2019 - 2020 USGS Lidar (QL2): Western PA

Dates of collection for PA_WesternPA_2 (Work Unit 208661). Includes part of Allegheny, Armstrong, Butler, Clarion, Forest, Indiana, Mercer, Venango, and Washington counties and the full counties of Beaver, Jefferson, and Lawrence.

Dates of collection for PA_WesternPA_4 (Work Unit 210015). Includes part of Clarion, Forest, Indiana, Mercer, and Venango counties and the full counties of Crawford, Erie, and Warren.

Dates of collection for PA_WesternPA_1 (Work Unit 186384). Includes part of Allegheny, Armstrong, Butler, Indiana, and Washington counties and the full counties of Cambria, Fayette, Greene, and Somerset.

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, in UTM Zone 17N NAD83 (2011), meters coordinates, orthometric heights 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 reports, breaklines, metadata, spatial metadata, and shapefiles.

Link to the USGS Project Report that provides information about the project, vertical accuracy results, and the point classes and sensors used.

Lidar report for PA_Western_PA_1 (Work Unit 186384) which covers part of Allegheny, Armstrong, Butler, Indiana, and Washington counties and the full counties of Cambria, Fayette, Greene, and Somerset.

Lidar report for PA_Western_PA_2 (Work Unit 208661) which covers part of Allegheny, Armstrong, Butler, Clarion, Forest, Indiana, Mercer, Venango, and Washington counties and the full counties of Beaver, Jefferson, and Lawrence.

Lidar report for PA_Western_PA_4 (Work Unit 210015) which covers part of Clarion, Forest, Indiana, Mercer, and Venango counties and the full counties of Crawford, Erie, and Warren.

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.

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.

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.

Raw Data and Boresight Processing: The boresight for each lift was done

individually as the solution may change slightly from lift to lift. The following steps

describe the Raw Data Processing and Boresight process: 1) Technicians processed the raw

data to LAS format flight lines using the final GPS/IMU solution. This LAS data set was

used as source data for boresight. 2) Technicians first used Quantum Spatial, Inc.

proprietary and commercial software to calculate initial boresight adjustment angles based

on sample areas selected in the lift. These areas cover calibration flight lines collected

in the lift, cross tie, and production flight lines. These areas are well distributed in

the lift coverage and cover multiple terrain types that are necessary for boresight angle

calculation. The technicians then analyzed the results and made any necessary additional

adjustment until it was acceptable for the selected areas. 3) Once the boresight angle

calculation was completed for the selected areas, the adjusted settings were applied to

all of the flight lines of the lift and checked for consistency. The technicians utilized

commercial and proprietary software packages to analyze how well flight line overlaps

matched for the entire lift and adjusted as necessary until the results met the project

specifications. 4) Once all lifts were completed with individual boresight adjustment, the

technicians checked and corrected the vertical misalignment of all flight lines and also

the matching between data and ground truth. The relative accuracy was less than or equal

to 7 cm RMSEz within individual swaths and less than or equal to 10 cm RMSEz or within

swath overlap (between adjacent swaths). 5) The technicians ran a final vertical accuracy

check of the boresighted flight lines against the surveyed checkpoints after the z

correction to ensure the requirement of NVA = 19.6 cm 95% Confidence Level (Required

Accuracy) was met.

LAS Point Classification: The point classification was performed as described

below. The bare earth surface was manually reviewed to ensure correct classification on

the Class 2 (Ground) points. After the bare-earth surface was finalized, it was then used

to generate all hydro-breaklines through heads-up digitization. All ground (ASPRS Class 2)

LiDAR data inside of the Lake Pond and Double Line Drain hydro-flattened breaklines were

then classified to Water (ASPRS Class 9) using TerraScan macro functionality. A buffer of

1 meter was also used around each hydro-flattened feature to classify these ground (ASPRS

Class 2) points to Ignored ground (ASPRS Class 20). All Lake Pond Island and Double Line

Drain Island features were checked to ensure that the ground (ASPRS Class 2) points were

reclassified to the correct classification after the automated classification was

completed. All overlap data was processed through automated functionality provided by

TerraScan to classify the overlapping flight line data to approved classes. The overlap

data was classified using standard LAS overlap bit. These classes were created through

automated processes only and were not verified for classification accuracy. Due to

software limitations within TerraScan, these classes were used to trip the withheld bit

within various software packages. These processes were reviewed and accepted through

numerous conference calls and pilot study areas. All data were manually reviewed and any

remaining artifacts removed using functionality provided by TerraScan and TerraModeler.

Global Mapper was used as a final check of the bare earth dataset. GeoCue was then used to

create the deliverable industry-standard LAS files for both the All Point Cloud Data and

the Bare Earth. Quantum Spatial, Inc. proprietary software was used to perform final

statistical analysis of the classes in the LAS files, on a per tile level to verify final

classification metrics and full LAS header information.

Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles 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 (GEOID12B).

The NOAA Office for Coastal Management (OCM) created references to the Entwine Point Tile (EPT) files that were 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.

These are the AWS URLs being accessed:

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/PA_WesternPA_1_2019/ept.json

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/PA_WesternPA_2_2019/ept.json

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/PA_WesternPA_4_2019/ept.json