The 2017 Digital Terrain Model (DTM) is a 2 foot pixel resolution raster in Erdas IMG format. This was created using the ground (class = 2) lidar points and incorporating the breaklines.

The DTMs were developed using LiDAR data. LiDAR is an acronym for LIght Detection And Ranging. Light detection and ranging is the science of using a laser to measure distances to specific points. A specially equipped airplane with positioning tools and LiDAR technology was used to measure the distance to the surface of the earth to determine ground elevation. The classified points were developed using data collected in April to May 2017. The LiDAR points, specialized software, and technology provide the ability to create a high precision three-dimensional digital elevation and/or terrain models (DEM/DTM). The use of LiDAR significantly reduces the cost for developing this information.

The DTMs are intended to correspond to the orthometric heights of the bare surface of the county (no buildings or vegetation cover). DTM data is used by county agencies to study drainage issues such as flooding and erosion; contour generation; slope and aspect; and hill shade images. This dataset was compiled to meet the American Society for Photogrammetry and Remote Sensing (ASPRS) Accuracy Standards for Large-Scale Maps, CLASS 1 map accuracy.

The U.S. Army Corps of Engineers Engineering and Design Manual for Photogrammetric Production recommends that data intended for this usage scale be used for any of the following purposes: route location, preliminary alignment and design, preliminary project planning, hydraulic sections, rough earthwork estimates, or high-gradient terrain / low unit cost earthwork excavation estimates. The manual does not recommend that these data be used for final design, excavation and grading plans, earthwork computations for bid estimates or contract measurement and payment.

This dataset does not take the place of an on-site survey for design, construction or regulatory purposes.

Digital Terrain Model for Continental Europe based on the three publicly available Digital Surface Models and predicted using an Ensemble Machine Learning (EML). EML was trainined using GEDI level 2B points (Level 2A; "elev_lowestmode") and ICESat-2 (ATL08; "h_te_mean"): about 9 million points were overlaid vs MERITDEM, AW3D30, GLO-30, EU DEM, GLAD canopy height, tree cover and surface water cover maps, then an ensemble prediction model (mlr package in R) was fitted using random forest, Cubist and GLM, and used to predict most probable terrain height (bare earth). Input layers used to train the EML include:

• "lcv_bare.earth_glcf.landsat": UMD GLAD bare earth estimate for year 2010 based on Landsat time series,
• "dtm_elev.dsm_alos.aw3d": Digital Surface Model based on ALOS AW3D,
• "dtm_canopy.height_glad.umd": UMD GLAD canopy height for 2019 based on GEDI data,
• "dtm_elev.dsm_eudem.eea": Copernicus EU DEM based on the SRTM and ASTER DEMs,
• "hyd_surface.water_jrc.gswe": JRC Global Surface Water Explorer surface water probability based on the Landsat time-series,
• "lcv_landcover.12_pflugmacher2019": land cover map of Europe at 30 based on Pflugmacher et al. (2019),
• "lcv_tree.cover_umd.landsat_2000": forest tree cover for year 2000 based on the Global Forest Change data,
• "lcv_tree.cover_umd.landsat_2010": forest tree cover for year 2010 based on the Global Forest Change data,

Detailed processing steps can be found here. Read more about the processing steps here.

Training data set can be obtained in the file "gedi_elev.lowestmode_2019_eumap.RDS". The initial linear model fitted using the four independent Digital Surface / Digital Terrain models shows:

Residuals:
 Min    1Q  Median    3Q   Max 
-124.627  -1.097  0.973  2.544  59.324 
 
Coefficients:
 Estimate Std. Error t value Pr(>|t|)  
(Intercept)     -1.6220640 0.0032415 -500.4  <2e-16 ***
 eu_dem25m_     -0.1092988 0.0005531 -197.6  <2e-16 ***
 eu_AW3Dv2012_30m_  0.0933774 0.0005957  156.7  <2e-16 ***
 eu_GLO30_30m_    0.2637153 0.0006062  435.1  <2e-16 ***
 eu_MERITv1.0.1_30m_ 0.7496494 0.0005009 1496.6  <2e-16 ***
 ---
 Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 7.059 on 9588230 degrees of freedom
(2046196 observations deleted due to missingness)
Multiple R-squared: 0.9996,  Adjusted R-squared: 0.9996 
F-statistic: 5.343e+09 on 4 and 9588230 DF, p-value: < 2.2e-16

Which show that MERIT DEM (Yamazaki et al., 2019) is the most correlated DEM with GEDI and ICESat-2, most likely because it has been systematically post-processed and majority of canopy problems have been removed. Summary results of the model training (mlr::makeStackedLearner) using all covariates (including canopy height, tree cover, bare earth cover) shows:

Variable: elev_lowestmode.f 
R-square: 1 
Fitted values sd: 333 
RMSE: 6.54 

Ensemble model:
Call:
stats::lm(formula = f, data = d)

Residuals:
   Min    1Q  Median    3Q   Max 
-118.788  -0.871  0.569  1.956 165.119 

Coefficients:
       Estimate Std. Error t value Pr(>|t|)  
(Intercept) -0.198402  0.003045 -65.15  <2e-16 ***
regr.ranger 0.452543  0.001117 405.04  <2e-16 ***
regr.cubist 0.527011  0.001516 347.61  <2e-16 ***
regr.glm   0.020033  0.001217  16.47  <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 6.544 on 9588231 degrees of freedom
Multiple R-squared: 0.9996,  Adjusted R-squared: 0.9996 
F-statistic: 8.29e+09 on 3 and 9588231 DF, p-value: < 2.2e-16

Which indicates that the elevation errors are in average (2/3rd of pixels) between +1-2 m. The variable importance based on Random Forest package ranger shows:

Variable importance:
        variable  importance
4  eu_MERITv1.0.1_30m_ 430641370770
1   eu_AW3Dv2012_30m_ 291483345389
2     eu_GLO30_30m_ 201517488587
3      eu_dem25m_ 132742500162
9 eu_canopy_height_30m_  5148617173
7       bare2010_  2087304901
8    treecover2000_  1761597272
6    treecover2010_  141670217

The output predicted terrain model includes the following two layers:

• "dtm_elev.lowestmode_gedi.eml_mf": mean estimate of the terrain elevation in dm (decimeters) filtered using Gaussian filter and 2x pixel window in SAGA GIS,
• "dtm_elev.lowestmode_gedi.eml_md": standard deviation of the independently fitted stacked predictors quantifying the prediction uncertainty in dm (decimeters),

The predicted elevations are based on the GEDI data hence the reference water surface (WGS84 ellipsoid) is about 43 m higher than the sea water surface for a specific EU country. Before modeling, we have corrected the reference elevations to the Earth Gravitational Model 2008 (EGM2008) by using the 5-arcdegree resolution correction surface (Pavlis et al, 2012).

All GeoTIFFs were prepared using Integer format (elevations rounded to 1 m) and have been converted to Cloud Optimized GeoTIFFs using GDAL.

Disclaimer: The output DTM still shows forest canopy (overestimation of the terrain elevation) and has not been hydrologically corrected for spurious sinks and similar. This data set is continuously updated. To report a bug or suggest an improvement, please visit here. To access DTM derivatives at 30-m, 100-m and 250-m please visit here. To register for updates please subscribe to: https://twitter.com/HarmonizerGeo.

The DTM is a homogeneous and regular point grid indicating the height of the ground level in order to model its surface. The DTM 1m is achieved by interpolating in Lambert 2008 source data in Lambert 72 and at a 1m-resolution from the Flemish and Brussels regions, and by adding Lambert 2008 data at 1m-resolution from the Walloon Region. The DTM 5m has an additional source, namely drawn structure lines and points adapted during systematic and continuous update by photogrammetric surveys. The DTM 20m is obtained by resampling of the DTM 1m.

The LIDAR Composite DTM (Digital Terrain Model) is a raster elevation model covering ~99% of England at 1m spatial resolution. The DTM (Digital Terrain Model) is produced from the last or only laser pulse returned to the sensor. We remove surface objects from the Digital Surface Model (DSM), using bespoke algorithms and manual editing of the data, to produce a terrain model of just the surface.

Produced by the Environment Agency in 2022, the DTM is derived from a combination of our Time Stamped archive and National LIDAR Programme surveys, which have been merged and re-sampled to give the best possible coverage. Where repeat surveys have been undertaken the newest, best resolution data is used. Where data was resampled a bilinear interpolation was used before being merged.

The 2022 LIDAR Composite contains surveys undertaken between 6th June 2000 and 2nd April 2022. Please refer to the metadata index catalgoues which show for any location which survey was used in the production of the LIDAR composite.

The data is available to download as GeoTiff rasters in 5km tiles aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-15cm RMSE.

A pilot bathymetric LiDAR survey was commissioned in 2021 which mapped the nearshore areas of Dundrum Bay and areas of Carlingford Lough./p>For the pilot bathymetric survey a Rapid Airborne Multi-bean Mapping System (RAMMS) operated at approximately 25000 range observations per second, while achieving 3-Secchi disk depth penetration. Where possible data was collected to depths of 10m, however, RAMMS is capable of capturing high resolution data to depths of three times the visual water clarity.This is the Digital Terrain Model created from the LiDAR dataset.

Coastal elevation data are essential for a wide variety of applications, such as coastal management, flood modelling, and adaptation planning. Low-lying coastal areas (found below 10 m +Mean Sea Level (MSL)) are at risk of future extreme water levels due to Sea Level Rise (SLR), subsidence and changing extreme weather patterns. However, current freely available elevation data sets are not sufficiently accurate to model these risks. We present DeltaDTM, a global coastal Digital Terrain Model (DTM) available in the public domain, with a horizontal spatial resolution of 30 m and a vertical mean absolute error (MAE) of 0.45 m overall. DeltaDTM corrects the CopernicusDEM with space borne lidar from the ICESat-2 and GEDI missions. Specifically, we correct the elevation bias in CopernicusDEM, apply filters to remove non-terrain cells, and fill the gaps using interpolation. Notably, our classification approach produces more accurate results than regression methods (including machine learning) recently used by others to correct DEMs, that achieve an overall MAE of 0.72 m at best. We conclude that DeltaDTM will be a valuable resource for coastal flood impact modelling and other applications.

A digital terrain model (DTM) is a digital representation of elevations throughout the Province. DTM files contain elevation mass points, check points, spot heights and random densified points. The spacing between the elevation points is approximately 70 metres and the absolute vertical accuracy of a single elevation point is approximately 2.5 metres. The elevations are expressed as metres above mean sea level.

The LIDAR Composite DTM (Digital Terrain Model) is a raster elevation model covering ~99% of England at 2m spatial resolution. The DTM (Digital Terrain Model) is produced from the last or only laser pulse returned to the sensor. We remove surface objects from the Digital Surface Model (DSM), using bespoke algorithms and manual editing of the data, to produce a terrain model of just the surface.

Produced by the Environment Agency in 2022, the DTM is derived from a combination of our Time Stamped archive and National LIDAR Programme surveys, which have been merged and re-sampled to give the best possible coverage. Where repeat surveys have been undertaken the newest, best resolution data is used. Where data was resampled a bilinear interpolation was used before being merged.

The 2022 LIDAR Composite contains surveys undertaken between 6th June 2000 and 2nd April 2022. Please refer to the metadata index catalgoues which show for any location which survey was used in the production of the LIDAR composite.

The data is available to download as GeoTiff rasters in 5km tiles aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-15cm RMSE.

This is a high resolution spatial dataset of Digital Terrain Model (DTM) data in South West England. The DTM along with a Digital Surface Model (DSM) cover an area of 9424 km2 that includes all the land west of Exmouth (i.e. west of circa 3 degrees 21 minutes West). The DTM represents the topographic model (height) of the bare earth. The dataset is a part of outcomes from the Centre for Ecology & Hydrology South West (SW) Project. There is also a Digital Surface Model (DSM) dataset covering the same areas available from the SW project. Full details about this dataset can be found at https://doi.org/10.5285/e2a742df-3772-481a-97d6-0de5133f4812

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.

Fugro were commissioned to undertake a post-storm LiDAR survey of the soft sedimentary areas along the north coast of Northern Ireland in March 2022 This survey was to cover the following areas: Curran Strand, Portrush East Strand, Portstewart Strand and Downhill Beach to Magilligan.This project was commissioned following the successive storm events during February and March 2022 (Storm Dudley, Storm Eunice and Storm Franklin) which did considerable damage to the sandy beaches along the North Coast. The objective of this survey was to ascertain change which has occurred along these soft sediment coastlines at the north coast since the baseline survey, which was acquired in 2021.Data was provided in the same format as the topographic LiDAR data collected in the Northern Ireland 3-Dimensional Coastal Survey to allow changes between these two datasets to be ascertained.This is the Digital Terrain Model created from the post-storm LiDAR data.

The digital terrain model (DTM) is a simplified representation of ground altimetry. The available data is in the form of an irregular triangular mesh (TIN). This is polygon numerical geographic data constructed by triangulating a set of points. The vertices are connected to a series of segments to form a mesh of triangles of different dimensions. This representation can be used as a basis for the 3D buildings of the digital base model. It should be noted that the data made available by the City is proposed for planning purposes and not for construction purposes given the associated decimeter details. The [3D buildings 2016 (LOD2 model with textures)]] (https://donnees.montreal.ca/ville-de-montreal/batiment-3d-2016-maquette-citygml-lod2-avec-textures2), the 2013 3D buildings (2013 3D buildings (CityGML LOD2 model with textures), or the 3D buildings 2009 (CityGML LOD2 model with textures), or the 3D buildings 2009 (CityGML LOD2 model with textures), or the 3D buildings 2009 (CityGML LOD2 model with textures) complement the digital terrain model in the urban territorial representation of Montreal. The elevation data from aerial LiDAR are also available on the portal.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Orthophotos, digital terrain models etc. provided by SDFE. See more information in the metadata file.This item is a part of the collection "Dataset for Bellinge: An urban drainage case study", https://doi.org/10.11583/DTU.c.5029124 Changes in version 2 - 31-08-2021- Updated documentation file- New names to subfolders

In 2021, a complete airborne LiDAR survey of the Northern Ireland coastline was commissioned as part of the NI 3D Coastal Survey, providing precise and accurate data of the current coastal morphology.The survey included the intertidal area and extended approximately 200 meters landward of the high-water mark.This is the Digital Terrain Model derived from the LiDAR data collected.

In the scope of the International Civil Aviation Organization (ICAO) requiring countries and airports to provide electronic Terrain and Obstacle Data (eTOD), the Administration de la navigation aérienne has been tasked by the Government to take the steps necessary to comply with this requirement. This Digital Terrain Model (DTM) is the result of a first LIDAR survey flight that has been done in October 2017 and corresponds to the standards required by ICAO. For this reason this DTM also uses the international reference systems WGS84 and EGM2008. The data itself is split up in 4 different areas, which are specified as follows: Area 1: The entire territory of Luxembourg; Area 2: Terminal Control Area (this area is larger than the territory of Luxembourg); Area 3: Aerodrome movement area; Area 4: Category II or III operations (Runway 24). The different areas come with different numerical requirements, such as data accuracy and resolution. Follow the links in the description or consult metadata for further Information.

dtm: Digital Terrain Model elevation derived using AW3D30, MERIT DEM, GLO-30 and EU-DEM

This dataset consists of the Digital Terrain Model 10m resolution data (DTM10) from the NEXTMap British Digital Terrain Model project produced by Intermap. These data have a spatial resolution of 5m and cover the British Isles.

The Digital Terrain Model was developed based on all available bathymetric data, already processed and validated. The SRTM30_PLUS (Shuttle Radar Topography Mission) data were used just to complement the bathymetric grid in distal regions of the Brazilian Continental Margin.

In order to prepare the bathymetric grid from a database composed by all qualified bathymetric information, it was adopted the Randgrid.GX/Geosoft - Oasis Montaj®, version 9.5.2, routine. The used mathematical model creates a surface of minimum curvature, using a similar method to that proposed by Swain (1976) and Briggs (1974), with the interpolation, in each knot of the grid, of X and Y values in metric coordinates and Z values (variable). The calculated surface adjusts itself to the irregularly sampled original values. The grid cell-size was 1,000 m, defined according the spatial distribution of the available data.

The Brazilian DTM Oasis grid file was converted to surfer files, Versions V6 and V7. The ASCII file and a Geotif image were also provided. The reference system and geodetic datum adopted for the bathymetric data was the WGS84. The projection adopted was the World Mercator (false N=0, false E=0, latitude of the natural origin=0 longitude of the natural origin=0, and the scaling factor of the natural origin=1).

Based on data from R/V Polarstern multibeam sonar surveys between 1984 and 1997 a high resolution bathymetry has been generated for the central Fram Strait. The area ensonified covers approx. 36,500 sqkm between 78°N-80°N and 0°E-7.5°E. Basic outcome of the investigation is a Digital Terrain Model (DTM) with 100 m grid spacing which was utilized for contouring and generation of a new series of bathymetric charts (AWI BCFS).

The digital terrain model of Greenland is constructed on the basis of GEUS's topographic datasets from the official geological maps of Greenland in scale ratio 1:100.000 and 1:500.000. The DEM is created using an interpolation method called Topo to Raster function in ArcGIS Desktop which is primarily supported by contour lines, coastlines and elevation points. The creation of the DEM was divided into in sub-areas based on the map sheet frames from the geological map of Greenland in 1:500.000 scale and assembled as a raster mosaic. The DEM was created with the spatial coordinate reference system WGS 1984 / UTM Zone 24N Complex with a resolution of a 100x100 meter grid. Based on the final DEM, a hillshade efect of the terrain has been constructed.