2014 USGS Lidar: Central Virginia Seismic (Louisa County)

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The project area addressed by this report falls within the Virginia county of Louisa with actual data edges falling within Fluvanna, Goochland, and Spotsylvania.

Date that the source FGDC record was last modified.

Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.

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Data for the Central Virginia Seismic LiDAR project was acquired by PAR using a ALTM NAV Flight Plan Optech ALTM3100EA LiDAR system Piper Navajo Aircraft.

LIDAR acquisition began on May 6, 2014 (julian day 126) and was completed on May 7, 2014 (julian day 127). A total of 2 survey missions were flown to complete the project. PAR utilized a Lecia ALS70-CM for the acquisition. 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 186 flight lines required to complete the project. The calibrated data was processed to NAD83(2011) UTM 17, meters, NAVD88 (Geoid12A), meters.

One base station was utilized VA_21. The base station coordinates are set forth below:

VA_21 Latitude: 28 00 25.25513

Longitude: -77 58 24.21356

Ellipsoid Height: 112.461

Orthometric Height: 144.7978

4 kinematic cross sections and 11 static points were surveyed at various locations throughout the project to be utilized for quality control and adjustment of the LIDAR data.

All airborne GPS trajectories were processed and checked on site. All trajectories were very high quality with forward/reverse separation rms between 1cm-3cm.

All equipment performed within specifications with no unusual occurrences or anomalies. All data was of a very high quality and the project was executed as planned.

Overall the LiDAR data products collected for Dewberry and Davis meet or exceed the requirements set out in the Statement of Work for this project. The quality control requirements of PARs Quality management program were adhered to throughout the acquisition stage of this project to ensure product quality.

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 Dewberry 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 1 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 . This class 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)

Dewberry used GeoCue software to develop raster stereo models from the LiDAR intensity. The raster resolution was 0.3 meters.

LiDAR intensity stereopairs were viewed in 3-D stereo using Socet Set for ArcGIS softcopy photogrammetric software. The breaklines are collected directly into an ArcGIS file geodatabase to ensure correct topology. The LiDARgrammetry was performed under the direct supervision of an ASPRS Certified Photogrammetrist. The breaklines were stereo-compiled in accordance with the Data Dictionary.

Inland Lakes and Ponds were collected according to specifications for the Central VA Seismic LiDAR Project.

The data dictionary defines Inland Ponds and Lakes as a closed water body feature that is at a constant elevation. These polygon features should be collected at the land/water boundaries of constant elevation water bodies such as lakes, reservoirs, and ponds. Features shall be defined as closed polygons and contain an elevation value that reflects the best estimate of the water elevation at the time of data capture. Water body features will be captured for features 2 acres in size or greater. Donuts will exist where there are islands greater than 1/2 acre in size within a closed water body. Breaklines must be captured at or just below the elevations of the immediately surrounding terrain. Under no circumstances should a feature be elevated above surrounding LiDAR points. The compiler shall take care to ensure that the z-value remains consistent for all vertices placed on the water body.

No Inland Streams, Rivers or Tidal Waters met the collection requirements within the project area.

Breaklines are reviewed against LiDAR intensity imagery to verify completeness of capture. All breaklines are then compared to ESRI terrains created from ground only points prior to water classification. The horizontal placement of breaklines is compared to terrain features and the breakline elevations are compared to LiDAR elevations to ensure all breaklines match the LiDAR within acceptable tolerances. Some deviation is expected between breakline and LiDAR elevations due to monotonicity, connectivity, and flattening rules that are enforced on the breaklines. Once completeness, horizontal placement, and vertical variance is reviewed, all breaklines are reviewed for topological consistency and data integrity using a combination of ESRI Data Reviewer tools and proprietary tools. Corrections are performed within the QC workflow and re-validated.

Class 2, ground, LiDAR points are exported from the LAS files into an Arc Geodatabase (GDB) in multipoint format. The 3D breaklines, Inland Lakes and Ponds are imported into the same GDB. An ESRI Terrain is generated from these inputs. The surface type of each input is as follows:

Ground Multipoint: Masspoints

Inland Lakes and Ponds: Hard Replace

The ESRI Terrain is converted to rasters. The rasters are created to pre-defined extents so that multiple rasters are created over the project area. Creating multiple rasters rather than one large raster over a large project area makes the data more maneageable to work with. The rasters are created with 2 tiles of overlap. This allows us to ensure seamless coverage and edge-matching in the final tiled product. These rasters were created with a 1 meter cell size.

The DEMs that are created over large areas are reviewed in ArcGIS with hillshades and in Global Mapper. Hillshades allow the analyst to view the DEMs in 3D and to more efficiently locate and identify potential issues. The first review is done on the area DEMs as this increases the efficiency of any corrections that may be performed. Performing corrections on area DEMs allows the analyst to perform corrections on multiple tiles at once and helps prevent errors from occurring along individual tile seamlines. Analysts review the area DEMs for incorrect water elevations and artifacts that are introduced during the raster creation process.

The corrected and final area DEMs are clipped to individual tiles. Dewberry uses a proprietary tool that clips the area DEMs to each tile located within the final Tile Grid, names the clipped DEM to the Tile Grid Cell name, and verifies that final extents are correct. All individual tiles are loaded into Global Mapper for the last review. During this last review, an analsyt checks to ensure full, complete coverage, no issues along tile boundaries, tiles seamlessly edge-match, and that there are no remaining processing artifacts in the dataset.

The NOAA Office for Coastal Management (OCM) received the topographic/bathymetric files in LAS format from the University of William and Mary's Center for Geospatial Analysis. A number of LAS files were found to have corrupt GPS times and other unknown factors affecting header information. The files contained lidar easting, northing, elevation, intensity, return number, etc. The data was received in UTM coordinates, zone 18 North, referenced to the NAVD88 for vertical using the Geoid09 model. OCM performed the following processing for data storage and Digital Coast provisioning purposes:

1. The LAS files were converted to geographic horizontal coordinates and ellipsoidal vertical coordinates.

2. The LAS files were cleared of error points and variable length records removed.