Web map displaying Wisconsin DNR-produced Digital Elevation Model (DEM) and Hillshade image services, along with their index layer, in formats that are clickable and can be symbolized and filtered. This map can also be used as a starting point to create a new map. To open the web map from DNR's GIS Open Data Portal, click the View Metadata: link to the right of the description, then click Open in Map Viewer.

Lidar point cloud data with classifications – unclassified (1), ground (2), low vegetation (3), medium vegetation (4), high vegetation (5), buildings (6), low point - noise (7), reserved – model keypoint (8), high noise (18).

This data was collected by the Geological Survey Ireland, the Department of Culture, Heritage and the Gaeltacht, the Discovery Programme, the Heritage Council, Transport Infrastructure Ireland, New York University, the Office of Public Works and Westmeath County Council. All data formats are provided as GeoTIFF rasters but are at different resolutions. Data resolution varies depending on survey requirements. Resolutions for each organisation are as follows: GSI – 1m DCHG/DP/HC - 0.13m, 0.14m, 1m NY – 1m TII – 2m OPW – 2m WMCC - 0.25m Both a DTM and DSM are raster data. 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. The grid cell size varies depending on the organisation that collected it. GSI data has a grid cell size of 1 meter by 1 meter. This means that each cell (pixel) represents an area of 1 meter squared.

This layer shows LiDAR Data in Hong Kong. It is a set of data made available by the Civil Engineering and Development Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data has been processed and converted into 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 CSDI Portal at https://portal.csdi.gov.hk.

Note: The shapefile download may fail when downloading the entire dataset. If this happens, download the file geodatabase instead.Feature class contains 2-foot interval contours of the area surrounding and including the Eugene urban growth boundary. Contours have been derived by LCOG from 2009 LiDAR data. The LiDAR data was prepared by Watershed Science for DOGAMI. General processing includes (1) joining Junction City, Coburg, Eugene East and Eugene West bare-earth quads into one mosaic, (2) smoothing the mosaic with a focal mean (3 x 3 rectangle), (3) contouring the smoothed bare-earth mosaic, and (4) quality-checking along the edges of the quads to insure matching contours. (DISCLAIMER: The maps and data available for access from the City of Eugene are provided "as is" without warranty or any representation of accuracy, timeliness or completeness. The burden for determining accuracy, completeness, timeliness, merchantability and fitness for or the appropriateness for use rests solely on the user accessing this information. The City of Eugene makes no warranties, expressed or implied, as to the use of the maps and data available for access at this website. There are no implied warranties of merchantability or fitness for a particular purpose. The user acknowledges and accepts all inherent limitations of the maps and data, including the fact that the maps and data are dynamic and in a constant state of maintenance, correction and revision. Any maps and associated data for access do not represent a survey. No liability is assumed for the accuracy of the data delineated on any map, either expressed or implied.)

Detroit Street View (DSV) is an urban remote sensing program run by the Enterprise Geographic Information Systems (EGIS) Team within the Department of Innovation and Technology at the City of Detroit. The mission of Detroit Street View is ‘To continuously observe and document Detroit’s changing physical environment through remote sensing, resulting in freely available foundational data that empowers effective city operations, informed decision making, awareness, and innovation.’ LiDAR (as well as panoramic imagery) is collected using a vehicle-mounted mobile mapping system.

Due to variations in processing, index lines are not currently available for all existing LiDAR datasets, including all data collected before September 2020. Index lines represent the approximate path of the vehicle within the time extent of the given LiDAR file. The actual geographic extent of the LiDAR point cloud varies dependent on line-of-sight.

Compressed (LAZ format) point cloud files may be requested by emailing gis@detroitmi.gov with a description of the desired geographic area, any specific dates/file names, and an explanation of interest and/or intended use. Requests will be filled at the discretion and availability of the Enterprise GIS Team. Deliverable file size limitations may apply and requestors may be asked to provide their own online location or physical media for transfer.

LiDAR was collected using an uncalibrated Trimble MX2 mobile mapping system. The data is not quality controlled, and no accuracy assessment is provided or implied. Results are known to vary significantly. Users should exercise caution and conduct their own comprehensive suitability assessments before requesting and applying this data.

Sample Dataset: https://detroitmi.maps.arcgis.com/home/item.html?id=69853441d944442f9e79199b57f26fe3

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 web map allows for the download of KyFromAbove LiDAR data by 5k tile in LAZ format. This point cloud data was acquired during the typical leaf-off acquisition period (winter-spring) over a period of several years and may be provided as LAS version 1.1, 1.2, or 1.4 depending upon the acquisition period. Users will need to download the LAZIP.exe in order to decompress each tile. LiDAR data specifications adopted by the KyFromAbove Technical Advisory Committee can be found here. This is the source data used to create the Commonwealth's 5 foot digital elevation model (DEM) and its associated derivatives. More information regarding this data resource can be found on the KyGeoPortal.

Statewide 2016 Lidar points colorized with 2018 NAIP imagery as a scene created by Esri using ArcGIS Pro for the entire State of Connecticut. This service provides the colorized Lidar point in interactive 3D for visualization, interaction of the ability to make measurements without downloading.Lidar is referenced at https://cteco.uconn.edu/data/lidar/ and can be downloaded at https://cteco.uconn.edu/data/download/flight2016/. Metadata: https://cteco.uconn.edu/data/flight2016/info.htm#metadata. The Connecticut 2016 Lidar was captured between March 11, 2016 and April 16, 2016. Is covers 5,240 sq miles and is divided into 23, 381 tiles. It was acquired by the Captiol Region Council of Governments with funding from multiple state agencies. It was flown and processed by Sanborn. The delivery included classified point clouds and 1 meter QL2 DEMs. The 2016 Lidar is published on the Connecticut Environmental Conditions Online (CT ECO) website. CT ECO is the collaborative work of the Connecticut Department of Energy and Environmental Protection (DEEP) and the University of Connecticut Center for Land Use Education and Research (CLEAR) to share environmental and natural resource information with the general public. CT ECO's mission is to encourage, support, and promote informed land use and development decisions in Connecticut by providing local, state and federal agencies, and the public with convenient access to the most up-to-date and complete natural resource information available statewide.Process used:Extract Building Footprints from Lidar1. Prepare Lidar - Download 2016 Lidar from CT ECO- Create LAS Dataset2. Extract Building Footprints from LidarUse the LAS Dataset in the Classify Las Building Tool in ArcGIS Pro 2.4.Colorize LidarColorizing the Lidar points means that each point in the point cloud is given a color based on the imagery color value at that exact location.1. Prepare Imagery- Acquire 2018 NAIP tif tiles from UConn (originally from USDA NRCS).- Create mosaic dataset of the NAIP imagery.2. Prepare and Analyze Lidar Points- Change the coordinate system of each of the lidar tiles to the Projected Coordinate System CT NAD 83 (2011) Feet (EPSG 6434). This is because the downloaded tiles come in to ArcGIS as a Custom Projection which cannot be published as a Point Cloud Scene Layer Package.- Convert Lidar to zlas format and rearrange. - Create LAS Datasets of the lidar tiles.- Colorize Lidar using the Colorize LAS tool in ArcGIS Pro. - Create a new LAS dataset with a division of Eastern half and Western half due to size limitation of 500GB per scene layer package. - Create scene layer packages (.slpk) using Create Cloud Point Scene Layer Package. - Load package to ArcGIS Online using Share Package. - Publish on ArcGIS.com and delete the scene layer package to save storage cost.Additional layers added:Visit https://cteco.uconn.edu/projects/lidar3D/layers.htm for a complete list and links. 3D Buildings and Trees extracted by Esri from the lidarShaded Relief from CTECOImpervious Surface 2012 from CT ECONAIP Imagery 2018 from CTECOContours (2016) from CTECOLidar 2016 Download Link derived from https://www.cteco.uconn.edu/data/download/flight2016/index.htm

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

Robots, such as unmanned aerial vehicles and robot dogs, are suitable for exploring unknown environments that are dangerous for a human to walk in. These robots are equipped with sensors to obtain information from the environment. A map of the environment is simultaneously constructed on the robot while an online exploration algorithm determines the next area to explore based on the map. In most recent research on robotics, LiDARs have gained increasing interest thanks to their ability to provide dense and accurate depth measurements of environments. This dataset includes LiDAR data collected in both indoor and outdoor environments of HKU, which aims to benefit the robotic community and facilitate future research to advance the LiDAR mapping technology.

The Project data set consists of the Classified Point Cloud. The Geographical Extent of this dataset extends to the entirety of the AL_SWCentral_B22 UTM Zone 16N boundary, approximately 4685 square miles in the following counties: Choctaw, Mobile, Tuscaloosa, Washington

Ground Conditions: water at normal levels; no unusual inundation; no snow; leaf off. How the Withheld Points are Identified...

This resource contains Lidar-DEM collection status shapefiles from the Texas Natural Resources Information System (TNRIS) [http://tnris.org]. November 2023 updates: this year, TNRIS changed its name to Texas Geographic Information Office (TxGIO). The domain name hasn't changed yet, but the data hub is continually evolving. See [1], [2] for current downloadable data.

For purposes of Hurricane Harvey studies, the 1-m DEM for Harris County (2008) has also been uploaded here as a set of 4 zipfiles containing the DEM in tiff files. See [1] for a link to the current elevation status map and downloadable DEMs.
Project name: H-GAC 2008 1m Datasets: 1m Point Cloud, 1M Hydro-Enforced DEM, 3D Breaklines, 1ft and 5ft Contours Points per sq meter: 1 Total area: 3678.56 sq miles Source: Houston-Galveston Area Council (H-GAC) Acquired by: Merrick, QA/QC: Merrick Catalog: houston-galveston-area-council-h-gac-2008-lidar

References: [1] TNRIS/TxGIO StratMap elevation data [https://tnris.org/stratmap/elevation-lidar/] [2] TNRIS/TxGIO DataHub [https://data.tnris.org/]

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

Note: This service is only for using online; full resolution downloads are not supported. To enable pop ups when opening this in a new web map, then click the ellipsis (three blue dots) under the layer name in the contents, and choose Enable Pop-up.Image service created from Digital Elevation Models (DEMs) derived from county-produced LiDAR covering Wisconsin. Elevation units are in feet. This service was last updated May 2023. It can be used in conjunction with its associated Index layer, DEM and Hillshade from LiDAR - Index, to determine flight years of source LiDAR and resolution of source DEMs. Also see the Index layer item details for detailed information about counties included in this service and in related services: DEM from LiDAR (Units in Meters) and Hillshade from LiDAR.Some areas display as data gaps (white artifacts) when the service is viewed at statewide scales but display normally when zoomed in to scales of approximately 1:1,000,000 or larger. We hope to address the no-data areas and small-scale data gaps in future updates to this service. The source DEMs have not been hydrologically conditioned. The Vertical Datum for the DEMs is NAVD88.WI DNR acknowledges the USDA Natural Resources Conservation Service, USGS, FEMA, the Southeastern WI Regional Planning Commission, and the individual counties listed in DEM and Hillshade from LiDAR - Index, for making source data available. For more information, visit https://dnr.wi.gov/feedback/ and choose Geographic Information Systems Data as the subject.

This is compilation of Maine DEMs generated from lidar as a hillshade for MGS web applications. Not all view scales have been created.Users looking for lidar data and/or data derivatives should contact, in order:United States Interagency Elevation Inventory (USIEI): https://coast.noaa.gov/inventory/Maine GeoLibrary Elevation Discovery and Download: https://www1.maine.gov/geolib/ediscovery/site/landing.htmlNational Map (USGS) ftp: ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/

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 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 data set is tiled lidar point cloud LAS files v1.4, for the 2016 Alabama 25 County lidar area of interest (AOI).

USGS NGTOC task order G17PD00243 required Spring 2017 LiDAR surveys to be collected over 18,845 square miles covering part or all of 25 counties in Alabama. These counties are Autauga, Baldwin, Barbour, Bullock, Butler, Chambers, Cherokee, Clarke, Conecuh, Covington, Cre...

USGS task order 140G0218F0420 required Winter, 2018/Spring, 2019 LiDAR surveys to be collected over 32,562 square miles covering part or all of 82 counties in Georgia and 3 partial counties in South Carolina in support of the State of Georgia and the USGS 3DEP program. Aerial LiDAR data for this task order was planned, acquired, processed and produced at an aggregate nominal pulse spacing (ANPS...