2014 USGS Lidar: Schoharie County, NY

Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options.

Bulk download of data files in LAZ format, UTM Zone 18N NAD83(2011), meters coordinates and NAVD88 (Geoid12A) elevations in meters .

The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.

Link to the Dewberry lidar report.

Link to the reports, breaklines, metadata, and spatial metadata.

Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.

Link to view the point cloud, using the Entwine Point Tile (EPT) format, in the 3D Potree viewer.

Data for the Schoharie County and Schoharie Watershed Expansion LiDAR project was acquired by The Atlantic Group (TAG) using a CESSNA TU206G aircraft.

The project area included approximately 965 contiguous square miles for Schoharie County, New York. LiDAR sensor data was collected with the Leica ALS70-HP LiDAR system. No imagery was requested or delivered. The calibrated data was processed to NAD83(2011) UTM 18, meters, NAVD88 (Geoid12A), meters. Deliverables for the project included a raw (unclassified) calibrated LiDAR point cloud, survey control, and a final control report.

A preliminary RMSEz error check is performed at this stage of the project life cycle in the raw LiDAR dataset against GPS static and kinematic data and compared to RMSEz project specifications. The LiDAR data is examined in open, flat areas away from breaks. Lidar ground points for each flightline generated by an automatic classification routine are used.

Overall the LiDAR data products collected by Atlantic meet or exceed the requirements set out in the Statement of Work. The quality control requirements of Atlantic's quality management program were adhered to throughout the acquisition stage fo this project to ensure product quality.

LIDAR acquisition began on May 26, 2014 (julian day 146) and was completed on June 2, 2014 (julian day 153). A total of 9 survey missions were flown to complete the project. The flight plan was flown as planned with no modifications. There were no unusual occurrences during the acquisition and the sensor performed within specifications. There were 131 flight lines required to complete the project.

The initial step of calibration is to verify availability and status of all needed GPS and Laser data against field notes and compile any data if not complete.

Subsequently the mission points are output using Leica's ALS Post Processor, initially with the most recent boresight values. The initial point generation for each mission calibration is verified within Microstation/Terrascan for calibration errors. If a calibration error greater than specification is observed within the mission, the roll pitch and scanner scale corrections that need to be applied are calculated. The missions with the new calibration values are regenerated and validated internally once again to ensure quality.

All missions are validated against the adjoining missions for relative vertical biases and collected GPS validation points for absolute vertical accuracy purposes.

On a project level, a supplementary coverage check is carried out to ensure no data voids unreported by Field Operations are present.

The initial points for each mission calibration are inspected for flight line errors, flight line overlap, slivers or gaps in the data, point data minimums, or issues with the LiDAR unit or GPS. Roll, pitch and scanner scale are optimized during the calibration process until the relative accuracy is met.

Relative accuracy and internal quality are checked using at least 3 regularly spaced QC blocks in which points from all lines are loaded and inspected. Vertical differences between ground surfaces of each line are displayed. Color scale is adjusted so that errors greater than the specifications are flagged. Cross sections are visually inspected across each block to validate point to point, flightline to flightline and mission to mission agreement.

For this project the specifications used are as follow:

Relative accuracy <= 7cm RMSEZ within individual swaths and <=10 cm RMSEZ or within swath overlap (between adjacent swaths).

UTM coordinate system, meters, zone 18, horizontal datum NAD83 (2011), vertical datum NAVD88, Geoid 12A

Dewberry utilizes a variety of software suites for inventory management, classification, and data processing. All LiDAR related processes begin by importing the data into the GeoCue task management software. The swath data is tiled according to project specifications (1,500 m x 1,500 m). The tiled data is then opened in Terrascan where Dewberry uses proprietary ground classification routines to remove any non-ground points and generate an accurate ground surface. The ground routine consists of three main parameters (building size, iteration angle, and iteration distance); by adjusting these parameters and running several iterations of this routine an initial ground surface is developed. The building size parameter sets a roaming window size. Each tile is loaded with neighboring points from adjacent tiles and the routine classifies the data section by section based on this roaming window size. The second most important parameter is the maximum terrain angle, which sets the highest allowed terrain angle within the model. Once the ground routine has been completed a manual quality control routine is done using hillshades, cross-sections, and profiles within the Terrasolid software suite. After this QC step, a peer review and supervisor manual inspection is completed on a percentage of the classified tiles based on the project size and variability of the terrain. After the ground classification corrections were completed, the dataset was processed through a water classification routine that utilizes breaklines compiled by Atlantic to automatically classify hydrographic features. The water classification routine selects ground points within the breakline polygons and automatically classifies them as class 9, water. During this water classification routine, points that are within 0.3 meter of the hydrographic features are moved to class 10, an ignored ground due to breakline proximity. In addition to classes 1, 2, 9, and 10, there is a Class 7, noise points . Class 7 was only used if needed when points could manually be identified as low/high points.

The fully classified dataset is then processed through Dewberry's comprehensive quality control program.

The data was classified as follows:

Class 1 = Unclassified. This class includes vegetation, buildings, noise etc.

Class 2 = Ground

Class 7= Noise

Class 9 = Water

Class 10=Ignored

The LAS header information was verified to contain the following:

Class (Integer)

GPS Week Time (0.0001 seconds)

Easting (0.003 m)

Northing (0.003 m)

Elevation (0.003 m)

Echo Number (Integer 1 to 4)

Echo (Integer 1 to 4)

Intensity (8 bit integer)

Flight Line (Integer)

Scan Angle (Integer degree)

Original point clouds in LAS/LAZ format were restructured as an Entwine Point Tile and stored on Amazon Web Services. The data were re-projected horizontally to WGS84 web mercator (EPSG 3857) and no changes were made to the vertical elevations in NAVD88 (GEOID12A).

The NOAA Office for Coastal Management (OCM) created references to the Entwine Point Tile (EPT) file that was ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the point cloud as it resides on Amazon Web Services (AWS) under the usgs-lidar-public container.

This is the AWS URL being accessed:

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_NY_Schoharie_2014_LAS_2016/ept.json