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 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.

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.

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.

A pilot bathymetric LiDAR survey was commissioned in 2021 which mapped the nearshore areas of Dundrum Bay and areas of Carlingford Lough./p>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 Digital Terrain Model created from the LiDAR dataset.

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.

In 2021, a complete airborne LiDAR survey of the Northern Ireland coastline was captured as part of the NI 3D Coastal Survey, providing precise and accurate data of the current coastal morphology.The survey included the intertidal area and extended approximately 200 meters landward of the high-water mark.This is the LiDAR Point Cloud created from the LiDAR data.

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...

This lidar dataset was collected by NCALM for Paula Figueiredo at North Carolina State University. This dataset was collected to examine earthquake dynamics related to the Mw 5.1 2020 earthquake in Sparta, North Carolina. The study area covers approximately 11 km2. Publications associated with this dataset can be found at NCALM's Data Tracking Center

High-resolution Lidar data (average first-return point density of 10 points m2 and 2-4 cm vertical accuracy) were obtained by NCALM for 121 km2 of the Christina River Basin Critical Zone Observatory (CRB-CZO) during both leaf-off (April 2010) and leaf-on (July 2010; see dataset CRB-10-Jul) periods. Data acquisition, ground-truthing, vegetation surveys and processing were funded and coordinated by NSF Award EAR-0922307 (PI. Qinghua Guo) to collect similar data at all six CZOs for a variety of cross-site analyses, including calibration of algorithms to extract vegetation characteristics from the LIDAR point cloud data. The CRB-CZO is particularly interested in using this LIDAR dataset for high-resolution analyses of stream channel and floodplain geomorphology. Publications associated with this dataset can be found at NCALM's Data Tracking Center

Airborne light detection and ranging (lidar) can provide high-quality topographic information over large areas. Lidar is an active remote sensing technology that employs laser ranging in near-infrared and green spectral wavelengths to provide three-dimensional (3D) point information for objects, including Earth’s surface, vegetation, and infrastructure. The U.S. Geological Survey (USGS) National Geospatial Program (NGP) 3D Elevation Program (3DEP) seeks to systematically acquire airborne topographic lidar for the conterminous U.S. (conus), Hawaii, and the U.S. territories. A series of field accuracy assessment surveys, using conventional surveying methods (i.e. total station and Global Navigation Satellite System (GNSS)) along with ground based lidar (GBL), were conducted at test sites in Northeastern Illinois (NEIL) to evaluate the 3D absolute and relative accuracy of airborne lidar acquired for 3DEP.

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 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.

Airborne lidar data were collected with the Optech Titan multispectral sensor of the McMurdo Dry Valleys, Antarctica during the austral summer of 2014-2015 as part of an effort to understand geomorphic changes over the past decade. Lidar point density varied from 2 to >10 returns per m2 with an average of about 5 returns per m2. Vertical and horizontal accuracies are estimated to be 0.07 m and 0.03 m, respectively. The lidar coverage comprises roughly 3600 km2 with includes the bottoms and sides of Taylor, Pearse, Wright, Victoria, Mckelvey, Barwick, and Valham valleys, Bull Pass, in addition to other ad hoc regions nearby including the Pegasus flight facility and two regions on Ross Island, McMurdo Station/Scott Base (and surroundings), and the coastal margin between Cape Royds and Cape Evans. A detailed description of the survey can be found in the Earth System Science Data publication High-resolution elevation mapping of the McMurdo Dry Valleys, Antarctica, and surrounding regions (Fountain et al., 2017). Publications associated with this dataset can be found at NCALM's Data Tracking Center

This lidar dataset was collected as part of an NCALM Seed grant for Anna Marshall at Colorado State University. This dataset was collected to help understand sources and functions of spatial heterogeneity in determining channel evolution of large mountain rivers. Lidar surveys were conducted over the Swan and Middle Fork Flathead rivers in Montana.

NCALM Seed. PI: Jill Marshall, San Francisco State University. The project area covers portions of the San Jose Mountains and consists of two polygons totaling approximately 50 square kilometers. The area of interest is located 30 kilometers west of San Jose, CA and was flown on Wednesday and Thursday, December 6-7, 2006.

Fugro were commissioned to undertake a post storm LiDAR survey of the soft sedimentary areas along the north coast of Northern Ireland in March 2022. This survey was to cover the following areas: Curran Strand, Portrush East Strand, Portstewart Strand and Downhill Beach to Magilligan.This project was commissioned following the successive storm events during February and March 2022 (Storm Dudley, Storm Eunice and Storm Franklin) which did considerable damage to the sandy beaches along the North Coast. The objective of this survey was to ascertain change which has occurred along these soft sediment coastlines at the north coast since the baseline survey, which was acquired in 2021.Data was provided in the same format as the topographic LiDAR data collected in the Northern Ireland 3-Dimensional Coastal Survey to allow changes between these two datasets to be ascertained.Later in the year Fugro were commissioned to undertake a second LiDAR survey of the north coast from White Rocks to Magilligan in September 2022. The aim of this repeat survey was to ascertain the levels of recovery along the soft sediment coastlines since March 2022.As with the initial survey undertaken by Fugro this topographic LiDAR survey collected data from the intertidal area to 10m inland for the same soft sediment areas along the north coast, with data being acquired at 0.5m resolution. The survey was quite restrictive when it could be flown: it had to be 2 hours either side of Low Water, during clear conditions below 6000ft, sun had to be at a suitable angle to capture imagery and as photography was being captured the survey could only be flown during day light hours. All data collected was to be directly comparable with the data collected in the initial post storm Survey undertaken, as this would help us to understand and accurately quantify how our soft, sedimentary coastlines respond and recover from extreme storm events.This is the LiDAR point cloud created from the post-storm recovery LiDAR data.

In 2018, the Nature Conservancy established the Jack and Laura Dangermond Preserve, a 24,364 acre property around Point Conception, California. The Preserve protects over eight miles of near-pristine coastline and rare connected coastal habitat in Santa Barbara County. Soon after the Preserve was established, Aeroptic, LLC, an aerial imagery company, worked with The Nature Conservancy and ESRI to capture aerial lidar and natural color orthomosaic imagery over the Preserve

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

This dataset provides the complete catalog of point cloud data collected during LiDAR surveys over selected forest research sites across the Amazon rainforest in Brazil between 2008 and 2018 for the Sustainable Landscapes Brazil Project. Flight lines were selected to overfly key field research sites in the Brazilian states of Acre, Amazonas, Bahia, Goias, Mato Grosso, Para, Rondonia, Santa Catarina, and Sao Paulo. The point clouds have been georeferenced, noise-filtered, and corrected for misalignment of overlapping flight lines. They are provided in 1 km2 tiles. The data were collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time.