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.

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.

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.

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 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 attributes along with header information and variable length records specific to the data. Millions of data points are stored as a 3-dimensional data cloud as a series of geo-referenced x, y coordinates and z (elevation), as well as other attributes for each point. Additonal information about the las file format can be found here: https://www.asprs.org/divisions-committees/lidar-division/laser-las-file-format-exchange-activities. All 3DEP products are public domain.

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.

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...

A bathymetric survey of Blue Mountain Lake, Arkansas, was conducted in May 2017 by the Lower Mississippi-Gulf Water Science Center of the U.S. Geological Survey (USGS) using methodologies for sonar surveys similar to those described by Wilson and Richards (2006). Point data from the bathymetric survey were merged with point data from an aerial LiDAR survey conducted in December 2010, for the U.S. Army Corps of Engineers (USACE), Little Rock District. From the combined point data, a terrain dataset (a type of triangulated irregular network, or TIN, model) was created in Esri ArcGIS for the lakebed within the extent of pool elevation 420 feet above the North American Vertical Datum of 1988 (NAVD88). This Esri file geodatabase contains the following products: 1) point data from the bathymetric and LiDAR surveys; 2) a terrain dataset; 3) a digital elevation model (DEM) in Esri GRID format with a 3-ft cell size; 4) a feature class of bathymetric contours at 4-ft intervals; and 5) a table of storage capacity (volume) of the lake at 1-ft increments in water-surface elevation from 350-420 ft NAVD88 and seasonal conservation and flood pool elevations.

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.

U.S. Geological Survey (USGS) scientists conducted field data collection efforts between October 25th and 31st, 2020 at several sites in eastern Iowa using high accuracy surveying technologies. The work was initiated as an effort to validate commercially acquired topographic light detection and ranging (lidar) data that was collected between December 7th, 2019 and November 19th, 2020 using wide area mapping lidar systems for the USGS 3D Elevation Program (3DEP). The goal was to compare and validate the airborne lidar data to topographic, 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 wide area topographic lidar mapping capabilities that are becoming more widely used in 3DEP. The airborne lidar was collected to support the U.S. Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) High Resolution Elevation Enterprise Program and the Iowa Department of Agriculture and Land Stewardship Iowa Flood Plain Program, in addition to the 3DEP mission. The data contained within this particular release are comprised of conventional survey (i.e. total station and GNSS) and ground based lidar data.

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.

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.

Mapping Lidar Laser Market Outlook

The global market size for Mapping Lidar Laser in 2023 is estimated to be around USD 2.3 billion, and it is projected to reach approximately USD 7.1 billion by 2032, growing at a CAGR of 13.2% during the forecast period. This growth trajectory is driven by the expanding adoption of Lidar technology in various industries such as construction, transportation, and environmental monitoring, as well as technological advancements and the increasing need for precise geospatial measurements.

One of the primary growth factors in the Mapping Lidar Laser market is the rise in infrastructure development activities globally. Governments and private sectors are heavily investing in smart city projects, which require advanced mapping technologies for urban planning and development. Lidar technology, with its high accuracy and rapid data collection capabilities, is becoming indispensable for creating detailed 3D maps and models. Additionally, the increasing demand for autonomous vehicles, which rely heavily on Lidar systems for navigation and safety, is further propelling the market growth.

Furthermore, the need for efficient corridor mapping and aerial surveying has been driving the market. Lidar technology offers precise topographical data, which is crucial for planning transportation routes, such as highways and railway lines. This technology is also being extensively adopted in the forestry and agriculture sectors for vegetation analysis and land use planning. The ability of Lidar to penetrate through foliage and provide detailed ground surface models makes it a valuable tool in these industries.

Technological advancements in Lidar systems are also contributing significantly to market growth. The development of compact, lightweight, and cost-effective Lidar sensors has made the technology more accessible to a broader range of applications. Innovations such as solid-state Lidar and advancements in data processing algorithms have improved the performance and reduced the costs of Lidar systems, making them an attractive option for various industries. This continuous evolution in technology is expected to sustain the market's growth momentum over the forecast period.

Light Detection and Ranging Devices, commonly known as Lidar, have revolutionized the way we perceive and interact with our environment. These devices utilize laser pulses to measure distances with high precision, creating detailed three-dimensional maps of the surroundings. The ability of Lidar to provide accurate and real-time data has made it an essential tool in various industries, from urban planning to autonomous vehicles. As the technology continues to advance, the integration of Lidar into everyday applications is becoming more seamless, enhancing our ability to monitor and manage complex systems. The growing demand for such devices underscores their critical role in driving innovation and efficiency across multiple sectors.

Regionally, North America is expected to dominate the Mapping Lidar Laser market due to the early adoption of advanced technologies and significant investments in infrastructure projects. The presence of major Lidar system manufacturers and the increasing use of Lidar in autonomous vehicles and environmental monitoring are driving the market in this region. Meanwhile, the Asia Pacific region is projected to witness the highest growth rate due to rapid urbanization, infrastructure development, and the adoption of smart city initiatives by countries such as China and India.

Component Analysis

The Mapping Lidar Laser market by component is segmented into hardware, software, and services. The hardware segment includes Lidar sensors, GPS systems, and IMUs (Inertial Measurement Units). This segment currently holds the largest market share due to the essential role of hardware components in Lidar systems. Continuous innovations in sensor technology, such as the development of solid-state Lidar, are enhancing the performance and reducing the costs of these systems, thereby driving market growth.

Software components are also crucial for the efficient processing and analysis of Lidar data. This segment is expected to grow significantly due to the increasing need for sophisticated data processing algorithms and visualization tools. Software advancements are enabling more accurate and faster data interpretation, which is essential for applications like urban planning and environme

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.

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...

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...

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.

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