This survey covers portions of Hawaii Volcano National Park, Upper Waiakea Forest Reserve, and Mauna Loa Forest Reserve on the Big Island of Hawaii. The survey area covers 299 square kilometers. These data were collected by the National Center for Airborne Laser Mapping (NCALM) on behalf of Steve Martel (University of Hawaii), Scott Rowland (University of Hawaii), Adam Soule (Woods Hole Oceanographic Institution) and Kathy Cashman (U. Oregon / Bristol U.).

Publications associated with this dataset can be found at NCALM's Data Tracking Center

The Environment Agency LIDAR Ground Truth surveys dataset is an archive of elevation points and attribute information that have been independently surveyed to verify the accuracy of the EA's LIDAR timestamped surveys. Captured by various independent surveyors, a ground truth survey is a collection of a few hundred points captured on a flat, unambiguous surface such as a tarmac car park or tennis court using GPS. Each ground truth point has an accuracy of +/-3cm R.M.S.E and contains attribute information such as the date of survey, surface type, survey method and transformation and geoidal models used. A ground truth survey may potentially be used for multiple LIDAR surveys provided it is less than 5 years old, or 3 years for coastal projects. The LIDAR timestamped survey is compared against the ground truth survey to assess the Root Mean Square Error (R.M.S.E), standard deviation and random error of the LIDAR. All LIDAR surveys must report an error of less than +/-15cm RMSE and 10cm for standard deviation and random error to pass quality control. For the specific ground truth results for a LIDAR survey please contact us. Attribution statement: © Environment Agency copyright and/or database right 2015. All rights reserved.

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.

Product: Processed, classified lidar point cloud data tiles in LAS 1.4 format. Geographic Extent: Approximately 4,028 square miles encompassing the Big Island of Hawaii. Dataset Description: The HI Hawaii Island Lidar NOAA 2017 B17 lidar project called for the planning, acquisition, processing, and production of derivative products of lidar data to be collected at a nominal pulse spacing (NPS...

This dataset is a lidar survey by the Middle Usumacinta Archaeological Project. It examines the distribution of archaeological sites in the Middle Usumacinta region in eastern Tabasco, Mexico. Data was collected for Dr. Takeshi Inomata at the University of Arizona.

The LIDAR Composite DTM (Digital Terrain Model) is a raster elevation model covering ~99% of England at 1m spatial resolution.The DTM (Digital Terrain Model) is produced from the last or only laser pulse returned to the sensor. We remove surface objects from the Digital Surface Model (DSM), using bespoke algorithms and manual editing of the data, to produce a terrain model of just the surface. Produced by the Environment Agency in 2022, the DTM is derived from a combination of our Time Stamped archive and National LIDAR Programme surveys, which have been merged and re-sampled to give the best possible coverage. Where repeat surveys have been undertaken the newest, best resolution data is used. Where data was resampled a bilinear interpolation was used before being merged. The 2022 LIDAR Composite contains surveys undertaken between 6th June 2000 and 2nd April 2022. Please refer to the metadata index catalgoues which show for any location which survey was used in the production of the LIDAR composite.DEFRA Data Services Platform Metadata URLDefra Network WMS server provided by the Environment Agency

This data collection of the 3D Elevation Program (3DEP) consists of Lidar Point Cloud (LPC) projects as provided to the USGS. These point cloud files contain all the original lidar points collected, with the original spatial reference and units preserved. These data may have been used as the source of updates to the 1/3-arcsecond, 1-arcsecond, and 2-arcsecond seamless 3DEP Digital Elevation Models (DEMs). 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. Lidar (Light detection and ranging) discrete-return point cloud data are available in LAZ format. The LAZ format is a lossless compressed version of the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format. Point Cloud data can be converted from LAZ to LAS or LAS to LAZ without the loss of any information. Either format stores 3-dimensional point cloud data and point ...

This metadata record describes the acquisition and processing of bare earth lidar data, raw point cloud lidar data, lidar intensity data, and floodmap breaklines consisting of a total of 280 sheets for Camp Shelby, MS. The post-spacing for this project is 3-meter. This project was broken into 3 parts, Acquisition, Part A Processing, and Part B Processing. Acquisition was tasked by Mississippi...

The surveyed area covers 28.5 square kilometers of the Black Hills Experimental Forest, South Dakota. These LAS and associated files were collected by Horizon's Inc. of Rapid City, SD and processed by the USDA Forest Service in Moscow, ID. The purpose of the data collection is to use Lidar in support of natural resource research and management applications.

U.S. Geological Survey (USGS) scientists conducted field data collection efforts between July 19th and 31st, 2021 over a large stretch of the McKenzie River in Oregon using high accuracy surveying technologies. The work was initiated as an effort to validate commercially acquired topobathymetric light detection and ranging (lidar) data that was collected coincidentally between July 26th and 30th, 2021 for the USGS 3D Elevation Program (3DEP). The goal was to compare and validate the airborne lidar data to topographic, bathymetric, structural, and infrastructural data collected through more traditional means (e.g., Global Navigational Satellite System (GNSS) surveying). Evaluating these data will provide valuable information on the performance of inland topobathymetric lidar mapping capabilities and their potential for use and inclusion in the USGS National Geospatial Program 3D Elevation Program. The airborne topobathymetric lidar data will be used for developing reliable hydraulic models, which can be used to model potential flood inundation and analysis for other potential hazards such as landslides. The bathymetric lidar data will also be used for characterization of endangered species aquatic habitat, including that of salmon and steelhead trout species. Furthermore, a large portion of the McKenzie River corridor that was mapped by the airborne topobathymetric lidar was impacted by the Holiday Farm Fire that burned over 170,000 acres during September of 2020 and the airborne data will be used to support post-fire geomorphic change detection.

The Utah Geological Survey (UGS) as part of its mission to provide timely scientific information about Utah's geologic environment, resources, and hazards, acquires Lidar data with its partners in support of various geologic mapping and research projects. In 2011, the UGS and partners acquired approximately 4927 square kilometers of 1 meter Lidar data over the Cedar/Parowan Valley, Great Salt Lake shoreline/wetlands, Hurricane fault zone, Lowry Water, Ogden Valley, and North Ogden areas of Utah. The datasets include raw LAS, LAS, DEM, DSM, and metadata (includes XML metadata, project tile indexes, and area completion reports) files. The datasets acquired by the UGS and its partners are in the public domain and can be freely distributed with proper credit to the UGS and its partners. These datasets were funded by the Utah Geological Survey, with the exception of the Great Salt Lake area, which was funded by the U.S. Environmental Protection Agency (grant no. CD-96811101-0) and the UGS, and the North Ogden area, which was funded by the Utah Division of Emergency Management, Floodplain Management Program.

High-resolution Lidar survey covers the area of 722 km2 which includes the Valles Caldera (upper part of the Jemez River basin) and Frijoles Canyon, New Mexico. The data collection was jointly funded by the National Science Foundation (NSF), Valles Caldera National Preserve (VCNP), Bandelier National Monument/National Park Service (BNM/NPS) and United States Geological Survey (USGS) and performed by the National Center for Airborne Laser Mapping (NCALM) during a snow-off season (June and July 2010). The dataset contains point cloud tiles in LAS format, 1 m Digital Surface Model (DSM) derived using first-stop points, 1 m Digital Elevation Model (DEM) derived using ground-class points and 1 m hill shade dataset derived from DEM. This dataset, together with the snow-on Lidar survey performed in March and April 2010, are being used to estimate snowpack, vegetation biomass and distribution, and bare earth elevations to help better understand and quantify ecosystem structure, geomorphology, and landscape processes within the Critical Zone Observatory.

LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The LiDAR systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures and vegetation. The ta...

This lidar dataset was collected as part of an NCALM Seed grant for Conor McMahon at the University of California, Santa Barbara. This dataset was collected to provide riparian vegetation mapping, classification, and measure historic drought response on the San Pedro river. The study area is located east of Sierra Vista, Arizona and covers approximately 81.5 km².

Publications associated with this dataset can be found at NCALM's Data Tracking Center

An aerial LiDAR survey of the lower Rio Puerco was conducted in April and July 2005 by Spectrum Mapping, LLC, under contract with the USGS (Contract #14040050). The surveyed reach extends from the NM Highway 6 crossing 55 km downvalley to the old Highway 85 bridge near the USGS streamgage near Bernardo, NM. Survey procedures, equipment and products are described in the Rio Puerco Project Report (Spectrum Mapping, LLC, Aug. 1, 2005), provided with this data set. The survey data include breaklines (shapefiles) used to process the elevation data, bare-earth Digital Terrain Models (DTMs) with 2-m cell size in the ArcGrid format, LAS-formatted files, and the original random xyz data. Results from analyses using these data were published in the following articles: Vincent, K.R., Friedman, J.M., and Griffin, E.R., 2009, Erosional consequence of saltcedar control, Environmental Management, 44, 218-227. doi: 10.1007/s00267-009-9314-8 Griffin, E.R., Smith, J.D., Friedman, J.M., and Vincent, K.R., 2010, Progression of streambank erosion during a large flood, Rio Puerco arroyo, New Mexico, Proceedings of the 2nd Joint Federal Interagency Conference, Las Vegas, NV, June 27 – July 1, 2010, 12 p. Perignon, M.C., Tucker, G.E., Griffin, E.R., and Friedman, J.M., 2013, Effects of riparian vegetation on topographic change during a large flood event, Rio Puerco, New Mexico, USA, Journal of Geophysical Research: Earth Surface, 118, 1193-1209. doi: 10.1002/jgrf.20073 Griffin, E.R., Perignon, M.C., Friedman, J.M., and Tucker, G.E., 2014, Effects of woody vegetation on overbank sand transport during a large flood, Rio Puerco, New Mexico, Geomorphology, 207, 30-50. doi: 10.1016/j.geomorph.2013.10.025 Friedman, J.M., Vincent, K.R., Griffin, E.R., Scott, M.L., Shafroth, P.B., and Auble, G.T., 2015, Processes of arroyo filling in northern New Mexico, USA, GSA Bulletin, 127(3/4), 621-640. doi: 10.1130/B31046.1

The survey covers areas of the Malheur National Forest, Idaho, and were collected by Watershed Sciences in Corvallis, OR and processed by the USDA Forest Service in Moscow, ID. Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (Lidar) data for the Damon Region of Malheur National Forest on September 15 and 16, 2007. The Area of Interest (AOI) covers 31,614 acres (north: 9,598 acres, south: 22,016 acres). The purpose of this collection is to use Lidar in support of natural resource research and management applications.

This Data Series Report contains lidar elevation data collected February 6, 2012, over the Chandeleur Islands, Louisiana. LAS 1.2 formatted point data files were generated based on these data. The point cloud data were processed to extract bare earth data; therefore, the point cloud data are classified into only these classes: 1 and 17-unclassified, 2-ground, 9-water, and 10-breakline proximity. Digital Aerial Solutions, LLC, was contracted by the USGS to collect and process these data. The lidar data were collected at a nominal pulse spacing (NPS) of 0.5 meter (m). The data are in decimal degree geographic coordinates, North American Datum 1983, National Spatial Reference System 2007 (NAD83 NSRS2007)). The vertical datum is North American Vertical Datum 1988, Geoid 2009, Geodetic Reference System 1980 (NAVD88 GEOID09 GRS80) in meters. Thirty-three LAS files, based on a 2-kilometer by 2-kilometer tiling scheme, cover the entire survey area. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.

This layer shows the Digital Surface Model of Hong Kong from 2020 LiDAR Survey. 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://GEODATA.GOV.HK/ ("Hong Kong Geodata Store"). The source data is in GML format and has been processed and converted into Esri File Geodatabase format and 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 Hong Kong Geodata Store at https://geodata.gov.hk/.

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

U.S. Geological Survey (USGS) scientists conducted field data collection efforts during the time periods of April 25 - 26, 2017, October 24 - 28, 2017, and July 25 - 26, 2018, using a combination of surveying technologies to map and validate topography, structures, and other features at five sites in central South Dakota. The five sites included the Chamberlain Explorers Athletic Complex and the Chamberlain High School in Chamberlain, SD, Hanson Lake State Public Shooting Area near Corsica, SD, the State Capital Grounds in Pierre, SD, and Platte Creek State Recreation Area near Platte, SD. The work was initiated as an effort to evaluate airborne Geiger-Mode and Single Photon light detection and ranging (lidar) data that were collected over parts of central South Dakota. Both Single Photon and Geiger-Mode lidar offer the promise of being able to map areas at high altitudes, thus requiring less time than traditional airborne lidar collections, while acquiring higher point densities. Real Time Kinematic Global Navigational Satellite System (RTK-GNSS), total station, and ground-based lidar (GBL) data were collected to evaluate data collected by the Geiger-Mode and Single Photon systems.