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

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.

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 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

In advance of design, permitting, and construction of a pipeline to deliver North Slope natural gas to out-of-state customers and Alaska communities, the Division of Geological & Geophysical Surveys (DGGS) has acquired lidar (Light Detection and Ranging) data along proposed pipeline routes, nearby areas of infrastructure, and regions where significant geologic hazards have been identified. Lidar data will serve multiple purposes, but have primarily been collected to (1) evaluate active faulting, slope instability, thaw settlement, erosion, and other engineering constraints along proposed pipeline routes, and (2) provide a base layer for the state-federal GIS database that will be used to evaluate permit applications and construction plans. The dataset represents all classified laser returns from the lidar survey and their associated geospatial coordinates.

This metadata record describes the ortho & LIDAR mapping of Citrus County, FL. The mapping consists of LIDAR data collection, contour generation, and production of natural color orthophotography with a 1ft pixel using imagery collected with a Wild RC-30 Aerial Camera.

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.

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 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 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.

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

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.

The LIDAR Composite First Return DSM (Digital Surface Model) is a raster elevation model covering ~99% of England at 2m spatial resolution. The first return DSM is produced from the first or only laser pulse returned to the sensor and includes heights of objects, such as vehicles, buildings and vegetation, as well as the terrain surface where the first or only return was the ground.

Produced by the Environment Agency in 2022, the first return DSM is derived from data captured as part of our national LIDAR programme between 11 November 2016 and 5th May 2022. This programme divided England into ~300 blocks for survey over continuous winters from 2016 onwards. These surveys are merged together to create the first return LIDAR composite using a feathering technique along the overlaps to remove any small differences in elevation between surveys. Please refer to the metadata index catalgoues which show for any location which survey was used in the production of the LIDAR composite.

The first return DSM will not match in coverage or extent of the LIDAR composite last return digital surface model (LZ_DSM) as the last return DSM composite is produced from both the national LIDAR programme and Timeseries surveys.

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.

These data were collected by the SHOALS-1000T(Scanning Hydrographic Operational Airborne Lidar Survey)system which consists of an airborne laser transmitter/receiver with a 1kHz. bathymetric laser and a10 kHz topographic laser. The system was operated from a Beechcraft King Air 90aircraft. Data were collected with the bathymetric laser while flying at altitudes of about 400 meters and a groundspeed of about 124 knots. The topographic laser data was collected at altitudes of about 700 m and a groundspeed of 150 kts. One KGPS base stations was used during processing of the dataset. The SHOALS system includes a ground-based data processing system for calculating accurate horizontal position and water depth / elevation. LIDAR is an acronym for LIght Detection And Ranging. The system operates by emitting a pulse of light that travels from an airborne platform to the water surface where a small portion of the laser energy is backscattered to the airborne receiver. The remaining energy at the water\x92s surface propagates through the water column and reflects off the sea bottom and back to the airborne detector. The time difference between the surface return and the bottom return corresponds to water depth. The maximum depth the system is able to sense is related to the complex interaction of radiance of bottom material, incident sunangle and intensity, and the type and quantity of organics or sediments in the water column. As a rule-of-thumb, the SHOALS 1000 system is capable of sensing bottom to depths equal to two or three times the Secchi depth. Bathymetric soundings are gridded in this dataset.

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.

U.S. Geological Survey (USGS) scientists completed a multidisciplinary data collection effort during the week of October 21-25, 2019, using new technologies to map and validate bathymetry over a large stretch of the non-tidal Potomac River. The work was initiated as an effort to validate commercially-acquired topobathymetric light detection and ranging (lidar) data funded through a partnership between the USGS and the Interstate Commission on the Potomac River Basin (ICPRB). The goal was to compare airborne lidar data to bathymetric data collected through more traditional means (boat-based sonar, wading Real Time Kinematic Global Navigational Satellite System (RTK-GNSS) surveys) and through unmanned aerial systems (UAS). In addition to accurately measuring river bottom elevations with GNSS and sonar, remote sensing imagery was collected with optical, multispectral, thermal, and ground-based lidar (GBL) sensors to test new technologies. The bathymetric lidar data, once delivere ...

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

2010 Boulder Creek, Colorado Snow-Off LiDAR Surveys LiDAR was acquired for a 600 km2 area inside the Boulder Creek watershed during a snow-off (August, 2010) time slice, near Boulder Colorado. This data was collected in collaboration between the National Center for Airborne Laser Mapping (NCALM) project and the Boulder Creek Critical Zone Observatory (CZO), both funded by the National Science Foundation (NSF). The dataset contains 1 m Digital Surface Models (first-stop), Digital Terrain Models (bare-earth), and 10 points/m2 LAS-formated point cloud tiles. The DSMs and DTMs are available in GeoTIFF format, approx. 1-2 GB each, with associated shaded relief models, for a total of 15 GB of data. The Digital Terrain Model (DTM) is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. Accessory layers consist of index map layers for point cloud tiles, DEM extent, and flight lines. Other LiDAR DSMs, DTMs, and point cloud data available in this series include snow-on data for 2010. Together, the LiDAR Digital Elevation Models (DEM) and point cloud data will be of interest to land managers, scientists, and others for study of topography, snow, ecosystems and environmental change. The Boulder Creek CZO will be using the LiDAR data to further their mission of focusing on how water, atmosphere, ecosystems, & soils interact and shape the Earth's surface. The "Critical Zone" lies between rock and sky. It is essential to life - including human food production - and helps drive Earth's carbon cycle, climate change, stream runoff, and water quality. PLEASE READ the FGDC-compliant metadata files that are available for each dataset (in .html, .txt, and .xml formats). These files provide numerous details that may be of interest. Also included are flight lines, survey reports, reference materials, and DEM extent shapefiles.

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.

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.