Dataset contains 32 terrestrial lidar scans of conifer forests and associated shapefile of locations in Sequoia and Kings Canyon National parks from the summer of 2022. These scans were co-located within field plots from a larger ongoing U.S. Geological Survey (USGS) project collecting wildfire fuels and forest structure data (informally known as the Fire and Fuels Project). These data can also be found in a USGS Earth Resources Observation and Science (EROS) database named IntELiMon (https://dmsdata.cr.usgs.gov/lidar-monitoring/viewer/).

This dataset includes topographic elevations (in meters) surrounding and bathymetric elevations within the upper Delaware River (USA). Bathymetric lidar data was acquired using the Experimental Advanced Airborne Research Lidar, version B. The EAARL-B is a successor instrument to the original EAARL bathymetric LiDAR sensor developed for mapping coral reef environments in clear water, but subsequently used in river mapping. Both the original EAARL and the EAARL-B are small footprint, full waveform digitizing, green wavelength (532nm) airborne laser scanners, capable of acquiring laser returns from submerged as well as subaerial topography. Improvements from the original sensor include increased sample density, increased pulse rate, enhanced deep and shallow bathymetry performance, and improved data processing hardware. The EAARL-B sensor differs from the original in a 10x laser power increase, and incorporation of three shallow water receiving channels, as well as a deep water recei ...

Product: Processed, classified lidar point cloud data tiles in LAS 1.4 format. Geographic Extent: Approximately 4,028 square miles encompassing the Big Island of Hawaii. Dataset Description: The HI Hawaii Island Lidar NOAA 2017 B17 lidar project called for the planning, acquisition, processing, and production of derivative products of lidar data to be collected at a nominal pulse spacing (NPS...

Lidar data was collected on 17 May 2017 at the USGS debris-flow flume to monitor the movement of a constructed landslide experiment. A static prism of sediment was emplaced behind a retaining wall at the top of the flume. Water was added via sprinklers to the surface and also via pipes to the subsurface, in order to saturate the sediment mass. The sediment mass eventually failed as a debris flow and moved down the flume. Lidar data was collected from a Riegl VZ-400 terrestrial laser scanner to capture the mass failure. The lidar unit was modified to scan a narrow swath (approximately 1 mm) along the full profile of the constructed sediment mass. The lidar scan rate was set to re-scan every 0.017 s or at a rate of 60 Hz. The data contained herein ecapsulates entire lidar point cloud from the time before prior to movement through full failure of the sediment mass. The points are organized in rows. The columns are: ['xM', 'yM', 'zM', 'rangeM', 'thetaDEG', 'phiDEG', 'riegl_ref', 'timestampSEC', 'Line'] . The 'xM', 'yM', 'zM' values are the x, y, and z real world UTM coordinates with units of meters. The 'rangeM' is the distance of each point from the scanner with units of meters. The vertical angle of the lidar scanner is shown as 'thetaDEG' with units of degrees. Similarly, the horizontal angle of the lidar scanner is shown as 'phiDEG' with units of degrees. The 'riegl_ref' represents reflectance value computed from the intensity. The timestamp is the number of seconds since the beginning of the scan. The 'Line' column represents all the points that belong to a single lidar profile swath.

Original Product: These lidar data are processed Classified LAS 1.4 files, formatted to 654 individual 1000 m x 1000 m tiles; used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.

Original Dataset Geographic Extent: 4 counties (Alameda, Marin, San Francisco, San Mateo) in California, covering approximately 53 total square miles.

Original Dataset Descriptio...

This data set is tiled lidar point cloud LAS files v1.4, for the 2016 Alabama 25 County lidar area of interest (AOI).

USGS NGTOC task order G17PD00243 required Spring 2017 LiDAR surveys to be collected over 18,845 square miles covering part or all of 25 counties in Alabama. These counties are Autauga, Baldwin, Barbour, Bullock, Butler, Chambers, Cherokee, Clarke, Conecuh, Covington, Cre...

These are terrestrial laser scanner datasets collected in forested areas west of Flagstaff, Arizona in 2015 and 2016. For each of the two scanners, six treatment areas were scanned, with four of them overlapping one another (Figure 1). These data are composed of individual scans referenced to one another using reflective targets, and geolocated using differentially corrected GPS and RTK locations of scan locations (Figure 3). There were overall large differences in point density among the two scanners (Figure 2).

This survey covers portions of Hawaii Volcano National Park on the Big Island of Hawaii. This dataset was contracted by the U.S. Geological Survey (USGS) via Quantum Spatial, Inc., and acquired by GEO1 and Windward Aviation. GEO1 conducted the collection activity using a Windward Aviation Hughes 500 helicopter with a dual LiDAR scanning system that utilized two Riegl VUX-SYS scanners operated as one unit. The dataset was acquired through 11 lifts, and comprises 4 distinct Areas of Interest (AOIs). The survey area covers 105 square kilometers. Dataset obtained from the USGS Kilauea LiDAR website. Please refer to that site for additional information.

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 ...

Lidar data was collected on 24 and 25 May 2017 at the USGS debris-flow flume to monitor two gate-release debris flow experiments. A static prism of sediment was emplaced behind a gate at the top of the flume. Water was added via sprinklers to the surface and also via pipes to the subsurface, in order to saturate the sediment mass. The sediment mass moved down the flume as a debris flow when the gate was opened. Lidar data was collected from a Riegl VZ-400 terrestrial laser scanner to capture the mass failure. The lidar unit was modified to scan a narrow swath (approximately 1 mm) along the full profile of the constructed sediment mass. The lidar scan rate was set to re-scan every 0.017 s or at a rate of 60 Hz. The data contained herein ecapsulates entire lidar point cloud from the time before prior to movement through full failure of the sediment mass. The points are organized in rows. The columns are: ['xM', 'yM', 'zM', 'rangeM', 'thetaDEG', 'phiDEG', 'riegl_ref', 'timestampSEC', 'Line'] . The 'xM', 'yM', 'zM' values are the x, y, and z real world UTM coordinates with units of meters. The 'rangeM' is the distance of each point from the scanner with units of meters. The vertical angle of the lidar scanner is shown as 'thetaDEG' with units of degrees. Similarly, the horizontal angle of the lidar scanner is shown as 'phiDEG' with units of degrees. The 'riegl_ref' represents reflectance value computed from the intensity. The timestamp is the number of seconds since the beginning of the scan. The 'Line' column represents all the points that belong to a single lidar profile swath.

Product: This lidar data set includes unclassified swath LAS 1.4 files, classified LAS 1.4 files, breaklines, digital elevation models (DEMs), and intensity imagery. Geographic Extent: The South Texas 2018 LiDAR AOI includes 30 counties in Texas, covering approximately 22,229 total square miles. Dataset Description: The South Texas 2018 LiDAR project called for the planning, acquisition, proc...

This is a tiled collection of the 3D Elevation Program (3DEP) and is one meter 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. USGS standard one-meter DEMs are produced exclusively from high resolution light detection and ranging (lidar) source data of one-meter or higher resolution. One-meter DEM surfaces are seamless within collection projects, but, not necessarily seamless across projects. The spatial reference used for tiles of the one-meter DEM within the conterminous United States (CONUS) is Universal Transverse Mercator (UTM) in units of meters, and in conformance with the North American Datum of 1983 (NAD83). All bare earth elevation values are in meters and are referenced to the North American Vertical Datum of 1988 (NAVD88). Each tile is distributed in the UTM Zone in which it lies. If a tile crosses two UTM zones, it is delivered in both zones. The one-meter DEM is the highest resolution standard DEM offered in the 3DEP product suite. Other 3DEP products are nationally seamless DEMs in resolutions of 1/3, 1, and 2 arc seconds. 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. Other 3DEP products include five-meter DEMs in Alaska as well as various source datasets including the lidar point cloud and interferometric synthetic aperture radar (Ifsar) digital surface models and intensity images. All 3DEP products are public domain.

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.

This dataset is comprised of three files containing northing, easting, and elevation ("XYZ") information for light detection and ranging (lidar) data representing the beach topography and sonar data representing near-shore topography of Lake Superior at Minnesota Point, near the Duluth entry, Duluth, Minnesota. The point data is the same as that in LAS files that were used to create the digital elevation models (DEMs) of the approximate 2.15 square kilometer surveyed area. Lidar data were collected September 07, 2022 using a boat mounted Velodyne VLP-16 unit and methodology similar to that described by Huizinga and Wagner (2019). Multibeam sonar data were collected September 06-07, 2022 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit and methodology similar to that described by Richards and Huizinga (2018). Single-beam sonar data were collected September 07, 2022 using a Ceescope echosounder and methodology similar to that described by Wilson and ...

This point shapefile represents 38 terrestrial laser scanner (TLS) survey scan locations collected by single-base real-time kinematic (RTK) global navigation satellite system (GNSS) surveys in Grapevine Canyon near Scotty's Castle, Death Valley National Park, from July 12-14, 2016. Data were collected by two Topcon GR-3 GNSS receivers at one-second intervals for three minutes for each _location.

We collected two ground-based (terrestrial) lidar scans of the southeast face of El Capitan cliff, located in Yosemite National Park, California. El Capitan is one of several iconic granitic cliffs in Yosemite and rises approximately 1000 meters above the floor of Yosemite Valley. The scans were collected from the same location and from a single vantage point on the edge of El Capitan meadow, about 1 kilometer from the cliff base. The two scans were collected roughly three hours apart from one another to assess accuracy related to thermal changes to the rock cliff. Each lidar scan captures an identical section of the wall totaling approximately 1 square kilometer in vertical surface area. The resulting point clouds each consists of approximately 59 million points (approximate point density of 59 points/square meter).

High-resolution, terrestrial laser scanning (TLS), was used to quantify the volume of sediment eroded from outcrops at Malakoff Diggins State Historic Park, located about 17 kilometers (km) northeast of Grass Valley, California. TLS was used to create centimeter-scale, three-dimensional (3-D) maps of the complex outcrop surfaces, which could not be mapped non-destructively or in sufficient detail with traditional surveying techniques. To develop a comprehensive sediment budget for the Malakoff Diggins mine pit that will help identify sources of sediment and metals within the pit that comprise the suspended sediment discharged from the pit into Humbug Creek, the USGS used TLS technology to quantify the eroded volumes and erosion rates of sedimentary units exposed in the pit walls. Eroded volumes from nineteen sedimentary units at four study sites located throughout the pit were calculated for the period December 2014 to August 2017. (Note that the monitoring sites were numbered 1, 2, 4, and 5.) Each survey at all four study sites was comprised of multiple lidar scans collected from different vantages that were combined into a composite 3-D point cloud. At all four study sites, the sequential surveys were co-registered or ‘aligned’ into a common and site-specific reference frame so that volumetric comparisons between surveys could be made. At each study site, sedimentary units were differentiated based on grain size, color, compaction, cementation, and slope angle. The various sedimentary units were mapped on the lidar point clouds and individually isolated for volumetric change analysis. The volumetric differences between surveys quantify the erosional and/or depositional volume change of each sedimentary unit.

This is a terrestrial LiDAR laser scanner dataset collected on October 14, 2020, in response to a flow event that occurred on September 8, 2020, at the USGS streamgage 09471580 - San Pedro River at St David, AZ. The reach scanned for this study is located at the bridge where State Route 80 crosses the waterway. A Leica MS-60 Multistation was used for the laser scanner data collection. Multiple scans were combined by setting up the scanner using resection techniques coupled with Leica RTK - GPS equipment. All scan data are corrected using measurements of a reference mark with a known _location.

This survey covers portions of Hawaii Volcano National Park on the Big Island of Hawaii. This dataset was contracted by the U.S. Geological Survey (USGS) via Quantum Spatial, Inc., and acquired by GEO1 and Windward Aviation. GEO1 conducted the collection activity using a Windward Aviation Hughes 500 helicopter with a dual LiDAR scanning system that utilized two Riegl VUX-SYS scanners operated as one unit. The dataset was acquired through 11 lifts, and comprises 4 distinct Areas of Interest (AOIs). The survey area covers 105 square kilometers. Dataset obtained from the USGS Kilauea LiDAR website. Please refer to that site for additional information.

This data release is composed of point cloud data from a terrestrial lidar survey, GNSS survey data, and derivative raster data. The data were collected on November 09, 2023. This survey was used to characterize a debris flow basin near El Portal, California for the National Park Service.