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.

This portion of the data release presents a digital surface model (DSM) and digital elevation model (DEM) of the exposed Los Padres Reservoir delta where the Carmel River enters the reservoir. The DSM and DEM have a resolution of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unoccupied aerial system (UAS) on 2017-11-01. The DSM represents the elevation of the highest object within the bounds of a cell, including vegetation, woody debris and other objects. The DEM represent the elevation of the ground surface where it was visible to the acquisiton system. Due to the nature of SfM processing, the DEM may not represent a true bare-earth surface in areas of thick vegetation cover; in these areas some DEM elevations may instead represent thick vegetation canopy. The raw imagery used to create these elevation models was acquired with a UAS fitted with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed autonomous flight lines spaced to provide approximately 70 percent overlap between images from adjacent lines. The camera was triggered at 1 Hz using a built-in intervalometer. The UAS was flown at an approximate altitude of 100 meters above ground level (AGL), resulting in a nominal ground-sample-distance (GSD) of 2.6 centimeters per pixel. The raw imagery was geotagged using positions from the UAS onboard single-frequency autonomous GPS. Twenty temporary ground control points (GCPs) consisting of small square tarps with black-and-white cross patterns were distributed throughout the area to establish survey control. The GCP positions were measured using real-time kinematic (RTK) GPS, using corrections from a GPS base station located on a benchmark designated SFML, located approximately 1 kilometer from the study area. The DSM and DEM have been formatted as cloud optimized GeoTIFFs with internal overviews and masks to facilitate cloud-based queries and display.

These datasets consist of four, 1-meter spatial resolution digital surface models (DSMs) that were generated to orthorectify airborne multispectral imagery acquired in 2002, 2009, 2013, and 2021 for the Colorado River in Grand Canyon in Arizona, USA. These datasets also consist of a 1-meter spatial resolution digital elevation model (DEM) that was generated from the 2021 DSM. The DSMs and DEM were also produced to support development of additional GIS products. Elevation values are expressed as ellipsoid heights. These datasets also include accuracy assessments that were performed to show the limitations of estimating elevation from the DSMs and DEM pixels locations on the landscape. Data were acquired during periods of low steady Colorado River flow of approximately 8,000 cubic feet per second released from Glen Canyon Dam.

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.

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 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.

This portion of the data release presents digital surface models (DSM) and hillshade images of the intertidal zones at Puget Creek and Dickman Mill Park, Tacoma, WA. The DSMs have a resolution of 2.5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-03. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been removed from the data. In addition, data artifacts resulting from noise in the original imagery have not been removed. The raw imagery used to create this DSM was acquired using a UAS fitted with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed autonomous flight lines at an approximate altitude of 50 meters above ground level (AGL). The flight lines were oriented roughly shore-parallel and were spaced to provide approximately 70 percent overlap between images from adjacent lines. The camera was triggered at 1 Hz using a built-in intervalometer. The imagery was geotagged using positions from the UAS onboard single-frequency autonomous GPS. Twelve temporary ground control points (GCPs) were distributed throughout each survey area to establish survey control. The GCPs consisted of a combination of small square tarps with black-and-white cross patterns and "X" marks placed on the ground using temporary chalk. The GCP positions were measured using post-processed kinematic (PPK) GPS, using corrections from a GPS base station located approximately 5 kilometers from the study area. The DSMs and hillshade images have been formatted as cloud optimized GeoTIFFs with internal overviews and masks to facilitate cloud-based queries and display. For file naming purposes the spatial resolution has been rounded to the nearest centimeter in the file names (for instance, the 2.5-cm resolution Puget Creek DSM is named PugetCreek_2019-06-03_DSM_3cm.tif).

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.

This is a high resolution spatial dataset of Digital Surface Model (DSM) data in South West England. It is a part of outcomes from the CEH South West (SW) Project. There is also a Digital Terrain Model (DTM) dataset covering the same areas available from the SW project. Both DTM and 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 DSM includes the height of features on the bare earth such as buildings or vegetation (if present). An overview of the TELLUS project is available on the web at http://www.tellusgb.ac.uk/.

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 Surface Model (DSM) is the result of a first LIDAR survey flight that has been done in October 2017 and is of a higher resolution than required by ICAO, thus for general purpose. For this reason this DSM also uses the national reference systems LUREF and NGL. 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.

Overview:
The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters.

The Copernicus DEM for Europe at 3 arcsec (0:00:03 = 0.00083333333 ~ 90 meter) in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/).

Processing steps:
The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in VRT format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized:

gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt

In order to reduce the spatial resolution to 3 arc seconds, weighted resampling was performed in GRASS GIS (using r.resamp.stats -w and the pixel values were scaled with 1000 (storing the pixels as integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using r.relief, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.

Projection + EPSG code:
Latitude-Longitude/WGS84 (EPSG: 4326)

Spatial extent:
north: 82:00:30N
south: 18N
west: 32:00:30W
east: 70E

Spatial resolution:
3 arc seconds (approx. 90 m)

Pixel values:
meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.)

Software used:
GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief)

Original dataset license:
https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf

Processed by:
mundialis GmbH & Co. KG, Germany (https://www.mundialis.de/)

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.

ATTENTION! The files in this dataset are designed for streaming, not downloading. For the best experience, please follow the instructions available in the resources. In replacement of the former Canadian Digital Elevation Model (CDEM) that is no longer supported, the Medium Resolution Digital Elevation Model (MRDEM) product is a multi-source product that integrates elevation data from the Copernicus DEM** acquired during the TanDEM-X Mission (AIRBUS, 2022), and the High Resolution Digital Elevation Model data derived from airborne lidar. This product provides a complete, 30 meters resolution, nationwide coverage for Canada. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived products. The spatial coverage extends into the USA, where needed, to provide coverage for cross-border watersheds in support of hydrological studies and applications. The MRDEM DSM dataset is based on the GLO-30 version of the Copernicus DEM** (hereafter named GLO-30). The process to generate the MRDEM DTM dataset is more complex and involves different sources. Where available, the HRDEM Mosaic derived from lidar was used since it already provides reliable terrain elevation values. The HRDEM Mosaic data used was resampled from 1 meter to 30 meters. Elsewhere, the processing workflow combines a forest removal model and a settlement removal model that is applied to the GLO-30 values in order to estimate the terrain elevation values. Both datasets are projected to Canada Atlas Lambert NAD83 (CSRS) (EPSG:3979). The MRDEM is referenced to the CGVD2013 which is the reference standard for orthometric heights across Canada. The product Medium Resolution Digital Elevation Model (MRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan. ** This product was in part produced using Copernicus WorldDEM-30 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014- 2018 provided under COPERNICUS by the European Union and ESA; all rights reserved. The organisations in charge of the Copernicus program by law or by delegation do not incur any liability for any use of the Copernicus WorldDEM-30.

Landgate Digital Elevation Models (DEMs) are of various postings around mainland Western Australia - excluding Cocos/Keeling Islands and Christmas Island. A DEM is a generic term for both a Digital Surface Model (DSM) or a Digital Terrain Model (DTM). In the main, Landgate DEMs are edited DSMs that remove the majority of buildings and trees to create pseudo-DTMs. Additional information, including a coverage map, is available on the Landgate website. © Western Australian Land Information Authority (Landgate). Use of Landgate data is subject to Personal Use License terms and conditions unless otherwise authorised under approved License terms and conditions.

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 (NAD83). All bare earth elevation values are in meters and are referenced to the North American Vertical Datum of 1988 (NAVD88). Each tile is distributed in the UTM Zone in which it lies. If a tile crosses two UTM zones, it is delivered in both zones. The one-meter DEM is the highest resolution standard DEM offered in the 3DEP product suite. Other 3DEP products are nationally seamless DEMs in resolutions of 1/3, 1, and 2 arc seconds. These seamless DEMs were referred to as the National Elevation Dataset (NED) from about 2000 through 2015 at which time they became the seamless DEM layers under the 3DEP program and the NED name and system were retired. Other 3DEP products include five-meter DEMs in Alaska as well as various source datasets including the lidar point cloud and interferometric synthetic aperture radar (Ifsar) digital surface models and intensity images. All 3DEP products are public domain.

A terrain surface dataset that represents the height value of all natural and built features of the surface of the city. Each pixel within the image contains an elevation value in accordance with …Show full descriptionA terrain surface dataset that represents the height value of all natural and built features of the surface of the city. Each pixel within the image contains an elevation value in accordance with the Australian Height Datum (AHD). The data has been captured in May 2018 as GeoTiff files, and covers the entire municipality. A KML tile index file can be found in the attachments to indicate the location of each tile, along with a sample image. Capture Information: Capture Pixel Resolution: 0.1 metres Limitations: Whilst every effort is made to provide the data as accurate as possible, the content may not be free from errors, omissions or defects.Preview: Download:A zip file containing all relevant files representing the Digital Surface ModelDownload Digital Surface Model data (12.0GB)

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.

A bare-earth, hydro-flattened, digital-elevation surface model derived from 2010 Light Detection and Ranging (LiDAR) data. Surface models are raster representations derived by interpolating the LiDAR point data to produce a seamless gridded elevation data set. A Digital Elevation Model (DEM) is a surface model generated from the LiDAR returns that correspond to the ground with all buildings, trees and other above ground features removed. The cell values represent the elevation of the ground relative to sea level. The DEM was generated by interpolating the LiDAR ground points to create a 1 foot resolution seamless surface. Cell values correspond to the ground elevation value (feet) above sea level. A proprietary approach to surface model generation was developed that reduced spurious elevation values in areas where there were no LiDAR returns, primarily beneath buildings and over water. This was combined with a detailed manual QA/QC process, with emphasis on accurate representation of docks and bare-earth within 2000ft of the water bodies surrounding each of the five boroughs.

A terrain surface dataset that represents the height value of all natural and built features of the surface of the city. Each pixel within the image contains an elevation value in accordance with the Australian Height Datum (AHD).

The data has been captured in May 2018 as GeoTiff files, and covers the entire municipality.

A KML tile index file can be found in the attachments to indicate the location of each tile, along with a sample image.

Capture Information:

Capture Pixel Resolution: 0.1 metres

Limitations:

Whilst every effort is made to provide the data as accurate as possible, the content may not be free from errors, omissions or defects.Preview:Download:A zip file containing all relevant files representing the Digital Surface ModelDownload Digital Surface Model data (12.0GB)

Peel's Digital Elevation Model (DEM) provides a generalized representation of both surface and ground features at a 1 metre resolution. The data is created using breaklines and a 10-metre grid of masspoints, both of which are photogrammatically created.

Available products

Peel Digital Elevation Model in TIFF format - 1.5 Gigabytes

Specifications

Capture year: Spring 2022 Spatial resolution: 1-metre File format: GeoTIFF, losslessly compressed Pixel type and depth: 32-bit float Horizontal projection: NAD 1983 UTM Zone 17N (EPSG: 26917) Vertical projection: CGVD 1928 (EPSG: 5713) Horizontal accuracy: ±50 centimetres Vertical accuracy: ±50 centimetres Method of creation: photogrammetric

Other data (Lidar) The Region of Peel doesn't have Lidar data in-house. The Province of Ontario through Land Information Ontario provides the following Lidar and Lidar-based datasets through their open data program:

Lidar-derived Digital Terrain Model (DTM) Lidar-derived Digital Surface Model (DSM) Lidar-derived classified point cloud - by request