2014 USGS NRCS Lidar: Choctaw and Washington Counties, AL

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, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. They will be in an orthometric datum.

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.

This graphic displays the footprint for this lidar data set.

Link to data set report.

This data set is the project specified acquired point cloud data.

This data set is the project specified lidar deliverables.

This data set is the project specified acquired ground control and QAQC control data.

This data set is the project specified acquired ground control and QAQC control data.

Using one Leica ALS70 (lidar) and one Optech Gemini (lidar) system on board a Cessna 404 and Cessna 310 aircraft respectively, high density data, at a nominal pulse spacing (NPS) of 0.7 meters, were collected for this task order (approximately 7,400 square miles). Leica Specs- AGL = 1981 meters - Aircraft Speed = 150 Knots, Field of View (Full) = 40 degrees, Pulse Rate = 272 kHz, Scan Rate = 41.6 Hz, with an average side lap of 25%. Optech Specs- AGL = 1524 meters - Aircraft Speed = 130 Knots, Field of View (Full) = 24 degrees, Pulse Rate = 125 kHz, Scan Rate = 46 Hz, with an average side lap of 30%. Multiple returns were recorded for each laser pulse along with an intensity value for each return. Forty-one (41) missions were flown between January 7, 2014 and February 15, 2014. Twelve (12) Global Navigation Satellite System (GNSS) Base Stations were used in support of the lidar data acquisition. Specific information regarding latitude, longitude, and ellipsoid height to the L1 phase center is included in the lidar processing report. The geoid used to reduce satellite derived elevations to orthometric heights was GEOID12A. Data for the task order is referenced to the UTM Zone 16N, North American Datum of 1983 (2011), and NAVD88, in meters. Once the data acquisition and GPS processing phases are complete, the lidar data was processed immediately to verify the coverage had no voids. The GPS and IMU data was post processed using differential and Kalman filter algorithms to derive a best estimate of trajectory. The quality of the solution was verified to be consistent with the accuracy requirements of the project. The SBET was used to reduce the lidar slant range measurements to a raw reflective surface for each flight line. The coverage was classified to extract a bare earth digital elevation model (DEM) and separate last returns. The ALS70/Optech Gemini calibration and system performance is verified on a periodic basis using Woolpert's calibration range. The calibration range consists of a large building and runway. The edges of the building and control points along the runway have been located using conventional survey methods. Inertial measurement unit (IMU) misalignment angles and horizontal accuracy are calculated by comparing the position of the building edges between opposing flight lines. The scanner scale factor and vertical accuracy is calculated through comparison of lidar data against control points along the runway. Field calibration is performed on all flight lines to refine the IMU misalignment angles. IMU misalignment angles are calculated from the relative displacement of features within the overlap region of adjacent (and opposing) flight lines. The raw lidar data is reduced using the refined misalignment angles.

Ground control and QAQC control point survey for the Mississippi AOI was performed by Woolpert surveyors, to support the USGS-NRCS Laurel MS 0.7m NPS Lidar project. All surveys were performed in such a way as to achieve ground control that supports lidar data at 9.25 cm RMSE accuracy and satisfy a local network accuracy of 5 cm at a 95% confidence level. All ground control survey field activities took place from 11/13/2013 thru 11/23/13. Woolpert collected control data for data processing as supplemental QAQC points. The supplemental QAQC points were collected to be used in independent accuracy testing. The field crew utilized Real-Time Kinematic (RTK) GPS surveying throughout most of the ground control data collection process. Using RTK GPS techniques, observations were performed on 26 ground control points and 161 quality control check points. The survey was conducted using a 1-second epoch rate, in a fixed solution RTK mode, with each observation lasting between 60 to 180 seconds. Each station was occupied twice to insure the necessary horizontal and vertical accuracies were being met for this photogrammetric project. In addition to the RTK GPS techniques, the project field crew utilized rapid-static (RS) GPS surveying techniques to establish RTK Base stations within areas lacking sufficient NGS control monument stations. Using Rapid-Static GPS techniques, observations were performed on one (2) RTK Base stations (110 & 111). The survey was conducted at a 5-second sync rate with each observation lasting between 40-360 minutes. All horizontal GPS control was based on UTM Zone 16N, NAD83 (2011) expressed in meters. The vertical datum used for this project was based on the North American Vertical Datum of 1988 (NAVD88), GEOID12A, also expressed in meters.

Ground control and QAQC control point survey for the Alabama AOI was performed by Magnolia River surveyors, to support the USGS-NRCS Laurel MS 0.7m NPS Lidar project. All surveys were performed in such a way as to achieve ground control that supports lidar data at 9.25 cm RMSE accuracy and satisfy a local network accuracy of 5 cm at a 95% confidence level. All ground control survey field activities took place from 01/24/2014 thru 04/03/14. Magnolia River surveyors collected control data for data processing as supplemental QAQC points. The supplemental QAQC points were collected to be used in independent accuracy testing. The field crew utilized Real-Time Kinematic (RTK) GPS surveying utilizing the Alabama Departemnt of Transportation (ALDOT) Continually Operating Reference Station (CORS) network, via the internet using TCP/IP protocol and MiFi cellular connection. ALDOT provides single base corrections from the nearest operating GPS reference station. Using RTK GPS techniques, observations were performed on 21 ground control points and 115 quality control check points. The survey was conducted using a 1-second epoch rate, in a fixed solution RTK mode, with each observation lasting between 60 to 180 seconds. Each station was occupied twice to insure the necessary horizontal and vertical accuracies were being met for this photogrammetric project. A Sokkia Set330R3 total station in combination with a Trimble TSC3 data collector was used in areas where sufficient satellite coverage was not available for some quality control check points. All horizontal GPS control was based on UTM Zone 16N, NAD83 (2011) expressed in meters. The vertical datum used for this project was based on the North American Vertical Datum of 1988 (NAVD88), GEOID12A, also expressed in meters.

The individual flight lines were inspected to ensure the systematic and residual errors have been identified and removed. Then, the flight lines were compared to adjacent flight lines for any mismatches to obtain a homogenous coverage throughout the project area. The point cloud underwent a classification process to determine bare-earth points and non-ground points utilizing "first and only" as well as "last of many" lidar returns. This process determined Default (Class 1), Ground (Class 2), Noise (Class 7), Water (Class 9), Ignored Ground (Class 10), Overlap Default (Class 17) and Overlap Ground (Class 18). The bare-earth (Class 2 - Ground) lidar points underwent a manual QA/QC step to verify the quality of the DEM as well as a peer-based QC review. This included a review of the DEM surface to remove artifacts and ensure topographic quality. Classification of water (class 9) and ignored ground (class 10) was completed via the use of the hydrologic breaklines collected for the hydro-flattening phase. The overlap classes were determined by first identifying the overlapping areas and reclassifying the LAS data by offset from a corridor. This allows the returns located on the edge of the swath to be removed from the bare earth coverage in an effort to produce a more uniform data density. The returns determined to be overlap are then further classified to produce overlap default (class 17) and overlap ground (class 18). The surveyed ground control points are used to make vertical adjustments to the data set and to perform the accuracy checks and statistical analysis of the lidar dataset. Supervisory QC monitoring of work in progress and completed editing ensured consistency of classification character and adherence to project requirements across the entire project area. The resulting deliverables for this task order consist of classified LAS file in LAS 1.2 format, Raw Swath LAS files in LAS 1.2 format, 1 meter pixel size DEM files in ERDAS IMG format, 1 meter pixel size 8-bit Intensity files in GeoTIFF format, and Hydrologic Breakline data in ESRI shape file format.

The Alabama counties for the full data set were not found at the USGS National Map, nor could copies of the data be found. The Alabama Department of Transportation provided NOAA Office for Coastal Management a copy of the data for the two counties. These were received in proprietary *.zlas format. The data were converted to *.laz format using the LASliberator software (https://github.com/LASliberator/LASliberator). The data were in NAD83(2011) Alabama State Plane West (US survey ft) projection with vertical feet. This is different than the original UTM data and there was no record of the transformation. Several issues about the dataset were noted by USGS, including:

Global Encoding bit is set to 0 instead of 1

Point Misclassification (Buildings): 2 buildings remain present and are classified as ground.

Point Misclassification (Vegetation): Vegetation is systematically classified as bridges in the point cloud.

The global encoding bit was set to 1 using lasinfo. Class 17, with vegetation and bridge decks, was reset to class 1 (unclassified). The lasclassify program was run to classify vegetation and buildings. Any real bridge decks are now in the unclassified class. The two buildings classified as ground were not found or changed.

For ingest into the NOAA Data Access Viewer, the data were unprojected to geographic coordinates and the vertical component was converted to ellipsoid heights in meters by removing the GEOID12A model.

The global encoding bit was found to be incorrect (0 indicating GPS seconds of the week) and was changed to reflect adjusted GPS seconds.