We developed an algorithm that was designed to create a spatial database of a forested transportation network using aerial LiDAR. The algorithm uses two main attributes, LiDAR intensity values and ground return density. The road extraction process was developed using aerial LiDAR from McDonald-Dunn Research Forest near Corvallis, Oregon, U.S.A. The road extraction process requires X, Y, Z coordinates, intensity values, canopy type, and the maximum road grade. To compare the results of the process, nine road segments were field surveyed with terrestrial LiDAR. The result of the road extraction process resulted in 80% true positives, 34% false positives, 20% false negatives, and 38% true negatives in identifying forest roads. The average absolute value difference in the road width between the two data sets were 1.1m, while the cut/fill slope differences were minimal (> 4%) and the difference in road cross slope was two percent. These results were comparable with other published studies that examined differences between LiDAR measurements and field measurements.

Raw project data is available by contacting ctemps@unr.edu

This dataset is part of the larger data collection, “Aerial imagery object identification dataset for building and road detection, and building height estimation”, linked to in the references below and can be accessed here: https://dx.doi.org/10.6084/m9.figshare.c.3290519. For a full description of the data, please see the metadata: https://dx.doi.org/10.6084/m9.figshare.3504413.

Imagery data from the United States Geological Survey (USGS); building and road shapefiles are from OpenStreetMaps (OSM) (these OSM data are made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/); and the Lidar data are from U.S. National Oceanic and Atmospheric Administration (NOAA), the Texas Natural Resources Information System (TNRIS).

The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980-1986 and 2004-2008. During 2022, U.S. Army Corps of Engineers contracted the acquisitions of airborne lidar surveys of Mount St. Helens crater and two primary drainages–upper North Fork Toutle River and South Fork Toutle River with GeoTerra, Inc. The U.S. Geological Survey generated a terrain dataset from the classified point cloud with supplied breaklines and modified lake hydro-flattening, then exported a single digital elevation model (DEM) of the ground surface (that is, 'bare earth'), including beneath forest cover. This USGS data release contains digital elevation and shaded relief data as 3-foot resolution raster datasets (2022dem.tif and 2022demhs.tif, respectively). This DEM can support a variety of earth science investigations.

Lidar-derived elevation data for Thane Road, Southeast Alaska, collected September 6, 2019, Raw Data File 2024-16, provides aerial lidar-derived classified point cloud data, a digital surface model (DSM), a digital terrain model (DTM), and an intensity model of Mount Roberts and Gastineau Peak along Thane Road, Southeast Alaska. The survey provides snow-free surface elevations for deriving snow depth distribution models with repeat surveys during snow-covered conditions. Ground control data were collected on September 5, 2019, and aerial lidar data were collected on September 6, 2019, and subsequently merged and processed using a suite of geospatial processing software. This data collection is released as a Raw Data File with an open end-user license. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/31278).

Pavement LiDAR Mapping Market Outlook

According to our latest research, the global pavement LiDAR mapping market size reached USD 1.48 billion in 2024, demonstrating robust momentum driven by infrastructure modernization and digital transformation in road asset management. The market is projected to grow at a CAGR of 12.7% from 2025 to 2033, reaching an estimated value of USD 4.36 billion by 2033. This dynamic growth is attributed to the increasing adoption of LiDAR technologies for accurate, rapid, and cost-effective pavement assessment and management, as governments and private stakeholders prioritize road safety, longevity, and efficient maintenance planning.

One of the primary growth factors for the pavement LiDAR mapping market is the urgent global need for advanced road infrastructure monitoring and maintenance. Traditional pavement inspection methods are labor-intensive, time-consuming, and often lack the precision required for modern asset management. LiDAR-based solutions offer high-resolution, three-dimensional data capture, enabling stakeholders to detect surface irregularities, cracks, rutting, and other pavement distresses with unparalleled accuracy. The ability to conduct rapid, non-intrusive surveys over large road networks significantly reduces operational costs and downtime, making LiDAR an increasingly favored technology among transportation agencies and construction firms. Furthermore, the integration of LiDAR data with GIS and other digital asset management platforms facilitates comprehensive lifecycle analysis and predictive maintenance, further driving market adoption.

The surge in smart city initiatives and the global push for digital transformation in public infrastructure are also major contributors to market growth. Governments across North America, Europe, and Asia Pacific are investing heavily in the digitization of transportation assets to improve safety, optimize maintenance budgets, and enhance urban mobility. The deployment of LiDAR mapping technologies supports these objectives by providing actionable insights for road condition assessment, construction planning, and real-time asset tracking. Additionally, the rise of autonomous vehicles and connected transportation systems is creating new demand for highly detailed and up-to-date pavement data, positioning LiDAR mapping as a foundational technology for next-generation mobility solutions. As regulatory standards for road quality and safety become more stringent, the market is expected to witness sustained demand from both public and private sectors.

Another significant growth driver is the rapid technological advancement and cost reduction in LiDAR hardware and software. Modern LiDAR systems are now more compact, energy-efficient, and capable of capturing data at higher speeds and resolutions than ever before. The proliferation of mobile and aerial LiDAR platforms has expanded the range of applications, enabling efficient mapping of diverse environments, from urban expressways to rural and mountainous roads. Software advancements, particularly in machine learning and artificial intelligence, have further enhanced the ability to process, analyze, and visualize complex LiDAR datasets, delivering actionable intelligence for pavement management. As industry players continue to innovate and introduce scalable, user-friendly solutions, the adoption barrier for LiDAR mapping technologies is expected to diminish, catalyzing further market expansion.

From a regional perspective, North America currently dominates the pavement LiDAR mapping market, accounting for over 38% of the global revenue in 2024. This leadership is driven by substantial investments in infrastructure renewal, stringent road safety regulations, and the early adoption of digital asset management practices. Europe follows closely, benefiting from well-established transportation networks and robust funding for smart mobility projects. Meanwhile, the Asia Pacific region is emerging as the fastest-growing market, fueled by rapid urbanization, increasing government spending on road development, and rising awareness of the benefits of LiDAR-based mapping. Latin America and the Middle East & Africa are also witnessing steady growth, albeit from a smaller base, as these regions gradually modernize their transportation infrastructure and embrace digital surveying technologies.

Under this task order, Precision Aerial Reconnaissance, LLC was contracted to provide acquisition and processing of airborne Lidar over St. Charles Parish, Louisiana. Airborne Lidar was captured to provide digital elevation models, lidar intensity imagery and contours for the project area. The NOAA Office for Coastal Management received the data for processing to the Digital Coast. This metadat...

Images were collected using a remotely piloted unoccupied aerial system (UAS) over the bluffs of the eastern shore of Lake Michigan in St. Joseph rural residential area, Berrien County, MI. Images were collected in two separate surveys conducted on July 8, 2019, and July 13, 2021, using a DJI Phantom 3 and 4 PRO commercial UAS respectively operated by the University of Toledo. The images cover an extent between the intersection of Lakeshore Dr. with Lakeshore Road to the north, and South Lakeshore Dr. to the south. The purpose of the survey was to monitor active bluff erosion in the area. The images are presented here in zipped files grouped by type of collection, nadir and oblique. The images were collected in JPG format and include Exif metadata with GPS date, time, longitude and latitude, and other fields. These files were used in structure-from-motion (SfM) processing to obtain georeferenced 3D point data. The 3D derived data are in open source compressed lidar data exchange laz format and were created from the collected images using SfM photogrammetry software. A description of the laz format and links to software tools for using laz files are provided at the USGS website: https://www.usgs.gov/news/3d-elevation-program-distributing-lidar-data-laz-format.The point cloud was not classified.

La Soufrière Volcano is a 1,220 m high stratovolcano that occupies the northern half of the island of St. Vincent, Lesser Antilles, Eastern Caribbean. It has a long history of explosive and sometimes devastating eruptions. Beginning in December 2020 and ending in April 2021, La Soufrière Volcano produced a Volcano Explosivity Index (VEI) 4 eruption that greatly impacted the landscape, communities, and infrastructure on the island of St. Vincent. The eruption produced intense ash plumes, heavy ashfall, and pyroclastic flows down several river valleys. During and following the eruption, destructive lahars (volcanic mudflows) impacted rivers valleys and coastal communities for months. The USGS-USAID Volcano Disaster Assistance Program (VDAP) provided remote assistance to our partners at the University of the West Indies Seismic Research Center (UWI-SRC) throughout the eruption, predominantly through satellite remote sensing observations. Following the eruption, VDAP contracted the ac ...

The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980-1986 and 2004-2008. Nearly four decades after the emplacement of the 1980 debris avalanche, high sediment production persists in the North Fork Toutle River basin, which drains the northern flank of the volcano. This high sediment production poses a risk of flooding to downstream communities along the Toutle and Cowlitz Rivers and of clogging the shipping channel of the Columbia River. Consequently, U.S. Army Corps of Engineers (USACE), under the direction of Congress, built a sediment retention structure on the North Fork Toutle River in 1989 to maintain an authorized level of flood protection. During 2006, 2010, 2011, 2012, 2013, and 2014, USACE contracted the acquisitions of six high-precision airborne lidar surveys of upper North Fork Toutle River valley near Mount St. Helens. All surveys used near infrared lasers except the 2014 topobathymetric lidar survey which used a green laser scanner. The U.S. Geological Survey (USGS) used classified returns and breaklines from these surveys to produce digital elevation models (DEMs) of the ground surface for each dataset, including beneath forest cover and shallow water surfaces. This USGS data release contains digital elevation data as a 3-foot resolution raster datasets (.tif files). This DEM can be used to develop sediment budgets and models of sediment erosion, transport, and deposition.

This dataset is part of the larger data collection, “Aerial imagery object identification dataset for building and road detection, and building height estimation”, linked to in the references below and can be accessed here: https://dx.doi.org/10.6084/m9.figshare.c.3290519. For a full description of the data, please see the metadata: https://dx.doi.org/10.6084/m9.figshare.3504413.

Imagery data from the United States Geological Survey (USGS); building and road shapefiles are from OpenStreetMaps (OSM) (these OSM data are made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/); and the Lidar data are from U.S. National Oceanic and Atmospheric Administration (NOAA), the Texas Natural Resources Information System (TNRIS).

The aerial laser scanning (ALS) dataset, acquired on 7 April 2009, covers two seperate areas along the track leading to St Elie in French Guiana. The northern plot has an area of 4.5 sq.km. This area covers the 100 hectares IRD-biodiversity plot. The southern area (1.4 sq.km) covers a grove of Spirotropis longifolia. The Lidar data was acquired as part of the Guyafor project. It was shared with the ESA Tropisar project and the Biomass project at Jet Propulsion Laboratory (JPL).

LiDAR Mapping Services Market Outlook

According to our latest research, the global LiDAR Mapping Services market size reached USD 2.1 billion in 2024, exhibiting robust growth momentum with a recorded CAGR of 15.2% over the past few years. The market is anticipated to accelerate further, with projections indicating it will attain a value of USD 7.2 billion by 2033, driven by significant advancements in sensor technologies, increased adoption of autonomous vehicles, and expanding applications across diverse industries. The primary growth factor for the LiDAR Mapping Services market is the escalating demand for high-resolution, real-time geospatial data to support infrastructure development, environmental monitoring, and smart city initiatives worldwide.

One of the most significant growth drivers for the LiDAR Mapping Services market is the rapid technological evolution in LiDAR hardware and software, which has dramatically enhanced the accuracy, efficiency, and affordability of mapping solutions. Modern LiDAR systems now offer higher point cloud density, improved range, and real-time data processing capabilities, making them indispensable for applications requiring detailed topographical information. The integration of LiDAR with advanced analytics and AI-powered platforms enables automated data interpretation, supporting industries such as civil engineering, mining, and urban planning in making informed decisions. The growing prevalence of digital transformation across sectors further fuels the adoption of LiDAR mapping services, as organizations increasingly leverage geospatial intelligence to optimize operations and mitigate risks.

Another compelling factor contributing to the market’s expansion is the surge in investments by both public and private sectors in infrastructure and transportation projects. Governments worldwide are prioritizing the modernization of roadways, railways, and utilities, necessitating precise mapping and surveying solutions. The proliferation of autonomous vehicles and advanced driver-assistance systems (ADAS) also significantly boosts demand, as LiDAR technology is critical for real-time environment sensing and navigation. Additionally, the increased frequency of natural disasters and the need for efficient disaster management have led to a greater reliance on LiDAR mapping for rapid assessment and recovery planning. This multifaceted demand landscape ensures sustained growth for service providers, fostering continuous innovation and service diversification.

Environmental monitoring and land management represent another major avenue of growth for the LiDAR Mapping Services market. The ability of LiDAR to penetrate dense vegetation and deliver accurate elevation models has revolutionized forestry management, flood risk assessment, and habitat mapping. Environmental agencies and research institutions are increasingly employing LiDAR to monitor changes in land use, track deforestation, and support conservation efforts. The technology’s utility in detecting subtle shifts in terrain and vegetation health is unparalleled, making it an essential tool for sustainable development initiatives. As climate change concerns intensify, the adoption of LiDAR mapping for environmental monitoring is expected to witness a significant uptrend, further propelling market growth.

From a regional perspective, North America continues to dominate the LiDAR Mapping Services market, accounting for the largest revenue share in 2024, followed closely by Europe and the Asia Pacific. The strong presence of leading technology providers, robust infrastructure development, and early adoption of autonomous vehicles contribute to North America’s market leadership. Meanwhile, the Asia Pacific region is experiencing the fastest growth, fueled by rapid urbanization, government investments in smart cities, and expanding applications in agriculture and forestry. Europe’s market is characterized by stringent regulatory standards and a strong focus on environmental sustainability, driving demand for high-precision mapping services. Latin America and the Middle East & Africa are also witnessing increased adoption, albeit at a relatively nascent stage, as governments and private enterprises recognize the benefits of LiDAR technology for infrastructure and resource management.

Service Type Analysis

The LiDAR Mapping Services market is segmented by service type into Aerial LiDAR, Terrestrial LiDAR, Mobile LiDAR, and UAV LiDAR, each catering to distinct application requirements a

This dataset is part of the larger data collection, “Aerial imagery object identification dataset for building and road detection, and building height estimation”, linked to in the references below and can be accessed here: https://dx.doi.org/10.6084/m9.figshare.c.3290519. For a full description of the data, please see the metadata: https://dx.doi.org/10.6084/m9.figshare.3504413.

Imagery data from the United States Geological Survey (USGS); building and road shapefiles are from OpenStreetMaps (OSM) (these OSM data are made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/); and the Lidar data are from U.S. National Oceanic and Atmospheric Administration (NOAA), the Texas Natural Resources Information System (TNRIS).

This dataset is part of the larger data collection, “Aerial imagery object identification dataset for building and road detection, and building height estimation”, linked to in the references below and can be accessed here: https://dx.doi.org/10.6084/m9.figshare.c.3290519. For a full description of the data, please see the metadata: https://dx.doi.org/10.6084/m9.figshare.3504413.

Imagery data from the United States Geological Survey (USGS); building and road shapefiles are from OpenStreetMaps (OSM) (these OSM data are made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/); and the Lidar data are from U.S. National Oceanic and Atmospheric Administration (NOAA), the Texas Natural Resources Information System (TNRIS).

LiDAR Corridor Mapping for Roads Market Outlook

According to our latest research, the Global LiDAR Corridor Mapping for Roads market size was valued at $1.7 billion in 2024 and is projected to reach $5.6 billion by 2033, expanding at a CAGR of 13.7% during 2024–2033. The primary growth driver for this market is the rapid adoption of advanced geospatial technologies by government agencies and private sector stakeholders to enhance infrastructure development, road safety, and asset management. With increasing investments in smart transportation and urban mobility projects, the demand for high-precision, real-time mapping solutions such as LiDAR corridor mapping for roads is surging globally. This technology’s ability to provide accurate, detailed, and actionable insights for road planning, construction monitoring, and asset management is revolutionizing how transportation networks are designed, maintained, and optimized.

Regional Outlook

North America holds the largest share of the LiDAR Corridor Mapping for Roads market, accounting for over 36% of the global revenue in 2024. This dominance is primarily attributed to the region’s mature infrastructure, early adoption of cutting-edge geospatial technologies, and the presence of leading LiDAR solution providers. The United States and Canada have been at the forefront of integrating LiDAR systems into large-scale highway mapping and infrastructure modernization projects, supported by robust government funding and favorable regulatory frameworks. The region also benefits from a highly skilled workforce and a strong ecosystem of engineering and technology firms, which accelerates innovation and deployment. Additionally, the push for autonomous vehicles and smart city initiatives further propels the demand for high-precision corridor mapping solutions in North America.

The Asia Pacific region is projected to be the fastest-growing market for LiDAR Corridor Mapping for Roads with a remarkable CAGR of 16.2% during the forecast period. This growth is driven by massive infrastructure development programs in countries like China, India, and Japan, where governments are investing heavily in modernizing transportation networks and urban corridors. The increasing adoption of UAV-based LiDAR and mobile mapping technologies is enabling cost-effective and efficient road mapping over vast and complex terrains. Strategic collaborations between local engineering firms and global LiDAR technology providers are also accelerating market penetration. Furthermore, rising urbanization, population growth, and government mandates for road safety and asset management are fueling demand for advanced LiDAR solutions across the region.

Emerging economies in Latin America and Middle East & Africa are gradually embracing LiDAR corridor mapping for roads, although adoption remains at a nascent stage due to budgetary constraints and limited technical expertise. These regions face unique challenges such as inconsistent regulatory policies, fragmented infrastructure, and a lack of standardized data formats, which hinder large-scale deployment. However, as international development agencies and technology vendors increase their focus on these markets, there is a growing awareness of the benefits of LiDAR-based mapping for road planning, construction monitoring, and asset management. Localized pilot projects and government-backed smart infrastructure programs are expected to drive incremental adoption in the coming years, provided that capacity-building and training initiatives are implemented effectively.

Report Scope

This data set contains topographic and bathymetric lidar data that were collected on April 21, 23, 30, May 2, and June 14, 17 of 2003, cooperatively by the U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), and National Park Service (NPS). The data is for part of the U.S. Virgin Islands (island of St. John and a portion of the northern coastline of St. Croix)....

Lidar is a remote sensing technique that uses laser light to detect, range, or identify remote objects based on light reflected by the object or emitted through its subsequent fluorescence. Airborne ranging lidar is now being applied in coastal environments to produce accurate, cost-efficient elevation datasets with high spatial density. The USGS, in cooperation with NASA and NPS, is using airborne lidar to measure the submerged topography of the Northern Florida Keys Reef Tract (NFKRT); secondarily, the data will be assessed for its potential in terms of benthic characterization. Elevation measurements were collected over the NFKRT using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure subaerial and submarine topography. The system uses a high frequency laser beam directed at the earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The EAARL system, developed by the NASA Wallops Flight Facility (WFF) in Virginia, measures ground elevation with a vertical resolution of roughly 15 centimeters. A sampling rate of up to 3 kHz results in an extremely dense spatial elevation data set. The EAARL system is typically flown at 300 m altitude AGL, resulting in a 240 m swath for each flightline. Data collection occurred with approximately 50% overlap between flightlines, resulting in about one laser sounding per square meter. The data were processed by the USGS, Florida Integrated Science Center (FISC] St. Petersburg office to produce 1 meter resolution raster images that can be easily ingested into a Geographic Information System (GIS). The data were organized as 2 km by 2 km data tiles in 32 bit floating-point integer GeoTIFF format.

For more information on Lidar science and the Experimental Advanced Airborne Research Lidar (EAARL) system and surveys, see http://ngom.usgs.gov/dsp/overview/index.php and http://ngom.usgs.gov/dsp/tech/eaarl/index.php .

LiDAR (Light Detection and Ranging) data of the City of Vancouver and UBC Endowment Lands with an Area of Interest (AOI) covering a total of 134 square kilometers.​Data products includes a classification that defines "bare earth" ground surface, water and of the upper most surface defined by vegetation cover, buildings and other structures.Data accessEach of the 181 polygons on the map or rows in the table provides corresponding link to the data in LAS format (zipped, file sizes range from 16.45MB to 2.74GB).AttributesPoint data was classified as:Unclassified;Bare-earth and low grass;Low vegetation (height <2m);High vegetation (height >2m);Water;Buildings;Other; andNoise (noise points, blunders, outliners, etc) Note​The 2022 LiDAR data is being utilized for initiatives including land management, planning, hazard assessment, (e.g. floods, landslides, lava flows, and tsunamis), urban forestry, storm drainage, and watershed analysis. Data currency​Aerial LiDAR was acquired on September 7th and September 9th, 2022 and is current as of those dates. Data accuracyThe LiDAR data is positioned with a mean density of approximately 49 points per square metreSidelap: minimum of 60% in north-south and east-west directionsVertical accuracy: 0.081 metre (95% confidence level)Coordinate system​The map of grid cells on this portal is in WGS 84 but the LiDAR data in the LAS files are in the following coordinate system:Projection: UTM Zone 10 (Central Meridian 123 West)Hz Datum: NAD 83 (CSRS) 4.0.0.BC.1.GVRDVertical Datum: CGVD28GVRDMetro Vancouver Geoid (HTMVBC00_Abbbyn.zip) Websites for further information City boundary dataset

The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980-1986 and 2004-2008. During 2017, U.S. Forest Service contracted the acquisitions of airborne lidar surveys of Mount St. Helens and upper North Fork Toutle River basin, part of a larger 2017-2018 survey of the Gifford Pinchot National Forest. The U.S. Geological Survey combined and reprojected 81 raster datasets, provided by the U.S. Forest Service in October 2018, into a single digital elevation model (DEM) of the ground surface, including beneath forest cover (that is, 'bare earth'). This USGS data release contains digital elevation data as a 1-meter resolution raster dataset (.tif file). This DEM can support a variety of earth science investigations.

Airborne terrestrial LiDAR was collected for St. Johns County, FL. System Parameters/Flight Plan. The LiDAR system acquisition parameters were developed based on a maximum average ground sample distance of 2.1 feet. A Leica ALS50 LiDAR sensor was used for acquisition. Acquisition specifications for the sensor follows: Field of View (full angle) - 24 degrees, Nominal flight altitude (AGL) - 3000 feet, Airspeed - 130 mph (113 knots), Laser pulse rate - 100,000 Hz, Nominal swath width (on ground) - 1275 feet, Maximum cross track point spacing - 2.07 feet, Maximum along track point spacing - 4.30 feet, Average point spacing - 1.67 feet, Flight line spacing - 970.47 feet, Side overlap - 23.91 percent. LiDAR System Calibration. Prior to the LiDAR acquisition, the system underwent a calibration to verify the operational accuracy and misalignment angles. Boresight calibrations were performed for the LiDAR system at the beginning and end of each flight mission. LiDAR Data Acquisition. LiDAR data acquisition only occurred when the sky was sufficiently clear of clouds, smoke, and atmospheric haze. The LiDAR data was processed immediately after the acquisition to verify the coverage had no voids. GPS/Inertial Measurement Unit (IMU) Post Processing. The GPS and IMU data was post processed using differential and kalman filter algorithms to derive a best estimate of trajectory. The quality of the solution was verified to be consistent with the accuracy requirements of the project. LiDAR Processing and Classification. The LiDAR data was post processed and verified to be consistent with the project requirements in terms of post spacing and absence of artifacts. The point cloud underwent classification to determine bare-earth points (class 2), noise points (class 7), water returns (class 9), and unclassified data (class 1). Class 12 contains LiDAR points removed from the overlap region between adjacent flight lines.