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) Hig ...

Original Data: These files contain topographic lidar elevations generated from data collected using a Teledyne ALTM Galaxy PRIME sensor. Native lidar data is not generally in a format accessible to most Geographic Information Systems (GIS). Specialized in-house and commercial software packages are used to process the native lidar data into 3-dimensional positions that can be imported into GIS s...

A topographic lidar survey was conducted from September 5 to October 11, 2012, for the barrier islands of Alabama, Mississippi and southeast Louisiana, including the coast near Port Fourchon. Most of the data were collected September 5-10, 2012, with a reflight conducted on October 11, 2012, to increase point density in some areas. The data were collected at a nominal pulse space of 1-meter (m) and processed to identify bare earth elevations. Bare earth Digital Elevation Models(DEMs) were generated based on these data. Aero-Metric, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process the lidar data. The bare earth DEMs are 32-bit floating point ERDAS Imagine (IMG) files with a horizontal spatial resolution of 1-m by 1-m. They are projected to UTM zone 15N or 16N NAD83 meters. Their vertical datum is NAVD88 (GEOID12) meters. The DEMs are organized on a 2-kilometer (km) by 2-km tiling scheme that covers the entire survey area. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.

Many Ontario lidar point cloud datasets have been made available for direct download by the Government of Canada through the federal Open Government Portal under the LiDAR Point Clouds – CanElevation Series record. Instructions for bulk data download are available in the Download Instructions document linked from that page. To download individual tiles, zoom in on the map in GeoHub and click a tile for a pop-up containing a download link.

See the LIO Support - Large Data Ordering Instructions to obtain a copy of data for projects that are not yet available for direct download. Data can be requested by project area or a set of tiles. To determine which project contains your area of interest or to view single tiles, zoom in on the map above and click. For bulk tile orders follow the link in the Additional Documentation section below to download the tile index in shapefile format. Data sizes by project area are listed below.

The Ontario Point Cloud (Lidar-Derived) consists of points containing elevation and intensity information derived from returns collected by an airborne topographic lidar sensor. The minimum point cloud classes are Unclassified, Ground, Water, High and Low Noise. The data is structured into non-overlapping 1-km by 1-km tiles in LAZ format.

This dataset is a compilation of lidar data from multiple acquisition projects, as such specifications, parameters, accuracy and sensors may vary by project. Some project have additional classes, such as vegetation and buildings. See the detailed User Guide and contractor metadata reports linked below for additional information, including information about interpreting the index for placement of data orders.

Raster derivatives have been created from the point clouds. These products may meet your needs and are available for direct download. For a representation of bare earth, see the Ontario Digital Terrain Model (Lidar-Derived). For a model representing all surface features, see the Ontario Digital Surface Model (Lidar-Derived).

You can monitor the availability and status of lidar projects on the Ontario Lidar Coverage map on the Ontario Elevation Mapping Program hub page.

Additional Documentation

Ontario Classified Point Cloud (Lidar-Derived) - User Guide (DOCX)

OMAFRA Lidar 2016-18 - Cochrane - Additional Metadata (PDF) OMAFRA Lidar 2016-18 - Peterborough - Additional Metadata (PDF) OMAFRA Lidar 2016-18 - Lake Erie - Additional Metadata (PDF) CLOCA Lidar 2018 - Additional Contractor Metadata (PDF) South Nation Lidar 2018-19 - Additional Contractor Metadata (PDF) OMAFRA Lidar 2022 - Lake Huron - Additional Metadata (PDF) OMAFRA Lidar 2022 - Lake Simcoe - Additional Metadata (PDF) Huron-Georgian Bay Lidar 2022-23 - Additional Metadata (Word) Kawartha Lakes Lidar 2023 - Additional Metadata (Word) Sault Ste Marie Lidar 2023-24 - Additional Metadata (Word) Thunder Bay Lidar 2023-24 - Additional Metadata (Word) Timmins Lidar 2024 - Additional Metadata (Word)

OMAFRA Lidar Point Cloud 2016-18 - Cochrane - Lift Metadata (SHP) OMAFRA Lidar Point Cloud 2016-18- Peterborough - Lift Metadata (SHP) OMAFRA Lidar Point Cloud 2016-18 - Lake Erie - Lift Metadata (SHP) CLOCA Lidar Point Cloud 2018 - Lift Metadata (SHP) South Nation Lidar Point Cloud 2018-19 - Lift Metadata (SHP) York-Lake Simcoe Lidar Point Cloud 2019 - Lift Metadata (SHP) Ottawa River Lidar Point Cloud 2019-20 - Lift Metadata (SHP) OMAFRA Lidar Point Cloud 2022 - Lake Huron - Lift Metadata (SHP) OMAFRA Lidar Point Cloud 2022 - Lake Simcoe - Lift Metadata (SHP) Eastern Ontario Lidar Point Cloud 2021-22 - Lift Medatadata (SHP) DEDSFM Huron-Georgian Bay Lidar Point Cloud 2022-23 - Lift Metadata (SHP) DEDSFM Kawartha Lakes Lidar Point Cloud 2023 - Lift Metadata (SHP) DEDSFM Sault Ste Marie Lidar Point Cloud 2023-24 - Lift Metadata (SHP) DEDSFM Sudbury Lidar Point Cloud 2023-24 - Lift Metadata (SHP) DEDSFM Thunder Bay Lidar Point Cloud 2023-24 - Lift Metadata (SHP) DEDSFM Timmins Lidar Point Cloud 2024 - Lift Metadata (SHP) GTA 2023 - Lift Metadata (SHP)

Ontario Classified Point Cloud (Lidar-Derived) - Tile Index (SHP)

Ontario Lidar Project Extents (SHP)

Data Package Sizes

LEAP 2009 - 22.9 GB

OMAFRA Lidar 2016-18 - Cochrane - 442 GB OMAFRA Lidar 2016-18 - Lake Erie - 1.22 TB OMAFRA Lidar 2016-18 - Peterborough - 443 GB

GTA 2014 - 57.6 GB GTA 2015 - 63.4 GB Brampton 2015 - 5.9 GB Peel 2016 - 49.2 GB Milton 2017 - 15.3 GB Halton 2018 - 73 GB

CLOCA 2018 - 36.2 GB

South Nation 2018-19 - 72.4 GB

York Region-Lake Simcoe Watershed 2019 - 75 GB

Ottawa River 2019-20 - 836 GB

Lake Nipissing 2020 - 700 GB

Ottawa-Gatineau 2019-20 - 551 GB

Hamilton-Niagara 2021 - 660 GB

OMAFRA Lidar 2022 - Lake Huron - 204 GB OMAFRA Lidar 2022 - Lake Simcoe - 154 GB

Belleville 2022 - 1.09 TB

Eastern Ontario 2021-22 - 1.5 TB

Huron Shores 2021 - 35.5 GB

Muskoka 2018 - 72.1 GB Muskoka 2021 - 74.2 GB Muskoka 2023 - 532 GB The Muskoka lidar projects are available in the CGVD2013 or CGVD28 vertical datums. Please specifify which datum is needed when ordering data.

Digital Elevation Data to Support Flood Mapping 2022-26:

Huron-Georgian Bay 2022 - 1.37 TB Huron-Georgian Bay 2023 - 257 GB Huron-Georgian Bay 2023 Bruce - 95.2 GB Kawartha Lakes 2023 - 385 GB Sault Ste Marie 2023-24 - 1.15 TB Sudbury 2023-24 - 741 GB Thunder Bay 2023-24 - 654 GB Timmins 2024 - 318 GB

GTA 2023 - 985 GB

Status On going: Data is continually being updated

Maintenance and Update Frequency As needed: Data is updated as deemed necessary

Contact Ontario Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca

The global topographic LiDAR market is experiencing robust growth, projected to reach $2359.8 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 6.6% from 2025 to 2033. This expansion is driven by increasing demand across diverse sectors like oil & gas, mining, and infrastructure development. These industries leverage LiDAR's high-accuracy 3D mapping capabilities for efficient resource management, precise surveying, and detailed terrain modeling. Furthermore, advancements in sensor technology, resulting in more compact, affordable, and higher-resolution LiDAR systems, are fueling market adoption. The integration of LiDAR with other technologies like GPS and GIS further enhances its utility, creating synergistic solutions for complex mapping and modeling projects. The market is segmented by maximum measuring distance (below 500m, 500-1000m, above 1000m) reflecting the varying needs of different applications. The growth is geographically diverse, with North America and Europe currently holding significant market share, but rapid infrastructure development in the Asia-Pacific region promises substantial future growth. The market's restraints include the high initial investment cost of LiDAR equipment and the need for specialized expertise to operate and process the collected data. However, this is partially offset by the increasing availability of user-friendly software and data processing services. Furthermore, ongoing technological advancements are continuously driving down the cost of LiDAR systems, making them accessible to a wider range of users. The competitive landscape is populated by established players like Hexagon Geosystems, Trimble, and Leica Geosystems, along with emerging companies offering innovative solutions. This competitive environment fosters innovation and drives the development of more sophisticated and efficient LiDAR technologies, further contributing to market expansion. Future growth will likely be driven by the increasing adoption of autonomous vehicles, precision agriculture, and the expanding needs of urban planning and development.

These files contain classified topographic and bathymetric lidar data as unclassified valid topographic data (1), valid topographic data classified as ground (2), noise (7), and valid bathymetric data (11). Classes 1, 2 and 7 aredefined in accordance with the American Society for Photogrammetry and Remote Sensing (ASPRS) classification standards, while class 11 is specific to NOAA CSC. These data were collected by the Compact Hydrographic Airborne RapidTotal Survey (CHARTS) system along the coast of Massachusetts and New Hampshire. CHARTS integrates topographic and bathymetric lidar sensors, a digital camera and a hyperspectral imager on a single remote sensing platform for usein coastal mapping and charting activities. Data coverage generally extends along the coastline from the waterline inland 500 meters (topography) and offshore 1,000 meters or to laser extinction (bathymetry). Native lidar data isnot generally in a format accessible to most Geographic Information Systems (GIS). Specialized in-house and commercial software packages are used to process the native lidar data into 3-dimensional positions that can be importedinto GIS software for visualization and further analysis. Horizontal positions, provided in decimal degrees of latitude and longitude, are referenced to the North American Datum of 1983 (NAD83). Vertical positions are referencedto the NAD83 ellipsoid and provided in meters. The National Geodetic Survey's (NGS) GEOID03 model is used to transform the vertical positions from ellipsoid to orthometric heights referenced to the North American Vertical Datumof 1988 (NAVD88). The 3-D position data are sub-divided into a series of LAS files, each covering approximately 5 kilometers of shoreline. The format of the file is LAS version 1.2.

This Data Series Report contains lidar elevation data collected September 5 to October 11, 2012, for the barrier islands of Alabama, Mississippi and southeast Louisiana, including the coast near Port Fourchon. Most of the data were collected September 5-10, 2012, with a reflight conducted on October 11, 2012, to increase point density in some areas. Lidar data exchange format (LAS) 1.2 formatted point data files were generated based on these data. The point cloud data were processed to extract bare earth data; therefore, the point cloud data are organized into only four classes: 1-unclassified, 2-ground, 7-noise and 9-water. Aero-Metric, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process these data. The lidar data were collected at a nominal pulse spacing (NPS) of 1.0 meter (m). The horizontal projection and datum of the data are Universe Transverse Mercator, zones 15N and 16N, North American Datum 1983 (UTM Zone 15N or 16N NAD83), meters. The vertic ...

The Topographic LiDAR Sensors market is experiencing robust growth, driven by increasing demand for high-accuracy 3D mapping and surveying solutions across various sectors. Applications span infrastructure development, environmental monitoring, precision agriculture, and autonomous vehicle navigation. The market's expansion is fueled by advancements in sensor technology, leading to improved range, resolution, and data processing capabilities. Furthermore, the decreasing cost of LiDAR systems is making the technology more accessible to a wider range of users, including smaller surveying firms and research institutions. Considering a typical CAGR of 15% within the geospatial technology sector and a logical estimation based on comparable markets, let's assume a market size of $2.5 billion in 2025. This suggests a substantial growth trajectory, potentially reaching over $5 billion by 2033. Key players, such as Leica Geosystems, Trimble, and Riegl, are constantly innovating, introducing new products and services to cater to the evolving demands of the market. Despite the promising outlook, market growth faces certain constraints. The high initial investment cost for LiDAR systems and the specialized expertise required for data acquisition and processing can present barriers to entry for some businesses. Additionally, weather conditions can significantly impact data acquisition quality, presenting operational challenges. However, ongoing technological advancements, such as the development of more compact and user-friendly systems, along with robust data processing software, are gradually mitigating these limitations. The segmentation of the market by application (infrastructure, environment, agriculture) and by sensor type (terrestrial, airborne, mobile) further highlights the market's diversification and future growth potential. The competitive landscape remains dynamic with existing players engaging in strategic partnerships and mergers and acquisitions to enhance their market share.

As part of a collaborative study with the City of Raleigh, North Carolina, the U.S. Geological Survey developed a suite of high-resolution lidar-derived raster datasets for the Greater Raleigh Area, North Carolina, using repeat lidar data from the years 2013, 2015, and 2022. These datasets include raster representations of digital elevation models (DEMs), DEM of difference, the ten most common geomorphons (i.e. geomorphologic feature), lidar point density, and positive topographic openness. Raster footprints vary by year based on extent of lidar data collection. All files are available as Cloud Optimized GeoTIFF, meaning they are formatted to work on the cloud or can be directly downloaded. These metrics have been developed to pair with field geomorphic assessments for use in the development of a model that can remotely predict streambank erosion potential along streams in the Greater Raleigh, NC Area, however, they have the potential to be used in numerous applications.

USGS Contract: G10PC00026, Task Order Number: G10PD02143 Task Order Numbers: G10PD01027 (ARRA) and G10PD02143 (non-ARRA) The LiDAR for the North East Project, funded in large part by the American Recovery and Reinvestment Act (ARRA) of 2009, as well as, other funding sources was designed to help stimulate the U.S. economy and provide for more accurate floodplain mapping in the North East, representing the start of a regional LiDAR collection program that served as a test case for a national elevation program. Lead by the United States Geological Survey's (USGS) National Geospatial Program Office and the State of Maine's Office of GIS with active collaboration and participation by other federal, state and local agencies resulted in LiDAR acquisition and processing of over 8,000 sq. miles of (LiDAR) data of a coastal zone spanning six North Eastern states, including Maine, New Hampshire, Massachusetts, Connecticut, Rhode Island, and New York. USGS's National Geospatial Technical Operations Center (USGS NGTOC) in Rolla, MO provided project management and quality control oversight for the project which consisted of two Task Orders issued to USGS contractor, GMR Aerial Surveys inc. d/b/a Photo Science (contractor), for task order execution through the use of USGS's Geospatial Products and Services Contract (USGS Contract: G10PC00026). Task Order specifications included state/area specific vertical accuracy, nominal post spacing and tide coordinated acquisition requirements. To see state/area specific information please see the individual project metadata links in the Supplemental_Information section below. NOAA CSC received the topographic LAS files from USGS and Maine Office of GIS. The data was minimally processed by CSC, however the classes were adjusted (individual points were not changed): NOAA CSC Modified Classification Scheme: Class 1: Unclassified Class 2: Ground Class 7: Noise Class 9: Water Class 10: Breakline Proximity Class 14: Bare (Open) Water Class 15: Overlap Water Class 16: Overlap Bare (Open) Water Class 17: Overlap Default Class 18: Overlap Ground

This data originated with USGS and partners and was modified by NOAA for distribution in the Digital Coast. Modifications primarily involve the projection, vertical datum, and point class coding. This data was acquired through USGS Contract: G10PC00026, Task Order Number: G10PD02143 Task Order Numbers: G10PD01027 (ARRA) and G10PD02143 (non-ARRA). The LiDAR for the North East Project, funded in large part by the American Recovery and Reinvestment Act (ARRA) of 2009, as well as, other funding sources was designed to help stimulate the U.S. economy and provide for more accurate floodplain mapping in the North East, representing the start of a regional LiDAR collection program that served as a test case for a national elevation program. Lead by the United States Geological Survey's (USGS) National Geospatial Program Office and the State of Maine's Office of GIS with active collaboration and participation by other federal, state and local agencies resulted in LiDAR acquisition and processing of over 8,000 sq. miles of (LiDAR) data of a coastal zone spanning six North Eastern states, including Maine, New Hampshire, Massachusetts, Connecticut, Rhode Island, and New York. USGS's National Geospatial Technical Operations Center (USGS NGTOC) in Rolla, MO provided project management and quality control oversight for the project which consisted of two Task Orders issued to USGS contractor, GMR Aerial Surveys inc. d/b/a Photo Science (contractor), for task order execution through the use of USGS's Geospatial Products and Services Contract (USGS Contract: G10PC00026). Task Order specifications included state/area specific vertical accuracy, nominal post spacing and tide coordinated acquisition requirements. To see state/area specific information please see the individual project metadata links in the Supplemental_Information section below. NOAA OCM received the topographic LAS files from USGS and Maine Office of GIS. The data was minimally processed by OCM, however the classes were adjusted (individual points were not changed): NOAA OCM received a redelivery for 32 tiles in Maine to fill small voids in data. These redelivered tiles were incorporated on 1/23/2014. NOAA OCM Modified Classification Scheme: Class 1: Unclassified Class 2: Ground Class 7: Noise Class 9: Water Class 10: Breakline Proximity Class 14: Bare (Open) Water Class 15: Overlap Water Class 16: Overlap Bare (Open) Water Class 17: Overlap Default Class 18: Overlap Ground

This collection of the 3D Elevation Program (3DEP) is at 1/3 arc-second (approximately 10 m) resolution. 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. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. The seamless 1/3 arc-second DEM layers are derived from diverse source data that are processed to a common coordinate system and unit of vertical measure. These data are distributed in geographic coordinates in units of decimal degrees, and in conformance with the North American Datum of 1983 (NAD 83). All elevation values are in meters and, over the continental United States, are referenced to the North American Vertical Datum of 1988 (NAVD88). The vertical reference will vary in other areas. The seamless 1/3 arc-second DEM layer provides coverage of the conterminous United States, Hawaii, Puerto Rico, other territorial islands, and in limited areas of Alaska. These seamless DEMs were referred to as the National Elevation Dataset (NED) from about 2000 through 2015 at which time they became the seamless DEM layers under the 3DEP program and the NED name and system were retired. All 3DEP products are public domain.

Fugro Horizons Inc. acquired highly accurate Light Detection and Ranging (lidar) elevation data for the Twin Cities metropolitan region in east-central Minnesota in Spring and Fall 2011, with some reflights in Spring 2012. The data cover Anoka, Benton, Carver, Dakota, Goodhue, Hennepin, Isanti, Kanabec, Meeker, Mille Lacs, Morrison, Ramsey, Scott, Sherburne and Washington counties.

Most of the data was collected at 1.5 points/square meter. Smaller areas were collected with 2 points/square meter and with 8 points/square meter:
1. 1.5 points/square meter covers Morrison, Mille Lacs, Benton, Isanti, Sherburne, Anoka, Meeker, Hennepin, Washington, Carver, Scott, and Goodhue counties.
2. 2 points/square meter covers the Dakota Block (southern 2/3 of Dakota County)
3. 8 points/square meter covers portions of Minneapolis/St. Paul and the City of Maple Grove
See map of block boundaries: https://www.mngeo.state.mn.us/chouse/elevation/metro_data_delivery_dates.pdf

Data are in the UTM Zone 15 coordinate system, NAD83 (HARN), NAVD88 Geoid09, meters. The tiling scheme is 16th USGS 1:24,000 quadrangle tiles.

The vendor delivered the data to the Minnesota Department of Natural Resources (DNR) in several formats:

1. One-meter digital elevation model
2. Edge-of-water breaklines
3. Classified LAS formatted point cloud data

DNR staff quality-checked the data and created three additional products: two-foot contours, building outlines and hillshades.

This metadata record was created at the Minnesota Geospatial Information Office using information supplied by the vendor and by DNR.

This zip file contains LIDAR, Digital Terrain Models (DTM's), surface, and breakline datasets covering the extent of Peoria County. The LIDAR data was captured during spring leaf-off in 2008. There are eight databases in Esri's file geodatabase format which are broken down by eight areas in the County. The DTM's conform to the ASPRS Class I Standards using the Illinois State Plane West coordinate system. Please contact us if you would like a copy of the data.More recent LIDAR data for Peoria County, IL was captured in 2012 by the State of Illinois through the Illinois Height Modernization Program (ILHMP). Please click Here to read about the program and data available for download.Contact InformationPeoria County GISEmail: gis@peoriacounty.orgPhone: 309-495-4840This data is bound to the Peoria County GIS Open Data License Agreement which can be found here: https://data-peoriacountygis.opendata.arcgis.com/pages/peoria-county-gis-open-data-license-agreement.

The Airborne LiDAR System market is experiencing robust growth, driven by increasing demand across diverse sectors. Applications in surveying and mapping, precision agriculture, infrastructure development, and environmental monitoring are key contributors to this expansion. The market's Compound Annual Growth Rate (CAGR) is estimated at 12% for the period 2025-2033, indicating significant future potential. Technological advancements, particularly in sensor technology and data processing capabilities, are enhancing the accuracy, speed, and efficiency of Airborne LiDAR Systems, leading to wider adoption. The integration of LiDAR with other technologies, such as GPS and IMU, is further enhancing the overall performance and reliability of these systems. Furthermore, the rising need for detailed 3D mapping for urban planning, autonomous vehicles, and disaster management contributes to market expansion. The North American and European regions currently dominate the market, owing to advanced technological infrastructure and substantial investments in research and development. However, developing economies in Asia-Pacific and the Middle East & Africa are demonstrating promising growth potential driven by infrastructural development and increasing government spending on mapping initiatives. The topographic LiDAR segment holds the largest market share, driven by its wide applicability in various industries. However, the bathymetric LiDAR segment is projected to witness significant growth owing to rising demand for accurate underwater mapping for offshore energy exploration and coastal management. Competition among established players like Leica Geosystems, Trimble, and RIEGL, alongside emerging companies, is fostering innovation and driving down costs, making this technology more accessible. While high initial investment costs can be a restraint, the long-term benefits in terms of improved accuracy, efficiency, and data quality are overcoming this challenge. The continued growth of the Airborne LiDAR System market is anticipated to be fueled by several factors. Government initiatives promoting digital mapping and spatial data infrastructure are creating a favorable environment. The increasing adoption of cloud-based data processing solutions is improving accessibility and reducing computational costs associated with LiDAR data processing. Moreover, the development of lighter, more compact Airborne LiDAR Systems is improving deployment flexibility, enhancing their usage across various terrain and environmental conditions. While challenges such as data processing complexity and skilled labor shortages exist, ongoing technological innovations and investment in training programs are mitigating these issues, leading to increased market penetration. The future of this market is promising, with sustained growth projected over the forecast period driven by technological advancements and rising demand across various applications.

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 and range from shoreline strips to full county coverage. The products have been delivered to the Center in various formats, projections, datums, and units. Once received, the data are reviewed, checked for errors, and standardized to LAZ format, geographic coordinates and ellipsoid heights in meters. Data are on a NAD83 or ITRF realization depending upon the collection specifics.

Terrapoint collected Light Detection and Ranging (LiDAR) data for the Lewis County project of 2005. The project site covered approximately 223 square miles, divided into two blocks: southern block 213 Square Miles, northern block 10 Square Miles. The field data collection took place from December 11th, 2004 to January 30th, 2005. LIDAR data was collected on 12/11/2004, 12/12/2004, 12/15/2004, 1/20/2005, 1/21/2005, 1/24/2005 and 1/30/2005. The control network and check point surveys were established from December 11th to December 23rd, 2004. The Airborne LiDAR survey was conducted using Terrapoint?s 40 kHz ALTMS (Airborne Laser Terrain Mapping System), flying at an optimum height of 3500 ft AGL at 140 knots. The system consists of a 36-degree full angle laser, a Trimble 4700 GPS receiver and a Honeywell H764 IMU unit. This metadata is a collaboration of metadata reports from each of the individual 15 projects. The Puget Sound Lowlands project covers more areas over 2000-2004, these areas were excluded for this project.

A digital elevation model (DEM) of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, post-Nor'Ida (November 2009 nor'easter), was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams 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 plane travels over the target area at approximately 50 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed by NASA at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of +/-15 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When subsequent elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

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 .

description: These files contain rasterized topobathy lidar elevations collected after Hurricane Irma. In an effort to provide data as soon as possible, JALBTCX will be sending rolling deliveries of data to the NOAA Office for Coastal Management for the Digital Coast. The total collection area will include the east coast of Florida, the Florida Keys, and Collier County. The data were collected by the Coastal Zone Mapping and Imaging Lidar (CZMIL) system. CZMIL integrates a lidar sensor with simultaneous topographic and bathymetric capabilities, a digital camera and a hyperspectral imager on a single remote sensing platform for use in coastal mapping and charting activities. Native lidar data is not generally in a format accessible to most Geographic Information Systems (GIS). Specialized in-house and commercial software packages are used to process the native lidar data into 3-dimensional positions that can be imported into GIS software for visualization and further analysis. The 3-D position data are sub-divided into a series of LAS files, which are tiled into 1-km by 1-km boxes defined by the Military Grid Reference System. In addition to the these topobathy bare earth Digital Elevation Models (DEMs) at a 1 meter grid spacing, the lidar point data are also available. These data are available for custom download here: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6330 DEMs that were created from all classes of points (1, 2, 29) at a 1 meter grid size are available by request via email at: coastal.info@noaa.gov. These products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA or OCM.; abstract: These files contain rasterized topobathy lidar elevations collected after Hurricane Irma. In an effort to provide data as soon as possible, JALBTCX will be sending rolling deliveries of data to the NOAA Office for Coastal Management for the Digital Coast. The total collection area will include the east coast of Florida, the Florida Keys, and Collier County. The data were collected by the Coastal Zone Mapping and Imaging Lidar (CZMIL) system. CZMIL integrates a lidar sensor with simultaneous topographic and bathymetric capabilities, a digital camera and a hyperspectral imager on a single remote sensing platform for use in coastal mapping and charting activities. Native lidar data is not generally in a format accessible to most Geographic Information Systems (GIS). Specialized in-house and commercial software packages are used to process the native lidar data into 3-dimensional positions that can be imported into GIS software for visualization and further analysis. The 3-D position data are sub-divided into a series of LAS files, which are tiled into 1-km by 1-km boxes defined by the Military Grid Reference System. In addition to the these topobathy bare earth Digital Elevation Models (DEMs) at a 1 meter grid spacing, the lidar point data are also available. These data are available for custom download here: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6330 DEMs that were created from all classes of points (1, 2, 29) at a 1 meter grid size are available by request via email at: coastal.info@noaa.gov. These products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA or OCM.

The Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the Massachusetts coast. Seventy-six maps were produced in 1997 depicting a statistical analysis of shoreline change on ocean-facing shorelines from the mid-1800s to 1978 using multiple data sources. In 2001, a 1994 shoreline was added. More recently, in cooperation with CZM, the U.S. Geological Survey (USGS) delineated a new shoreline for Massachusetts using color aerial ortho-imagery from 2008 to 2009 and topographic lidar data collected in 2007. This update included a marsh shoreline, which was defined to be the tonal difference between low- and high-marsh seen in ortho-photos. Further cooperation between CZM and the U.S. Geological Survey (USGS) has resulted in another update in 2018, which includes beach shorelines, marsh shorelines and dune parameters, all of which were calculated from 2013-14 topographic lidar data. This metadata file describes the marsh shoreline that is part of the 2018 update. The marsh shoreline was defined to be the steep slope found at the seaward edge of the marsh vegetation. This definition was used because the marsh edge is the preferred shoreline indicator for computing rates of change and making position forecasts.