A seamless hydro-flattened digital surface model (DSM) with 1 metre resolution. The DSM captures the land surface and natural and built features on the earth's surface, such as trees and buildings.The LiDAR data was captured for the Halifax Regional Municipality's coastal flood mapping project through topographic andtopo-bathymetric lidar data collection in 2017-2018 and was processed by the Applied Geomatics Research Group at NSCC.Due to limitations of the sensor used in the topography lidar data acquisition mission, the dataset excludes a significant number of buildings and other asphalt surfaces such as driveways. Users should use caution when using the data for those purposes. Metadata

The Digital Elevation Model (DEM) market, encompassing Digital Surface Models (DSM) and Digital Terrain Models (DTM), is experiencing robust growth, driven by increasing demand across diverse sectors. The market, currently valued at $1034.9 million in 2025, is projected to expand significantly over the forecast period (2025-2033). Key application areas like planning and construction, where DEMs are crucial for site analysis, infrastructure development, and 3D modeling, are fueling this expansion. Furthermore, the aviation industry relies heavily on DEMs for air traffic route planning and navigation, ensuring safe and efficient flight operations. Meteorological services utilize DEMs for accurate weather forecasting and modeling, while geological exploration leverages them for subsurface analysis and resource mapping. Technological advancements, including improved sensor technologies (LiDAR, photogrammetry) and the increasing availability of high-resolution satellite imagery, are further contributing to market growth. While data acquisition costs and processing complexities can pose challenges, the overall market outlook remains positive, supported by the continuous demand for precise and detailed elevation data across a broad range of applications. The geographical distribution of the DEM market is widespread, with North America and Europe currently holding significant market share. However, rapid economic development and infrastructure projects in Asia-Pacific regions, particularly China and India, are expected to drive substantial growth in these markets. Government initiatives promoting digital mapping and spatial data infrastructure are also contributing to market expansion globally. Competition in the DEM market is intense, with a mix of established players and emerging technology providers. The market is characterized by ongoing innovation in data acquisition techniques, processing algorithms, and data delivery platforms. Companies are focusing on developing integrated solutions that combine DEM data with other geospatial information, providing comprehensive analysis and visualization tools for end-users. The future of the DEM market is expected to be shaped by advancements in artificial intelligence (AI) and machine learning (ML), enabling automated data processing, improved accuracy, and enhanced analytical capabilities.

Digital Surface Model (DSM) for portions of the Hawaiian islands based upon lidar data collected by State of Hawaii and its data partners from 1999-2017. Elevation values are in meters.

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.

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.

LiDAR (Light Detection and Ranging) is a remote sensing technology, i.e. the technology is not in direct contact with what is being measured. From satellite, aeroplane or helicopter, a LiDAR system sends a light pulse to the ground. This pulse hits the ground and returns back to a sensor on the system. The time is recorded to measure how long it takes for this light to return. Knowing this time measurement scientists are able to create topography maps.LiDAR data are collected as points (X,Y,Z (x & y coordinates) and z (height)). The data is then converted into gridded (GeoTIFF) data to create a Digital Terrain Model and Digital Surface Model of the earth. This LiDAR data was collected on 25th March 2015.An ordnance datum (OD) is a vertical datum used as the basis for deriving heights on maps. This data is referenced to the Malin Head Vertical Datum which is the mean sea level of the tide gauge at Malin Head, County Donegal. It was adopted as the national datum in 1970 from readings taken between 1960 and 1969 and all heights on national grid maps are measured above this datum. Digital Terrain Models (DTM) are bare earth models (no trees or buildings) of the Earth’s surface.Digital Surface Models (DSM) are earth models in its current state. For example, a DSM includes elevations from buildings, tree canopy, electrical power lines and other features. Hillshading is a method which gives a 3D appearance to the terrain. It shows the shape of hills and mountains using shading (levels of grey) on a map, by the use of graded shadows that would be cast by high ground if light was shining from a chosen direction.This data shows the hillshade of the DSM.This data was collected by New York University. All data formats are provided as GeoTIFF rasters. Raster data is another name for gridded data. Raster data stores information in pixels (grid cells). Each raster grid makes up a matrix of cells (or pixels) organised into rows and columns. NYU data has a grid cell size of 1meter by 1meter. This means that each cell (pixel) represents an area of 1meter squared.

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 1000 meter resolution (EU-LAEA projection) 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 reproject the data to EU-LAEA projection while reducing the spatial resolution to 1000 m, bilinear resampling was performed in GRASS GIS (using r.proj 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: ETRS89-extended / LAEA Europe (EPSG: 3035) Spatial extent: north: 6874000 south: -485000 west: 869000 east: 8712000 Spatial resolution: 1000 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.proj; 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/) Acknowledgements: This study was partially funded by EU grant 874850 MOOD. The contents of this publication are the sole responsibility of the authors and don't necessarily reflect the views of the European Commission.

Digital Surface and Terrain Models (DSM,DTM) dataset current as of 2012. DSM & DTM products.The tile-based DSMs were created from the first return of all classified LiDAR points with a 1 meter cell size,DTMs created from the class 2 - ground LiDAR points .Their pixel size and alignment matches the DEM pixel size and alignment.

This is a collection of Digital Surface Models and Highest Hit rasters covering selected U.S. Forest Service and adjoining lands in the Southwest Region, encompassing Arizona and New Mexico. The data are presented in a time-enabled format, allowing the end-user to view available data year-by-year, or all available years at once, within a GIS system. The data encompass varying years, varying resolutions, and varying geographic extents, dependent upon available data as provided by the region. DSM and Highest Hit rasters represent elevation of Earth's surface, including its natural and human-made features, such as vegetation and buildings.The data contains an attribute table. Notable attributes that may be of interest to an end-user are:lowps: the pixel size of the source raster, given in meters.highps: the pixel size of the top-most pyramid for the raster, given in meters.beginyear: the first year of data acquisition for an individual dataset.endyear: the final year of data acquisition for an individual dataset.dataset_name: the name of the individual dataset within the collection.metadata: A URL link to a file on IIPP's Portal containing metadata pertaining to an individual dataset within the image service.resolution: The pixel size of the source raster, given in meters.Terrain-related imagery are primarily derived from Lidar, stereoscopic aerial imagery, or Interferometric Synthetic Aperture Radar datasets. Consequently, these derivatives inherit the limitations and uncertainties of the parent sensor and platform and the processing techniques used to produce the imagery. The terrain images are orthographic; they have been georeferenced and displacement due to sensor orientation and topography have been removed, producing data that combines the characteristics of an image with the geometric qualities of a map. The orthographic images show ground features in their proper positions, without the distortion characteristic of unrectified aerial or satellite imagery. Digital orthoimages produced and used within the Forest Service are developed from imagery acquired through various national and regional image acquisition programs. The resulting orthoimages can be directly applied in remote sensing, GIS and mapping applications. They serve a variety of purposes, from interim maps to references for Earth science investigations and analysis. Because of the orthographic property, an orthoimage can be used like a map for measurement of distances, angles, and areas with scale being constant everywhere. Also, they can be used as map layers in GIS or other computer-based manipulation, overlaying, and analysis. An orthoimage differs from a map in a manner of depiction of detail; on a map only selected detail is shown by conventional symbols whereas on an orthoimage all details appear just as in original aerial or satellite imagery.Tribal lands have been masked from this public service in accordance with Tribal agreements.

(Link to Metadata) This metadata applies to the following collection area(s): Addison County 2012 1.6m and related Digital Surface Model (DSM) data. This metadata complies with the VT Geodata Portal format and applies to thematic layers with the same resolution (RESCLASS), e.g., 0p7m, 1m etc., and may include multiple data "collection" efforts. For the original vendor metadata containing specific details on each collections "point cloud" such as flight dates, nominal pulse spacing and RMSEz etc., see the "All Available LiDAR" Product page: (https://vcgi.vermont.gov/warehouse/products/ALL-LDR_MIX_LIDAR_STATE_ALL). For an overview of the "Vermont LiDAR Initiative" please see "https://vcgi.vermont.gov/lidar".

This database supports the work of the Digital Elevation Model Intercomparison eXperiment (DEMIX) working group (Strobl and others, 2021; Guth and others, 2021; Bielski and others, 2023, 2024). The two files have the database in CSV format, and a metadata file describing the contents of each field in the database.

To understand the use of the database, see the prepint (Bielski and others, 2023).

Changes to version 2 which is the only version you should use:

1. Added 2 new areas, Stateline and Canary Islands East which should have minimal differences between the DSM and the DTM and no significant changes over the last 20 years.

2. Added the country to the database

3. Added a number of areas in France

4. Added some additional tiles for a few areas

5. Total number of tiles almost doubled

6. Now using GDAL to compute the datum shift, horizontal and vertical, for USGS 3DEP

7. Fixed some anomalies computing pixel-is-area DEMs

8. Recomputed all the reference data and the version 1.0 GIS database (Guth, 2022)

9. New file naming conventions

References:

Bielski, C.; López-Vázquez, C.; Guth. P.L.; Grohmann, C.H. and the TMSG DEMIX Working Group, 2023. DEMIX Wine Contest Method Ranks ALOS AW3D30, COPDEM, and FABDEM as Top 1” Global DEMs: https://arxiv.org/pdf/2302.08425.pdf

Bielski, C.; López-Vázquez, C.; Grohmann, C.H.; Guth. P.L.; Hawker, L.; Gesch, D.; Trevisani, S.; Herrera-Cruz, V.; Riazanoff, S.; Corseaux, A.; Reuter, H.; Strobl, P., 2024. Novel approach for ranking DEMs: Copernicus DEM improves one arc second open global topography. IEEE Transactions on Geoscience & Remote Sensing. vol. 62, pp. 1-22, 2024, Art no. 4503922, https://doi.org/10.1109/TGRS.2024.3368015

Guth, P.L.; Van Niekerk, A.; Grohmann, C.H.; Muller, J.-P.; Hawker, L.; Florinsky, I.V.; Gesch, D.; Reuter, H.I.; Herrera-Cruz, V.; Riazanoff, S.; López-Vázquez, C.; Carabajal, C.C.; Albinet, C.; Strobl, P. Digital Elevation Models: Terminology and Definitions. Remote Sens. 2021, 13, 3581. https://doi.org/10.3390/rs13183581

Strobl, P.A.; Bielski, C.; Guth, P.L.; Grohmann, C.H.; Muller, J.P.; López-Vázquez, C.; Gesch, D.B.; Amatulli, G.; Riazanoff, S.; Carabajal, C. The Digital Elevation Model Intercomparison eXperiment DEMIX, a community based approach at global DEM benchmarking. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2021, XLIII-B4-2021, 395–400. https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-395-2021

This 1m Digital Surface Model (DSM) shaded relief is derived from first-stop Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. The DSM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DSM shaded relief has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DSM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. cm RMSE at 1 sigma. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. This shaded relief model was also generated. A similar layer, the Digital Terrain Model (DTM), is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. A processing report and readme file are included with this data release. The DSM dataset is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.

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

Additional Documentation

Ontario DSM (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 Bay 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 DSM (Lidar-Derived) - Tile Index (SHP) Ontario Lidar Project Extents (SHP)

Product Packages Download links for the Ontario DSM (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

This 1m Digital Surface Model (DSM) is derived from first-stop Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. The DSM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DSM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DSM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. cm RMSE at 1 sigma. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. A shaded relief model was also generated. A similar layer, the Digital Terrain Model (DTM), is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. A processing report and readme file are included with this data release. The DSM is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.

Digital Surface Model of parts of Maui and Molokai. Partial coverage Vexcel, Inc. LIDAR of Maui and Molokai were purchased by County of Maui to assist with three-dimensional modeling of structures in areas of higher development. 1'/px, LIDAR-derived, digital surface elevation raster of parts of Maui and Molokai – specifically, Central Molokai, Kahului, Kihei, Lahaina and Pukalani. XY units: feet, Z units: meters. Use Limitations: 1.Disclaimer - This dataset is being placed in the public domain. Any use is allowed except for re-sale. Neither Vexcel, Inc., the County of Maui, nor the State of Hawaii make any guarantees, expressed or implied, regarding its accuracy or fitness of use. Users should verify XYZ values through a licensed surveyor for any engineering application. This data should only be used as a guide, vs. a statement of fact regarding real-world conditions. 2.Vertical Datum - The originator of this LIDAR dataset, Vexcel Inc. of Boulder, Colorado referenced Z values to the North American Vertical Datum of 1988 (NAVD88). NAVD88 is not recognized as a valid vertical reference for the state of Hawaii. Currently Hawaii has no official (de jure or de facto) vertical datum, and NOAA's National Geodetic Survey (NGS) recommends that elevations be referenced to the nearest NOAA tidal gauge. A legacy LIDAR dataset produced in 2013 by the United States Army Corps of Engineers (USACE) used NAD83(PA11) as its vertical reference. In theory this approach should result in better accuracy for the Z dimension as PA11 is a Pacific plate-centric datum. In comparing flat areas containing neither structures or vegetation, it was found that the Vexcel values sit approximately 4 feet above the USACE dataset. The vertical datum issue was brought to the attention of Vexcel, Inc. Vexcel used the 2013 USACE LIDAR as vertical control to correct their LIDAR data. The (corrected) .las data is shared as it was delivered. As stated above, the use of this data transfers all risks and assumption of responsibility to the user For more information see https://files.hawaii.gov/dbedt/op/gis/data/Maui_2019_DSM.html or contact County of Maui at GISMonitor@co.maui.hi.us or Hawaii Statewide GIS Program at gis@hawaii.gov.

This dataset has been deprecated. Please use our 2017 Digital Elevation Models instead.The Digital Surface Model (DSM) is a 3-foot pixel resolution raster in GeoTIFF format. This was created using all points (excluding NOISE) from our 2007 LiDAR data without incorporating the breaklines. Merrick and Co. MARS (ver. 8.0.4, build 8185) software was used to create the GeoTIFF images.The DSMs 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. The classified points were developed using data collected in April to May 2007. 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) as well as digital surface models (DSM). The use of LiDAR significantly reduces the cost for developing this information.The DSMs are intended to correspond to the orthometric heights of the surface of the county including above ground features such as buildings, vegetation cover, utility structures, vehicles ... etc. DSM data are used by county agencies and others to study drainage issues such as flooding and erosion; contour generation; slope and aspect; and hill shade images. Elevation data and models are used in several different ways including:Visualization representations of the elevation data. Examples include:- A hillshaded or shaded relief image- An image representing slope- An image representing aspectAnalysis of the elevation data and analytical products which can be generated. Examples include:- Viewshed calculations for visibility and line-of-sight analysis- Areas of highest Solar energy potential- Uses in disaster management- Industrial planning- Calculation of cartographic contours- Calculation of profiles along straight lines or line segmentsThese data are derived from other data sources, no accuracy measurements or tests were conducted. Primary use and intent for these data are for visualizations and topographic analysis. This dataset does not take the place of an on-site survey for design, construction or regulatory purposes.

Digital Surface Model. This dataset was created using first return LiDAR points.

This product set contains reduced-resolution Interferometric Synthetic Aperture Radar (IFSAR) imagery and geospatial data for the Barrow Peninsula (155.39 - 157.48 deg W, 70.86 - 71.47 deg N), for use in Geographic Information Systems (GIS) and remote sensing software. The primary IFSAR data sets were acquired by Intermap Technologies from 27 to 29 July 2002, and consist of an Orthorectified Radar Imagery (ORRI), a Digital Surface Model (DSM), and a Digital Terrain Model (DTM). Derived data layers include aspect, shaded relief, and slope-angle grids (floating-point binary format), as well as a vector layer of contour lines (ESRI Shapefile format). Also available are accessory layers compiled from other sources: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow Peninsula (ESRI Shapefile format). The DSM and DTM data sets (20 m resolution) are provided in floating-point binary format with header and projection files. The ORRI mosaic (5 m resolution) is available in GeoTIFF format. FGDC-compliant metadata for all data sets are provided in text, HTML, and XML formats, along with the Intermap License Agreement and product handbook. The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are available via FTP and CD-ROM.

Digital Surface Model (DSM) has three layers. Two layers come from the rasterisation of the building and vegetation classes among all the points of the LiDAR file .las; and the third layer is the hydrography of the Geographical Reference Information. By applying a suitable colour for each layer, the final product is visualised. ECW file format. ETRS89 reference geodetic system (in the Canary Islands REGCAN95, compatible with ETRS89) and EPSG projection: 3857 throughout the national territory

This layer is updated as new elevation data is available.ProjectionNew Zealand Transverse Mercator 2000 (NZTM2000).The New Zealand Hillshade DSM is a cached layer that visualizes New Zealand's Digital Surface Model as a Multi-Directional Hillshade. This layer can be used in combination with other New Zealand basemaps. In the map viewer, by using the layer blending options, this layer can be combined with other layers. The hillshade layer uses the publicly available 1m elevation data. Only for regions where high resolution DSM is available has this layer coverage. This layer will be regularly updated as more high resolution elevation data become available by Land Information New Zealand.The data in this layer is the same as the data in the New Zealand Elevation layer, except for datasets that don't have equivalent DSM. More information about this data can be found in the NZ Elevation metadata layer.This service is offered by Eagle Technology (Official Esri Distributor). Eagle Technology offers layers and maps that can be used in the ArcGIS platform. The Content team at Eagle Technology updates the layers on a regular basis and regularly adds new content to the Living Atlas. By using this content and combining it with other data you can create new information products quickly and easily.If you have any questions or remarks about the content, please let us now at livingatlas@eagle.co.nz