The Point Cloud LiDAR Data Processing Software market is experiencing robust growth, driven by the increasing adoption of LiDAR technology across various sectors. The surge in demand for accurate 3D spatial data in applications like autonomous vehicles, precision agriculture, infrastructure management, and urban planning is fueling market expansion. Technological advancements, including the development of sophisticated algorithms for point cloud processing and the integration of AI and machine learning capabilities, are enhancing the efficiency and accuracy of these software solutions. The market is segmented by software type (e.g., point cloud editing, registration, classification, and modeling software), deployment mode (cloud-based and on-premise), and end-user industry. While competition is intense among established players like Trimble, Bentley Systems, Leica Geosystems, Autodesk, and FARO, the market also presents opportunities for specialized niche players focusing on specific industry applications or innovative processing techniques. The global market is geographically diverse, with North America and Europe currently holding significant market share due to early adoption and technological advancements. However, rapid growth is anticipated in Asia-Pacific and other emerging regions driven by infrastructure development and increasing government investments in digitalization initiatives. The forecast period (2025-2033) projects sustained growth, potentially exceeding a Compound Annual Growth Rate (CAGR) of 15%, reflecting the continued integration of LiDAR data processing into mainstream workflows. Challenges remain, including the high cost of LiDAR data acquisition and processing, the complexity of software solutions, and the need for skilled professionals to operate and interpret the results. Nevertheless, ongoing innovation and the increasing affordability of LiDAR technology are mitigating these challenges, contributing to the market's positive outlook. The competitive landscape is dynamic, with both established players and new entrants continually seeking to improve software features, expand their market reach, and enhance customer support. Strategic partnerships and acquisitions are expected to play a significant role in shaping the market's future trajectory.

The market is segmented into the following types and applications: Report Coverage & Deliverables Market Segmentations: Type:

Point Cloud Processing Software GIS Integration Software Others

Application:

Land Surveying and Mapping Urban Planning and Design Environmental Monitoring Water Resources Management Others

Regional Insights:

North America: Largest market due to high adoption in construction and infrastructure projects Europe: Growing demand for environmental monitoring and urban planning Asia-Pacific: Rapid urbanization and increasing investments in infrastructure Rest of the World: Emerging markets with potential for growth

Lidar Data Processing Software Trends Driving Forces:

Increasing adoption of lidar technology in various industries Growing need for accurate and detailed data for decision-making Advancements in cloud computing and artificial intelligence

Challenges and Restraints:

High cost of lidar data collection and processing Limited availability of skilled professionals Data storage and management challenges

Emerging Trends:

Integration of lidar data with other data sources Real-time data processing and visualization Automated workflows and machine learning

Growth Catalysts:

Government initiatives to promote lidar technology Increasing awareness of the benefits of lidar data Collaboration between industry players

Leading Players in the Lidar Data Processing Software

Trimble: Faro Technologies: ESRI: L3Harris Geospatial: Leica Geosystems: Autodesk: PointCloud International: Beijing Yupont Electric Power Technology Co., Ltd.: Blue Marble Geographics: Terrasolid: Beijing Green Valley Technology Co., Ltd: RIEGL Laser Measurement Systems: QCoherent Software: TopoDOT: Merrick & Company: Teledyne Optech: RiAcquisition: RIEGL Software: SLAMTEC: LizarTech:

Significant Developments in Lidar Data Processing Software Sector

Partnerships between software providers and lidar sensor manufacturers Investment in research and development to enhance software capabilities Growing adoption of cloud-based solutions for data storage and processing

Market Analysis for Point Cloud LiDAR Data Processing Software The global point cloud LiDAR data processing software market is projected to reach USD 1,666.7 million by 2033, exhibiting a CAGR of 15.9% from 2025 to 2033. The increasing adoption of LiDAR technology in architecture, land surveying, and other industries, coupled with advancements in artificial intelligence (AI) and machine learning (ML) algorithms for data processing, are driving the market growth. The need for accurate and detailed 3D representations of physical spaces and the benefits of LiDAR in generating point clouds for precise modeling and visualization are further fueling market expansion. Key market trends include the adoption of cloud-based solutions, which offer flexibility, scalability, and reduced infrastructure costs. The integration of AI and ML in data processing is automating tasks, enhancing accuracy, and improving efficiency. Moreover, the growing demand for smart city initiatives and infrastructure development is creating new opportunities for the use of point cloud LiDAR data processing software in urban planning, asset management, and transportation systems. Companies in the market include Trimble, Bentley Systems, Leica Geosystems AG, Autodesk, and FARO, who are investing in research and development to provide innovative solutions that meet the evolving needs of their customers.

Light Detection and Ranging (lidar) is a technology used to create high-resolution models of ground elevation with a vertical accuracy of 10 centimeters (4 inches).  rnrnFEMA collects lidar elevation data to support flood mapping. USGS is the primary Federal steward of lidar data. FEMA archives lidar data for FEMA projects where USGS does not manage the Lidar data collection. rnrnDatapoints include ground elevation models and vertical metrics for ground elevation.

Many different partners and groups, and several Center-led data projects, have contributed to the lidar data collection housed and distributed by the NOAA Office for Coastal Management. The data span more than two decades and were collected using many different sensors. The collection includes data from topographic and bathymetric lidar sensors. Data are available for all of the coastal states...

OCM plans to collect lidar data to support coastal zone management activities. Projects could take place anywhere within US coastal zone.

Access collections of data that contain a mix of LIDAR point clouds, derived elevation models, imagery and vector building footprints for major US Cities

These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the Sea Level Rise and Coastal Flooding Impacts Viewer. It depicts potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at sea level rise and coastal flooding impacts. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The Sea Level Rise and Coastal Flooding Impacts Viewer may be accessed at: https://coast.noaa.gov/slr. This metadata record describes the Puerto Rico digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer described above. This DEM includes the best available lidar known to exist at the time of DEM creation that met project specifications. This DEM data includes St. Croix, St. Thomas and St. John. The DEM was produced from the following lidar data sets: 1. 2018 USGS Lidar DEM: Post Hurricane Maria - USVI The DEM is referenced vertically to the Virgin Islands Vertical Datum of 2009 (VIVD09, Geoid12B) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83 2011). The resolution of the DEM is approximately 3 meters.

LiDAR Point Cloud Processing Software Market Outlook

The LiDAR Point Cloud Processing Software market size is projected to grow significantly from an estimated USD 1.2 billion in 2023 to USD 3.8 billion by 2032, with a CAGR of approximately 13.5% during the forecast period. This robust growth is driven by increasing adoption in various sectors including urban planning, environmental monitoring, and disaster management, propelled by the need for advanced spatial data analysis and precise 3D mapping solutions.

One of the primary growth factors for the LiDAR Point Cloud Processing Software market is the escalating demand for high-resolution 3D imaging technology across multiple industries. Urban planning departments, environmental agencies, and construction firms are increasingly relying on LiDAR technology for accurate mapping and analysis, which in turn drives the demand for sophisticated software capable of processing the voluminous point cloud data generated by these systems. The precision and speed offered by these software solutions make them indispensable tools in modern data acquisition and analysis workflows.

Another pivotal driver is the rising investments in smart city projects globally. Governments and private entities are investing heavily in the development of smart infrastructure, which necessitates the integration of advanced geospatial data analytics. LiDAR technology, with its ability to deliver detailed 3D representations, plays a crucial role in these projects. The software that processes this data is critical for the implementation and success of these initiatives, fueling the marketÂ’s growth further.

Technological advancements and innovation in LiDAR systems, including improvements in sensor accuracy and reductions in equipment costs, are also contributing to market expansion. As LiDAR systems become more affordable and accessible, smaller enterprises and new application areas are adopting this technology, thereby increasing the demand for effective point cloud processing software. The integration of artificial intelligence and machine learning algorithms into these software solutions is another trend that enhances data processing capabilities, enabling more efficient and insightful analysis.

From a regional perspective, North America currently holds the largest market share due to the early adoption of LiDAR technology and substantial investments in infrastructure development and environmental monitoring. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, driven by rapid urbanization, industrialization, and extensive government initiatives for smart city development. Europe remains a significant market as well, with growing applications in construction and transportation sectors.

The evolution of LiDAR technology has seen the development of Multi Line LiDAR systems, which offer enhanced data capture capabilities compared to traditional single-line systems. These advanced systems utilize multiple laser beams to scan and capture data simultaneously, significantly increasing the density and accuracy of the point cloud data. This makes Multi Line LiDAR particularly advantageous in applications requiring high-resolution mapping and detailed analysis, such as urban planning and environmental monitoring. The ability to capture more data in less time not only improves efficiency but also provides richer datasets for more comprehensive analysis. As industries continue to demand more precise and reliable data, the adoption of Multi Line LiDAR systems is expected to grow, further driving the need for sophisticated processing software capable of handling these complex datasets.

Component Analysis

The LiDAR Point Cloud Processing Software market is segmented by component into software and services. The software segment is expected to dominate the market throughout the forecast period. This is due to the increasing deployment of advanced software solutions that can handle large volumes of data generated by LiDAR systems. These software solutions are essential for converting raw point cloud data into usable formats, conducting analysis, and providing actionable insights. This segment is seeing rapid innovation, with new features and functionalities continually being added to enhance performance and usability.

The services segment, while smaller in comparison to software, is also poised for substantial growth. Services include consulti

This layer contains the DEM for LiDAR data in the Northland region, captured between 18 April 2024 – 28 June 2024

The DSM is available as layer Northland LiDAR 1m DSM (2024).

The Index Tiles are available as layer Northland LiDAR Index Tiles (2024).

The LAS Point Cloud is available as layer Northland LiDAR Point Cloud (2024).

LiDAR was captured for Regional Software Holdings Ltd by Landpro Ltd from 18 April to 28 June 2024. The dataset was generated by Landpro and their subcontractors. Data management and distribution is by Toitū Te Whenua Land Information New Zealand. Data comprises:

DEM: tif or asc tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout

DSM: tif or asc tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout

Point cloud: las tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout

Pulse density specification is at a minimum of 8 pulses/square metre.

Vertical Accuracy Specification is +/- 0.2m (95%) Horizontal Accuracy Specification is +/- 1.0m (95%)

Vertical datum is NZVD2016.

LiDAR in Mapping Market Outlook

The global LiDAR in Mapping market size is projected to grow from USD 1.2 billion in 2023 to USD 3.8 billion by 2032, reflecting a CAGR of 13.3%. This significant growth is driven by the increasing demand for precise mapping and surveying solutions across various industries. The adoption of LiDAR technology is bolstered by the rapid advancements in sensor technology, the growing need for high-resolution topographic data, and the expanding applications of LiDAR in urban planning, environmental monitoring, and infrastructure development.

The LiDAR technology's remarkable growth is largely due to its unparalleled ability to produce high-resolution, three-dimensional images of the Earth's surface. This capability makes it an indispensable tool in urban planning, where detailed and accurate mapping is crucial for efficient development and management. The rising urbanization and the need for smart city planning are significant factors contributing to the market's expansion. Moreover, the growing awareness about the environmental impact of urban sprawl has led to an increased demand for LiDAR in environmental monitoring and disaster management.

Another crucial growth driver for the LiDAR in Mapping market is the increasing investment in infrastructure development worldwide. Governments and private sector stakeholders are increasingly utilizing LiDAR technology to ensure precision and efficiency in construction projects. This technology not only enhances the accuracy of topographic surveys but also reduces the time and cost associated with traditional surveying methods. As a result, the construction and transportation sectors are witnessing a surge in the adoption of LiDAR solutions.

Furthermore, the integration of LiDAR technology with other advanced technologies such as Geographic Information Systems (GIS) and Artificial Intelligence (AI) is opening new avenues for market growth. These integrations enhance the capabilities of LiDAR systems, making them more versatile and efficient. For instance, the combination of LiDAR with AI enables real-time data processing and analysis, which is particularly useful in disaster management scenarios. This technological synergy is expected to drive the market's growth throughout the forecast period.

Regionally, North America dominates the LiDAR in Mapping market due to the early adoption of advanced technologies and significant government investments in infrastructure projects. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. The rapid urbanization, increasing infrastructure development, and supportive government initiatives in countries like China and India are key factors driving the market growth in this region.

Component Analysis

In the LiDAR in Mapping market, components are broadly categorized into Hardware, Software, and Services. Each of these components plays a crucial role in the overall functionality and efficiency of LiDAR systems. Hardware comprises the LiDAR sensors and other physical components necessary for data collection. The continuous advancements in sensor technology, such as the development of compact and lightweight LiDAR sensors, are driving the growth of this segment. These innovations are making it easier to deploy LiDAR systems in various applications, from terrestrial to airborne mapping.

Software is another critical component in the LiDAR in Mapping market as it is responsible for data processing, analysis, and visualization. The increasing complexity of data collected by LiDAR sensors necessitates sophisticated software solutions capable of handling large datasets efficiently. Advances in software algorithms and the incorporation of AI and machine learning techniques are enhancing the capabilities of LiDAR software, making it more efficient in producing accurate and high-resolution maps. This segment is expected to witness significant growth as software solutions become more advanced and user-friendly.

The Services segment includes various support and maintenance services provided by companies to ensure the optimal functioning of LiDAR systems. These services are essential for the seamless operation of LiDAR technology, as they offer regular updates, troubleshooting, and training for users. The growing adoption of LiDAR technology across different industries is driving the demand for specialized services that can cater to the specific needs of various applications. This, in turn, is contributing to the overall growth of the Services segment.

This data set is comprised of lidar point cloud data. This project required lidar data to be acquired over Horry County, South Carolina. The total area of the Horry County Elevation Data and Imagery AOI is approximately 1092 square miles. Lidar data was collected and processed to meet the requirements of the project task order. The lidar collection was a collaborative effort between two data acquisition firms. While Woolpert was responsible for collection of the majority of the county, the coastal portion of the data was collected by Quantum Geospatial and is detailed in the processing steps of the metadata. 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 task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, four (4) foot pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Ground conditions: Water at normal levels; no unusual inundation; no snow. The bare earth DEMs along the coast may have a variance in the water heights due to temporal differences during the lidar data acquisition and will be represented in DEM as a seam-like anomaly. One coastal elevation was applied to entire project area. Due to differing acquisition dates and thus differing tide levels there will be areas in the DEM exhibiting what appears to be "digging" water features. Sometimes as much as approximately 2.5 feet. This was done to ensure that no coastal hydro feature was "floating" above ground surface. This coastal elevation will also affect connected river features wherein a sudden increase in flow will be observed in the DEM to accommodate the coastal elevation value. During Hydrologic breakline collection, Woolpert excluded obvious above-water piers or pier-like structures from the breakline placement. Some features extend beyond the apparent coastline and are constructed in a manner that can be considered an extension of the ground. These features were treated as ground during classification and subsequent hydrologic delineation. In all cases, professional practice was applied to delineate what appeared to be the coast based on data from multiple sources; Due to the many substructures and the complexity of the urban environment, interpolation and apparent "divots" (caused by tinning) may be evident in the surface of the bare earth DEM. In all cases, professional practice was applied to best represent the topography. The data received by the NOAA OCM are topographic data in LAS 1.2 format, classified as unclassified (1), ground (2), all noise (7), water (9), ignored ground (10), overlap unclassified (17), and overlap ground (18). Digital Elevation Models (DEMs) and breakline data are also available. The DEM data are available at: ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid18/data/4814/DEMs/ The breakline data are available at: ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid18/data/4814/breaklines Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office of Coastal Management (OCM)or its partners. Original contact information: Contact Org: Woolpert Phone: (937) 461-5660

Lidar Technology in Mapping Market Outlook

The global Lidar Technology in Mapping market size was valued at approximately USD 1.6 billion in 2023 and is expected to reach USD 5.3 billion by 2032, growing at a robust CAGR of 14.2% during the forecast period. The major growth factors driving this market include the rapidly increasing demand for high-resolution topographic and spatial data, advancements in Lidar technology, and its expanding application across various industries such as transportation, urban planning, and forestry.

One of the primary growth factors for the Lidar Technology in Mapping market is the increasing demand for high-resolution maps and spatial data, which are essential for a wide range of applications including environmental monitoring, urban planning, and disaster management. High-resolution Lidar data enables precise mapping of terrain features and land cover, facilitating better decision-making processes. As urbanization continues to expand globally, the need for accurate and detailed maps has become more crucial, driving the growth of this market.

Technological advancements in Lidar systems have significantly contributed to the market's growth. Modern Lidar systems are now more compact, efficient, and capable of capturing data at higher resolutions than ever before. Innovations such as solid-state Lidar and the integration of Lidar with advanced imaging technologies like hyperspectral and multispectral cameras have enhanced the capabilities of Lidar systems. These advancements have broadened the scope of Lidar applications, making it an indispensable tool in various fields including forestry, archaeology, and civil engineering.

Another significant growth driver is the expanding application of Lidar technology in autonomous vehicles and drones. Lidar is a crucial component in the navigation systems of autonomous vehicles, providing accurate and real-time 3D mapping of the environment. Similarly, the use of drones equipped with Lidar sensors for aerial surveys and inspections has gained popularity, offering a cost-effective and efficient solution for mapping large and inaccessible areas. This growing adoption of Lidar technology in emerging applications is expected to further fuel the market's growth.

The regional outlook for the Lidar Technology in Mapping market shows significant growth potential across various regions, with North America and Asia Pacific leading the way. North America, particularly the United States, has been a major market due to the early adoption of advanced technologies and substantial investments in infrastructure development and environmental monitoring. Meanwhile, the Asia Pacific region is expected to witness the highest growth rate, driven by rapid urbanization, infrastructure projects, and increasing government initiatives for smart city development. Europe also holds a substantial market share, supported by the presence of key market players and extensive research activities in Lidar technology.

Component Analysis

The Lidar Technology in Mapping market can be segmented by component into hardware, software, and services. Each of these components plays a crucial role in the overall functionality and effectiveness of Lidar systems. The hardware segment includes Lidar sensors, GPS receivers, IMUs, and other related components. The software segment comprises data processing and analysis tools that convert raw Lidar data into useful information. The services segment includes installation, maintenance, and consulting services that support the deployment and operation of Lidar systems.

In the hardware segment, Lidar sensors are the most critical component, responsible for emitting laser pulses and measuring the time it takes for them to return after hitting an object. Recent advancements in sensor technology have led to the development of more compact and efficient sensors, capable of capturing high-resolution data at longer ranges. These innovations have not only improved the accuracy and reliability of Lidar systems but also reduced their size and cost, making them more accessible for various applications.

The software segment is equally important, as it involves the processing and analysis of raw Lidar data to generate detailed maps and models. Advanced software tools offer features such as point cloud processing, terrain modeling, and feature extraction, enabling users to derive actiona

These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the NOAA Lake Level Viewer. It depicts potential lake level rise and fall and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at lake level change, coastal flooding impacts, and exposed lakeshore. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The NOAA Lake Level Viewer may be accessed at: https://coast.noaa.gov/llv. This metadata record describes the Lake Erie digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Lake Level Viewer described above. This DEM includes the best available lidar and US Army Corps of Engineer dredge survey data known to exist at the time of DEM creation that met project specifications. This DEM includes data for Monroe and Wayne Counties in Michigan; Chautauqua and Erie Counties in New York; Ashtabula, Cuyahoga, Erie, Lake, Lorain, Lucas, Ottawa, Sandusky, and Wood Counties in Ohio; and Erie County in Pennsylvania. The DEM was produced from the following lidar data sets: 1. 2011 - 2012 USACE NCMP Topobathy Lidar: Lake Erie (MI, NY, OH, PA) 2. 2011 USACE NCMP Topobathy Lidar: MI/NY Great Lakes 3. 2008 FEMA Lidar: Erie County, NY 4. 2007 USACE NCMP Topobathy Lidar: Lake Erie (Erie County, PA) and Lake Michigan (Manitou Islands) (MI, PA) 5. 2007 USACE NCMP Topobathy Lidar: Lake Erie (NY Shoreline) 6. 2006 USACE NCMP Topobathy Lidar: Lake Erie (OH, PA), Lake Huron (MI) and Lake Michigan (Porter County, IN) 7. 2007 Pennsylvania Department of Conservation and Natural Resources (PA DCNR) Statewide Lidar 8. 2006 Ohio Statewide Imagery Program (OSIP) Lidar: North The DEM was produced from the following sonar data sets: 9. 2015 USACE Detroit District; Detroit River, MI; Livingstone Channel Reach 10. 2015 USACE Buffalo District, Ashtabula Harbor, OH 11. 2015 USACE Buffalo District, Erie Harbor, PA 12. 2015 USACE Buffalo District, Fairport Harbor, OH 13. 2015 USACE Buffalo District, Rocky River, OH 14. 2013 USACE Buffalo District; Buffalo Harbor, NY; Buffalo River and Ship Canal 15. 2014 USACE Detroit District, Point Mouillee, MI 16. 2014 USACE Buffalo District, Conneaut Harbor, OH 17. 2014 USACE Buffalo District, Dunkirk Harbor, NY 18. 2014 USACE Buffalo District, Niagara River, NY 19. 2014 USACE Buffalo District, Sandusky Harbor, OH The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 3 meters.

The NC Emergency Management's Spatial Data Download website. GIS data available includes: flood zones, QL1 and QL2 LiDAR, Digital Elevation Models (DEMs) sourced from the LiDAR, building footprints, and school locations. An NCID or Google login is required - see the website for more details.https://sdd.nc.gov/sdd

LiDAR (Light Detection And Ranging) is a modern survey method that produces three-dimensional spatial information in the form of a data point cloud. LiDAR is an active remote sensing system; it produces its own energy to acquire information, versus passive systems, like cameras, that only receive energy. LiDAR systems are made up of a scanner, which is a laser transmitter and receiver; a GNSS (GPS) receiver; and an inertial navigation system (INS). These instruments are mounted to an aircraft. The laser scanner transmits near-infrared light to the ground. The light reflects off the ground and returns to the scanner. The scanner measures the time interval and intensity of the reflected signals. This information is integrated with the positional information provided by the GNSS and INS to create a three-dimensional point cloud representing the surface. A LiDAR system can record millions of points per second, resulting in high spatial resolution, which allows for differentiation of many fine terrain features. Point clouds collected with LiDAR can be used to create three-dimensional representations of the Earth’s surface, such as Digital Elevation Models (DEMs) and Digital Surface Models (DSMs). DEMs model the elevation of the ground without objects on the surface, and DSMs model ground elevations as well as surface objects such as trees and buildings. LidarBC's Open LiDAR Data Portal (see link under Resources) is an initiative to provide open public access to LiDAR and associated datasets collected by the Government of British Columbia. The data in the portal is released as Open Data under the Open Government Licence – British Columbia (OGL-BC). Four Government of British Columbia business areas and one department of the Government of Canada make LiDAR data available through the portal: * GeoBC * Emergency Management and Climate Readiness (EMCR) * BC Timber Sales (BCTS) * Forest Analysis and Inventory Branch (FAIB) * Natural Resources Canada (NRCan) GeoBC is the provincial branch that oversees and manages LidarBC’s Open LiDAR Data Portal, including storage, distribution, maintenance, and updates. Please direct questions to LiDAR@gov.bc.ca.

Between January and March 2010, lidar data was collected in southeast/coastal Georgia under a multi-agency partnership between the Coastal Georgia Regional Development Center, USGS, FEMA, NOAA and local county governments. Data acquisition is for the full extent of coastal Georgia, approximately 50 miles inland, excluding counties with existing high-resolution lidar derived elevation data. The...

Lidar (light detection and ranging) is a technology that can measure the 3-dimentional location of objects, including the solid earth surface. The data consists of a point cloud of the positions of solid objects that reflected a laser pulse, typically from an airborne platform. In addition to the position, each point may also be attributed by the type of object it reflected from, the intensity of the reflection, and other system dependent metadata. The NOAA Coastal Lidar Data is a collection of lidar projects from many different sources and agencies, geographically focused on the coastal areas of the United States of America. The data is provided in Entwine Point Tiles (EPT; https://entwine.io) format, which is a lossless streamable octree of the point cloud, and in LAZ format. Datasets are maintained in their original projects and care should be taken when merging projects. The coordinate reference system for the data is The NAD83(2011) UTM zone appropriate for the center of each data set for EPT and geographic coordinates for LAZ. Vertically they are in the orthometric datum appropriate for that area (for example, NAVD88 in the mainland United States, PRVD02 in Puerto Rico, or GUVD03 in Guam). The geoid model used is reflected in the data set resource name.
The data are organized under directories entwine and laz for the EPT and LAZ versions respectively. Some datasets are not in EPT format, either because the dataset is already in EPT on the USGS public lidar site, they failed to build or their content does not work well in EPT format. Topobathy lidar datasets using the topobathy domain profile do not translate well to EPT format.

Mapped management areas from the 1997 Forest Plan for the Black Hills National Forest. For more information about each management areas and how they are defined see the 1997 Forest Management Plan Document.

The State of Utah, including the Utah Automated Geographic Reference Center, Utah Geological Survey, and the Utah Division of Emergency Management, along with local and federal partners, including Salt Lake County and local cities, the Federal Emergency Management Agency, the U.S. Geological Survey, and the U.S. Environmental Protection Agency, have funded and collected over 8380 km2 (3236 mi2) of high-resolution (0.5 or 1 meter) Lidar data across the state since 2011, in support of a diverse set of flood mapping, geologic, transportation, infrastructure, solar energy, and vegetation projects. The datasets include point cloud, first return digital surface model (DSM), and bare-earth digital terrain/elevation model (DEM) data, along with appropriate metadata (XML, project tile indexes, and area completion reports). This 0.5-meter 2013-2014 Wasatch Front dataset includes most of the Salt Lake and Utah Valleys (Utah), and the Wasatch (Utah and Idaho), and West Valley fault zones (Utah). Other recently acquired State of Utah data include the 2011 Utah Geological Survey Lidar dataset covering Cedar and Parowan Valleys, the east shore/wetlands of Great Salt Lake, the Hurricane fault zone, the west half of Ogden Valley, North Ogden, and part of the Wasatch Plateau in Utah.