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.

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 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.

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.DEFRA Data Services Platform Metadata URLDefra Network WMS server provided by the Environment Agency

Download In State Plane Projection Here 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.

Zoom in on the map above and click your area of interest or use the Tile Index linked below to determine which package(s) you require for download. The DTM data is available in the form of 1-km by 1-km non-overlapping tiles grouped into packages for download.This dataset is a compilation of lidar data from multiple acquisition projects, as such specifications, parameters and sensors may vary by project. See the detailed User Guide linked below for additional information.

You can monitor the availability and status of lidar projects on the Ontario Lidar Coverage map on the Ontario Elevation Mapping Program hub page.

Now also available through a web service which exposes the data for visualization, geoprocessing and limited download. The service is best accessed through the ArcGIS REST API, either directly or by setting up an ArcGIS server connection using the REST endpoint URL. The service draws using the Web Mercator projection.

For more information on what functionality is available and how to work with the service, read the Ontario Web Raster Services User Guide. If you have questions about how to use the service, email Geospatial Ontario (GEO) at geospatial@ontario.ca.

Service Endpoints

https://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DTM_LidarDerived/ImageServer https://intra.ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DTM_LidarDerived/ImageServer (Government of Ontario Internal Users)

Additional Documentation

Ontario DTM (Lidar-Derived) - User Guide (DOCX)

OMAFRA Lidar 2016-2018 -Cochrane-Additional Contractor Metadata (PDF) OMAFRA Lidar 2016-2018 -Peterborough-AdditionalContractorMetadata (PDF) OMAFRA Lidar 2016-2018 -Lake Erie-AdditionalContractorMetadata (PDF) CLOCA Lidar 2018 - Additional Contractor Metadata (PDF) South Nation Lidar 2018-19 - Additional Contractor Metadata (PDF) OMAFRA Lidar 2022 - Lake Huron - Additional Contractor Metadata (PDF) OMAFRA Lidar 2022 - Lake Simcoe - Additional Contractor Metadata (PDF) Huron-Georgian Lidar 2022-23 - Additional Contractor Metadata (Word) Kawartha Lakes Lidar 2023 - Additional Contractor Metadata (Word) Sault Ste Marie Lidar 2023-24 - Additional Contractor Metadata (Word) Thunder Bay Lidar 2023-24 - Additional Contractor Metadata (Word) Timmins Lidar 2024 - Additional Contractor Metadata (Word)

Ontario DTM (Lidar-Derived) - Tile Index (SHP) Ontario Lidar Project Extents (SHP)

OMAFRA Lidar DTM 2016-2018 -Cochrane- Breaklines (SHP) OMAFRA Lidar DTM 2016-2018 -Peterborough-Breaklines (SHP) OMAFRA Lidar DTM 2016-2018 -Lake Erie-Breaklines (SHP) CLOCA Lidar DTM 2018-Breaklines (SHP) South Nation Lidar DTM 2018-19-Breaklines (SHP) Ottawa-Gatineau Lidar DTM 2019-20 - Breaklines (SHP) OMAFRA Lidar DTM 2022 - Lake Huron - Breaklines (SHP) OMAFRA Lidar DTM 2022 - Lake Simcoe - Breaklines (SHP) Eastern Ontario Lidar DTM 2021-22 - Breaklines (SHP) Muskoka Lidar DTM 2018 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP) Muskoka Lidar DTM 2021 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP) Muskoka Lidar DTM 2023 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP) DEDSFM Huron-Georgian Bay 2022-23 - Breaklines (SHP) DEDSFM Kawartha Lakes 2023 - Breaklines (SHP) DEDSFM Sault Ste Marie 2023-24- UTM16 - Breaklines (SHP) DEDSFM Sault Ste Marie 2023-24- UTM17 - Breaklines (SHP) DEDSFM Sudbury 2023-24 - Breaklines (SHP) DEDSFM Thunder Bay 2023-24 - Breaklines (SHP) DEDSFM Timmins 2024 - Breaklines (SHP)

Product PackagesDownload links for the Ontario DTM (Lidar-Derived) (Word) Projects: LEAP 2009 GTA 2014-18 OMAFRA 2016-18 CLOCA 2018 South Nation CA 2018-19 Muskoka 2018-23 York-Lake Simcoe 2019 Ottawa River 2019-20 Ottawa-Gatineau 2019-20 Lake Nipissing 2020 Hamilton-Niagara 2021 Huron Shores 2021 Eastern Ontario 2021-22 OMAFRA Lake Huron 2022 OMAFRA Lake Simcoe 2022 Belleville 2022 Digital Elevation Data to Support Flood Mapping 2022-26

Huron-Georgian Bay 2022-23 Kawartha Lakes 2023 Sault Ste Marie 2023-24 Sudbury 2023-24 Thunder Bay 2023-24 Timmins 2024

Greater Toronto Area Lidar 2023

Status On going: Data is continually being updated

Maintenance and Update Frequency As needed: Data is updated as deemed necessary

Contact Ontario Ministry of Natural Resources - Geospatial Ontario,geospatial@ontario.ca

Preston, R. and Mills, P., 2002. Generation of a Hydrologically Corrected Digital Elevation Model for the Republic of Ireland. Unpublished report submitted to EPA by Compass Informatics as part of the 2000-LS-2.2.2 Fourth Progress Report.Ordnance Survey Ireland (OSi) 1:50,000 data was used to create it. Individual DEMs were generated for hydrometric areas for the Republic of Ireland, including the coastal islands of Ireland at grid resolution of 20m. The project required significant pre-processing of source data to facilitate the generation of DEMs but the end result is a hydrologically corrected digital representation of terrain for the whole of the country, suitable for numerous environmental applications. Contours at 10m intervals were generated from the hDTM.Digital Terrain Models (DTM) are bare earth models (no trees or buildings) of the Earth’s surface.The map is a vector dataset. The contours are shown as lines. Each line has info on the contour interval and an ID.

The Current Height File Netherlands DTM (AHN) is the digital height map for the entire Netherlands of ground level without objects such as buildings or trees. The AHN raster files have a resolution of 0.5 meters. It contains detailed and precise height data determined with a minimum of 10 height measurements per square meter. The height is measured with laser altimetry: a technique in which a plane with a laser beam scans the Earth’s surface. Of the measured heights (points), 3D point clouds and grids are made. Ahn is a collaboration of the provinces, government and water boards. The height file AHN4 DTM ground level grid is the grid manufactured by classifying points as “ground level” and converting them to a grid based on a Squared IDW method. No further operations have been carried out. Points that are omitted are objects such as trees, buildings, bridges, water and other objects. The current AHN is version 4, this version has been obtained over the years 2020, 2021 and 2022. For more information on the AHN see https://ahn.nl/ahn-4.

Dataset Summary:This 3-foot resolution Digital Terrain Model (DTM) depicts topography, while removing all above-ground objects on the earth’s surface, like trees and buildings. The DTM represents the state of the landscape when countywide LiDAR data was collected in 2018 and 2020. Figure 1 shows the vintages of LiDAR contained in this raster. Quality level 1 LiDAR (QL1, red areas in figure 1) was collected in 2018. Quality level 2 LiDAR (QL2) was collected in summer, 2020.Figure 1. Recent LiDAR collections, by Quality Level (QL) in Santa Cruz County Methods:This LiDAR derivative provides information about the bare surface of the earth. The 3-foot resolution raster was produced from 2018 Quality Level 2 and 2020 Quality Level 1 LiDAR point cloud data (already ground classified) using Lastools. The processing steps were as followsCreate Tiles (lastile)Create DTM from ground classified points (las2dem)N Note that this DTM is neither hydro-flattened nor hydro-enforced.Uses and Limitations:The DTM provides a raster depiction of the ground returns for each 3x3 foot raster cell across Santa Cruz County. The layer is useful for hydrologic and terrain-focused analysis. The DTM will be most accurate in open terrain and less accurate in areas of very dense vegetation.Related Datasets:This dataset is part of a suite of LiDAR of derivatives for Santa Cruz County. See table 1 for a list of all the derivatives.Table 1. LiDAR derivatives for Santa Cruz CountyDatasetDescriptionLink to DatasheetLink to DataCanopy Height ModelThis depicts Santa Cruz County’s woody canopy as a Digital Elevation Model.https://vegmap.press/sc_chm_datasheethttps://vegmap.press/sc_chmNormalized Digital Surface ModelThis depicts the height above ground of objects on the earth’s surface, like trees and buildings.https://vegmap.press/sc_ndsm_datasheethttps://vegmap.press/sc_ndsmDigital Surface ModelThis depicts the elevation above sea level atop of objects on the earth’s surface.https://vegmap.press/sc_dsm_datasheethttps://vegmap.press/sc_dsm HillshadeThis depicts shaded relief based on the Digital Terrain Model. Hillshades are useful for visual reference when mapping features such as roads and drainages and for visualizing physical geography. https://vegmap.press/sc_hillshade_datasheethttps://vegmap.press/sc_hillshadeDigital Terrain ModelThis depicts topography, while removing all above-ground objects on the earth’s surface, like trees and buildings.https://vegmap.press/sc_dtm_datasheethttps://vegmap.press/sc_dtm

Spatial coverage index compiled by East View Geospatial of set "Romania 1:50,000 Scale Topographic Maps (DTM)". Source data from DTM (publisher). Type: Topographic. Scale: 1:50,000. Region: Europe.

This is a tiled collection of the 3D Elevation Program (3DEP) and is one meter resolution. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. USGS standard one-meter DEMs are produced exclusively from high resolution light detection and ranging (lidar) source data of one-meter or higher resolution. One-meter DEM surfaces are seamless within collection projects, but, not necessarily seamless across projects. The spatial reference used for tiles of the one-meter DEM within the conterminous United States (CONUS) is Universal Transverse Mercator (UTM) in units of meters, and in conformance with the North American Datum of 1983 ...

A Digital Terrain Model (DTM) is a digital file consisting of a grid of regularly spaced points of known height which, when used with other digital data such as maps or orthophotographs, can provide a 3D image of the land surface. 10m and 50m DTM’s are available. This is a large dataset and will take sometime to download. Please be patient. This service is published for OpenData. By download or use of this dataset you agree to abide by the LPS Open Government Data Licence.Please Note for Open Data NI Users: Esri Rest API is not Broken, it will not open on its own in a Web Browser but can be copied and used in Desktop and Webmaps

The High Resolution Digital Elevation Model Mosaic provides a unique and continuous representation of the high resolution elevation data available across the country. The High Resolution Digital Elevation Model (HRDEM) product used is derived from airborne LiDAR data (mainly in the south) and satellite images in the north. The mosaic is available for both the Digital Terrain Model (DTM) and the Digital Surface Model (DSM) from web mapping services. It is part of the CanElevation Series created to support the National Elevation Data Strategy implemented by NRCan. This strategy aims to increase Canada's coverage of high-resolution elevation data and increase the accessibility of the products. Unlike the HRDEM product in the same series, which is distributed by acquisition project without integration between projects, the mosaic is created to provide a single, continuous representation of strategy data. The most recent datasets for a given territory are used to generate the mosaic. This mosaic is disseminated through the Data Cube Platform, implemented by NRCan using geospatial big data management technologies. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The mosaic is available from Web Map Services (WMS), Web Coverage Services (WCS) and SpatioTemporal Asset Catalog (STAC) collections. Accessible data includes the Digital Terrain Model (DTM), the Digital Surface Model (DSM) and derived products such as shaded relief and slope. The mosaic is referenced to the Canadian Height Reference System 2013 (CGVD2013) which is the reference standard for orthometric heights across Canada. Source data for HRDEM datasets used to create the mosaic is acquired through multiple projects with different partners. Collaboration is a key factor to the success of the National Elevation Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.

This web map shows the Digital Terrain Model (DTM) of Hong Kong. It shows the topography of terrain (including non-ground information such as elevated roads and bridges) in 5-metre raster grid with an accuracy of ±5m. It is a subset of open data made available by the Survey and Mapping Office, Lands Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in ArcInfo ASCII Grid format and processed and converted to Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort. For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.

This data is no longer available on the Defra Data Services Platform.

Visit Scottish Remote Sensing Portal to access the latest LIDAR data for Scotland: https://remotesensingdata.gov.scot/data#/list

This metadata record is for Approval for Access product AfA458. Light Detection and Ranging (LIDAR) is an airborne mapping technique, which uses a laser to measure the distance between the aircraft and the ground. Up to 100,000 measurements per second are made of the ground, allowing highly detailed terrain models to be generated at spatial resolutions of between 25cm and 2 metres. The Environment Agency’s LIDAR data archive contains digital elevation data derived from surveys carried out by the Environment Agency's specialist remote sensing team. This dataset is derived from a combination of our full dataset which has been merged and re-sampled to give the best possible coverage. Data is available at 2m, 1m, 50cm, and 25cm resolution. The dataset can be supplied as a Digital Surface Model produced from the signal returned to the LIDAR (which includes heights of objects, such as vehicles, buildings and vegetation, as well as the terrain surface) or as a Digital Terrain Model produced by removing objects from the Digital Surface Model. The dataset can be presented as an ESRI Binary Grid which contains height values, or as a georeferenced JPEG which is an image showing what LIDAR looks like when loaded into specialist software. Attribution statement: Visit Scottish Remote Sensing Portal for information.

This layer shows the Digital Terrain Model (DTM) of Hong Kong. It shows the topography of terrain (including non-ground information such as elevated roads and bridges) in 5-metre raster grid with an accuracy of ±5m. It is a subset of open data made available by the Survey and Mapping Office, Lands Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in ArcInfo ASCII Grid format and processed and converted to Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort. For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.

The LIDAR DTM (Digital Terrain Model) Time Stamped Tiles product is an archive of raster elevation data produced by the Environment Agency. Site specific LIDAR surveys have been carried out across England since 1998, with certain areas, such as the coastal zone, being surveyed multiple times. Data is available at varying resolutions of 25cm, 50cm, 1m and 2m, depending on project requirements.

The DTM (Digital Terrain Model) is produced from the last return LIDAR signal. 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.

Available to download as GeoTiff rasters in 5km zipfiles, data is presented in metres, referenced to Ordnance Survey Newlyn and data aligned to the OS Grid. All LIDAR data has a vertical accuracy of +/-15cm RMSE. The transformation used on the data is specific to the time period of survey.

Please refer to the metadata index catalogue which show, for any location, what time stamped data is available, the specific dates of survey, resolution of product and what transformation and geoidal model used.

Part of the Nova Scotia Topographic Database (NSTDB), DTM is a vector data set of spot elevations collected from aerial photography. An elevation point is collected at ground level approximately every eighty meters in an irregular grid pattern. These spot elevations, or mass points, can be used to create profiles of the ground or Digital Elevation Models (DEM). Data download also available via GeoNova: https://nsgi.novascotia.ca/WSF_DDS/DDS.svc/DownloadFile?tkey=fhrTtdnDvfytwLz6&id=37 Map Service view also available via GeoNova: https://nsgiwa.novascotia.ca/arcgis/rest/services/BASE/BASE_NSTDB_10k_DTM_UT83/MapServer?f=jsapi

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:

• 30-m EDTM

https://s3.eu-central-1.wasabisys.com/openlandmap/dtm/dtm.bareearth_ensemble_p10_30m_s_2018_go_epsg4326_v20230221.tif

• Standard deviation

https://s3.eu-central-1.wasabisys.com/openlandmap/dtm/dtm.bareearth_ensemble_std_30m_s_2018_go_epsg4326_v20230221.tif

Derived using ALOS AW3D, GLO-30, MERITDEM, and national DTMs. We derived a lower 10% quantile from all maps. In order to create bare earth data, we used canopy height (canopy height > 2m) and standard deviation (sd > 6m) to mask building and forest in AW3D and GLO-30. Practical processing is written here in Python.

To access and visualize maps use: OpenLandMap.org

If you discover a bug, artifact or inconsistency, or if you have a question please use some of the following channels:

• Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/-/issues
• General questions and comments: https://disqus.com/home/forums/landgis/

All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL in Cloud Optimised GeoTiff (COG). File naming convention:

• dtm.bareearth = variable: digital terrain model (m), bare earth
• ensemble = determination method: ensemble of mutli-source dsm and dtm
• p10/std = aggregation/statistics method: 10th percentile / standard deviation
• 250m = spatial resolution / block support: 250 m,
• s = vertical reference: at surface,
• go = bounding box: global land without Antarctica
• epsg.4326 = ESPG code: epsg.4326
• v20230221 = version code: creation date 20230221

The present dataset is part of the Alaiz Experiment-2017 (ALEX17). The information is divided into two groups based on their source. 1)Two raster-tpye geotif files containing the Digital Elevation and Digital Surface Models (DEM and DSM) data of the ALEX17 domain. The models were built by TRACASA ( https://tracasa.es/all-about-us/) which is a company part of the Navarra Government. The original dataset is cropped to fit the ALEX17 experimental domain with the following spatial coverage: 607700, 4720300 628010, 4738800 The datasets are generated through lidar airborne scans taken during years 2011 and 2012 and updated by photogrammetry with orthophotos of year 2014. The original lidar scans (2011-2012) have a density of 1pnt/m^2 . The raw data are then processed and converted to orthometric heights (from the original ellipsoidal heights ) and later projected into a 2x2m grid with spatial reference EPSG:25830. The conversion from ellipsoidal to orthometric height is carried out with the EGM2008_REDNAP model, generated by the Spanish Geographic National Institute available in: ftp://ftp.geodesia.ign.es/geoide/ 2)The second dataset is also a raster-type file which contains the approximate annual mean of aerodynamic roughness length in meters. The maps was created with two data sources: Visual estimation of the roughness length values & zones. The Corine Land Cover (CLC) 2006 data. 2.1) The visual estimations of roughness values w carried out with the use of both, orthophotos gathered from the National Geographic Institute of Spain (IGN) as well as site visits. These values were assigned to the Alaiz mountain region while the 2.2) CLC-derived roughness was set to the rest of the domain area. The orthophotos are obtained from the National Plan for Aerial Orthophotogrpy (PNOA) program (available at http://www.ign.es/ign/layoutIn/faimgsataerea.do ). These photos have a pixel size of 50cm and were taken in summer 2014. On the other hand, the Corine Land Cover (CLC) 2006 raster dataset have a 100 m grid size. These data are available at http://www.eea.europa.eu/data-and-maps/data/corine- land-cover-2006-raster-3 (g100_06.zip file). The roughness values were derived from the Land Cover data mostly based on the relation between CLC and the aerodynamic roughness length applied by the Finnish wind atlas (http://www.tuuliatlas.fi/modelling/mallinnus_3.html ). The final composed roughness raster map was built by interpolation (nearest-neighbor) of the two data sources onto a 10x10 meters grid . The map is also projected with the same spatial reference as the DEM/DSM data described above.