in this data release. The 3D geologic model was constructed from a wide variety of publicly available surface and subsurface geologic data; none of these input data are part of this Data Release, but data sources are thoroughly documented such that a user could obtain these data from other sources if desired. This model was created as part of the U.S. Geological Survey’s (USGS) National Geologic Synthesis (NGS) project—a part of the National Cooperative Geologic Mapping Program (NCGMP). The WSouthDakota3D geodatabase contains twenty-five (25) subsurface horizons in raster format that represent the tops of modeled subsurface units, and a feature dataset “GeologicModel”. The GeologicModel feature dataset contains a feature class of thirty-five (35) faults served in elevation grid format (FaultPoints). The feature class “ModelBoundary” describes the footprint of the geologic model, and was included to meet the NCGMP’s GeMS data schema. Nonspatial tables define the data sources used (DataSources), define terms used in the dataset (Glossary), and provide a description of the modeled surfaces (DescriptionOfModelUnits). Separate file folders contain the vector data in shapefile format, the raster data in ASCII format, and the nonspatial tables as comma-separated values. In addition, a tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and the accompanying nonspatial tables (EntityAndAttributes). An included READ_ME file documents the process of manipulating and interpreting publicly available surface and subsurface geologic data to create the model. It additionally contains critical information about model units, and uncertainty regarding their ability to predict true ground conditions. Accompanying this data release is the “WSouthDakotaInputSummaryTable.csv”, which tabulates the global settings for each fault block, the stratigraphic horizons modeled in each fault block, the types and quantity of data inputs for each stratigraphic horizon, and then the settings associated with each data input.

A 10m high resolution raster layer containing height information is generated for core urban areas of selected cities (capitals in EU28 + EFTA) as part of the Urban atlas. Height information is based on IRS-P5 stereo images and derived datasets like the digital surface model, the digital terrain model and the normalized DSM.This product is generated based on IRS-P5 stereo images acquired as close as possible to the defined reference year. Based on these stereo images a digital surface model is generated. Afterwards a digital terrain model is derived from the DSM with different filter algorithms and the assistance of Urban Atlas 2012 datasets. The calculation of the normalized DSM is done by a simple subtraction of the DTM from the DSM. The final product is then clipped based on UA 2012 building blocks and fully quality controlled.

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2016 and 2017 at Looe Key coral reef near Big Pine Key, Florida (FL), within a 19.74 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2019) derived from an elevation-change analysis between two elevation datasets acquired in 2016 and 2017 using the methods of Yates and others (2017). A seafloor stability threshold was determined for the 2016-2017 Looe Key elevation-change dataset based on the vertical uncertainty of the 2016 and 2017 digital elevation models (DEMs). Five stability categories (which include, Stable: 0.0 meters (m) to ±0.24 m or 0.0 m to ±0.49 m; Moderately stable: ±0.25 m to ±0.49 m; Moderately unstable: ±0.50 m to ±0.74 m; Mostly unstable: ±0.75 m to ±0.99 m; and Unstable: ±1.00 m to Max/Min elevation change) were created and used to define levels of stability and instability for each elevation-change value (4,934,364 data points at 2-m horizontal resolution) based on the amount of erosion and accretion during the 2016 to 2017 time period. Seafloor-stability point and triangulated irregular network (TIN) surface models were created at five different elevation-change data resolutions (1st order through 5th order) with each resolution becoming increasingly more detailed. The stability models were used to determine the level of seafloor stability at potential areas of interest for coral restoration and ten habitat types found at Looe Key. Stability surface (TIN) models were used for areas defined by specific XY geographic points, while stability point models were used for areas defined by bounding box coordinate locations. This data release includes ArcGIS map packages containing the binned and color-coded stability point and surface (TIN) models, potential coral restoration locations, and habitat files; maps of each stability model; and data tables containing stability and elevation-change data for the potential coral restoration locations and habitat types. Data were collected under Florida Keys National Marine Sanctuary permit FKNMS-2016-068. Coral restoration locations were provided by Mote Marine Laboratory under Special Activity License SAL-18-1724-SCRP.

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2016 and 2019 along the Florida Reef Tract (FRT) from Miami to Key West within a 939.4 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Fehr and others (2021) derived from an elevation-change analysis between two elevation datasets acquired in 2016/2017 and 2019 using the methods of Yates and others (2017). Most of the elevation data from the 2016/2017 time period were collected during 2016, so as an abbreviated naming convention, we refer to this time period as 2016. Due to file size limitations, the elevation-change data was divided into five blocks. A seafloor stability threshold was determined for the 2016-2019 FRT elevation-change datasets based on the vertical uncertainty of the 2016 and 2019 digital elevation models (DEMs). Five stability categories (which include, Stable: 0.0 meters (m) to ±0.24 m or 0.0 m to ±0.49 m; Moderately stable: ±0.25 m to ±0.49 m; Moderately unstable: ±0.50 m to ±0.74 m; Mostly unstable: ±0.75 m to ±0.99 m; and Unstable: ±1.00 m to Max/Min elevation change) were created and used to define levels of stability and instability for each elevation-change value (total of 235,153,117 data points at 2-m horizontal resolution) based on the amount of erosion and accretion during the 2016 to 2019 time period. Seafloor-stability point and triangulated irregular network (TIN) surface models were created for each block at five different elevation-change data resolutions (1st order through 5th order) with each resolution becoming increasingly more detailed. The stability models were used to determine the level of seafloor stability at potential areas of interest for coral restoration and 14 habitat types found along the FRT. Stability surface (TIN) models were used for areas defined by specific XY geographic points, while stability point models were used for areas defined by bounding box coordinate locations. This data release includes ArcGIS Pro map packages containing the binned and color-coded stability point and surface (TIN) models, potential coral restoration locations, and habitat files for each block; maps of each stability model; and data tables containing stability and elevation-change data for the potential coral restoration locations and habitat types. Data were collected under Florida Keys National Marine Sanctuary permit FKNMS-2016-068. Coral restoration locations were provided by Mote Marine Laboratory under Special Activity License SAL-18-1724-SCRP.

This digital dataset was created as part of a U.S. Geological Survey hydrologic resource assessment and development of an integrated numerical hydrologic model of the hydrologic system of the Upper Colorado River Basin, an extensive region covering approximately 412,000 square kilometers in five states: Wyoming, Colorado, Utah, Arizona, and New Mexico. As part of this larger study, the USGS developed this digital dataset of geologic data and a three-dimensional hydrogeologic framework model (3D HFM) that define the elevation, thickness, and extent of seven hydrogeologic units in the Upper Colorado River Basin. The hydrogeologic setting of the Colorado Plateau consists of thick Paleozoic, Mesozoic, and Cenozoic aquifers, predominantly sandstone and limestone, that are separated by regionally extensive confining units of fine-grained siliciclastic rocks, all overlain by generally thin Quaternary sediments. Based in part on the need to maintain consistency with previously published USGS hydrogeologic studies in the region (Craigg, 2001; Freethy and Cordy, 1991; Geldon, 2003; Glover and others, 1998), seven hydrogeologic units (HGUs) were modeled across the Upper Colorado River Basin: (1) TIPCG, Tertiary Intrusions and Precambrian Granite, a confining unit that includes crystalline igneous and metamorphic rocks of all ages; (2) PZAU, Paleozoic aquifer unit, including Mississippian and Pennsylvanian carbonate rocks and Permian sandstones and conglomerate; (3) CMCU, the Chinle-Moenkopi confining unit, including red Triassic fine-grained sandstone, siltstone and shale; (4) MZAU, Mesozoic aquifer unit, including thick, dominantly eolian Triassic and Jurassic sandstones of the Glen Canyon Group and overlying dominantly fluvial and alluvial sandstones and shales of the San Rafael Group; (5) MCU, Mancos confining unit, including thick sections of Cretaceous marine shale; (6) KTAU, Cretaceous-Tertiary aquifer unit, including marginal marine to continental siliciclastic sections with locally thick Cenozoic volcanic rocks; and (7) QAU, Quaternary alluvial unit, consisting predominantly of alluvial sediment along modern washes and drainages. Surface and subsurface data compiled include a digital elevation model, geologic contacts shown on geologic maps, reported formation tops from oil and gas wells, and structure contour and isopach maps. Input surface and subsurface data have been reduced to points that define the elevation of the top of each hydrogeologic units; these point data sets serve as digital input to the 3D framework model. Surfaces representing the elevation of the top of each hydrogeologic unit were created through standard interpolation methods of input data points using two-dimensional horizon gridding software. Data were interpolated using faults as two-dimensional boundaries that acted as a barrier to information flow during interpolation. Resultant HGU elevations were mapped to an x, y array of 1-km polygonal cells in geographic information systems (GIS) software. Each cell within the array was assigned attributes representing the top elevation thickness of each hydrogeologic unit. This polygonal cellular array is essentially a “flattened”, 2.5D (multiple z values stored at each x,y coordinate) representation of the digital 3D HFM, defining the elevation, thickness, and extent of each of the 7 HGUs at every cell centroid. The digital dataset includes a geospatial database that contains the following data elements: (1) a digital hydrogeologic map and map of fault locations for the model domain, (2) compiled digital input data to the 3D HFM for each hydrogeologic unit; (3) the 3D HFM, stored as interpolated elevation and thickness of the seven hydrogeologic as attributes of an XY array of polygonal cells; and (4) elevation surfaces of each HGU interpolated as triangular irregular networks (TINs) and extruded volumes (“multipatch”). The spatial data are accompanied by non-spatial tables that describe the sources of geologic information, a glossary of terms, a description of model units, and a Data Dictionary that duplicates the Entity and Attribute information contained in the metadata file. Spatial data from the geodatabase are also saved in shapefile format and nonspatial tables from the geodatabase are also provided in CSV format.