Quantum Spatial541-752-1204517 SW 2nd St, Suite 400CorvallisOregon97333UShttp://www.quantumspatial.com20160425ArcGIS Metadata1.00.328Kevin RyanU.S. Army Corp of Engineers1222 Spruce St.St. LouisMO63103kevin.m.ryan@usace.army.milUS603-646-4106Kevin RyanShapefile2016-04-22vector digital dataSt_Marys_00001Quantum Spatial541-752-1204517 SW 2nd St., Suite 400CorvallisOregon97333UShttp://www.quantumspatial.comQuantum Spatial<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This shapefile represents 0.5 m contours based on LiDAR-derived terrain elevation data of the St. Mary's River Topo-Bathy 2015 LiDAR dataset. The major contour interval is labelled every 5m. The horizontal datum for this dataset is NAD83(2011), the vertical datum is NAVD88, Geoid 12B, and the data is projected in State Plane Michigan North FIPS 2111. Units are in Meters. Quantum Spatial collected the St. Mary's River Topo-Bathy 2015 LiDAR dataset for U.S. Army Corp of Engineers between 10/09/2015 and 11/29/2015.</SPAN></P></DIV></DIV></DIV>Provide support for high resolution terrain elevation data from the St. Mary's River Topo-Bathy 2015 LiDAR dataset. U.S. Army Corp of EngineersGreat LakesMichiganLiDAR, Contours, ShapefileContoursLiDAR-derivedShapefileGreat LakesMichiganMicrosoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.1.0.3035This data is projected in State Plane Michigan North FIPS 2111.1-83.366624-83.36142445.84981545.8481622015-10/092015-11/29St. Mary's River Topo-Bathy 2015 LiDARKevin RyanU.S. Army Corp of Engineers1222 Spruce St.St. LouisMO63103kevin.m.ryan@usace.army.milUS603-646-4106Kevin RyanPlease contact the U.S. Army Corp of Engineers for information regarding the use of this data.Acquisition. Quantum Spatial collected the St. Mary's River Topo-Bathy 2015 LiDAR data between 10/09/2015 and 11/29/2015. The survey used Riegl VQ820G and Leica ALS50 laser systems mounted in a Cessna 208B. Data was collected using a multi pulse flight plan. Near nadir scan angles were used to increase penetration of vegetation to ground surfaces. Ground level GPS and aircraft IMU were collected during the flight.
Riegl VQ820G Instrument Parameters:
Beam diameter: 40 cm,
Pulse rate: 284 kHz,
Maximum returns: unlimited,
Speed: 120 knots,
Overlap: 60 %,
Laser power: High,
Field of view (FOV): 42°,
Beam wavelength: 1064 nm,
Frequency of GPS sampling: 2 Hz,
Frequency of IMU sampling: 200 Hz,
Swath width: 323 m,
AGL: 400 m,
Average pulse density: 4 ppms
Leica ALS50 Instrument Parameters:
Beam diameter: 10 cm,
Pulse rate: 150 kHz,
Maximum returns: unlimited,
Speed: 120 knots,
Overlap: 60 %,
Laser power: 14.5 %,
Field of view (FOV): 44°,
Beam wavelength: 1064 nm,
Frequency of GPS sampling: 2 Hz,
Frequency of IMU sampling: 200 Hz,
Swath width: 323 m,
AGL: 400 m,
Average pulse density: 8 ppms2015-11-29T00:00:001. Flight lines and data were reviewed to ensure complete coverage of the study area and positional accuracy of the laser points.
2. Laser point return coordinates from the Leica ALS50 were computed using Waypoint Inertial Explorer and Leica Cloudpro software based on independent data from the LiDAR system, IMU, and aircraft. PosPac and RiProcess software were used in the computation of laser point return coordinates from the Riegl VQ820G.
3. The raw LiDAR file was assembled into flight lines per return with each point having an associated x, y, and z coordinate.
4. Visual inspection of swath to swath laser point consistencies within the study area were used to perform manual refinements of system alignment.
5. Custom algorithms were designed to evaluate points between adjacent flight lines. Automated system alignment was computed based upon randomly selected swath to swath accuracy measurements that consider elevation, slope, and intensities. Specifically, refinement in the combination of system pitch, roll and yaw offset parameters optimize internal consistency.
6. Noise (e.g., pits and birds) was filtered using postprocessing software, based on known elevation ranges and included the removal of any cycle slips.
7. Using TerraScan and Microstation, ground classifications utilized custom settings appropriate to the study area.
8. The corrected and filtered return points were compared to the RTK ground survey points collected to verify the vertical accuracy.
2016-04-22Processing notes specific to contour dataset:
1. Contour sinuosity was minimized through a model key point routine run on ground and bathymetric classified points.
2. Contour lines (0.5 m interval) were derived from model keypoints using MicroStation v8i and TerraModeler contour derivation tools.
3. Bathymetric void shapes were used to add confidence to the contour lines. Bathymetric voids are considered areas with no bathymetric returns within a 9 square meter area.
4. The elevation contour lines were intersected with the void shapes to add the confidence to the contour line shapefile. Contour lines over well covered areas with high confidence in the elevation data have a confidence code of high. Small areas of voids with lower confidence in the elevation data have a confidence code of low.
2016-04-22T00:00:00Shaded relief images have been visually inspected for data errors such as pits, border artifacts, and shifting.
LiDAR flight lines have been examined to ensure consistent elevation values across overlapping flight lines. The Root Mean Square Error (RMSE) of line to line relative accuracy for this dataset is 0.033 m. Please see the LiDAR data report for a discussion of the statistics related to this dataset.
Data was examined at a 1:2000 scale. Relative accuracy of the flight lines was assessed in Microstation using TerraMatch. RMSEm0.033 mLiDAR data has been collected and processed for all areas within the project study area.Flight plans are designed with sufficient sidelap to ensure there are no gaps between flight lines. Shaded relief images have been visually inspected for gaps. The Fundamental Vertical Accuracy (FVA) of this dataset, tested at 95% confidence level is 0.045 m. Please see the LiDAR data report for a discussion of the statistics related to this dataset.Fundamental Vertical Accuracy was assessed using 164 ground check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data. FVAm0.045 mVertical accuracy was also assessed using ground control points that were used in the calibration and post processing of the LiDAR point cloud as they still serve as a good indication of the overall accuracy of the LiDAR dataset. The Root Mean Square Error (RMSE) of the vertical accuracy of the LiDAR dataset as compared to ground control points is 0.024 m. Please see the LiDAR data report for a discussion of the statistics related to this dataset.3092 ground control points were collected and utilized in the calibration and post processing of the LiDAR data point cloud.RMSE0.024 mThe accuracy of the bathymetric returns, tested at 95% confidence level is 0.048 m. Please see the LiDAR data report for a discussion of the statistics related to this dataset.
Bathymetric accuracy was assessed using 334 check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data. 95% Confidencem0.0941.05000005000FGDC2016042519060700St_Marys_000018282103.2445008282500.000000124834.249700125000.00000010.328file://\\CVO-168\H\!!Deliverables!!\Vectors\Contours\St_Marys_00001.shpLocal Area NetworkProjectedGCS_NAD_1983_2011Linear Unit: Meter (1.000000)NAD_1983_2011_StatePlane_Michigan_North_FIPS_2111<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.1'><WKT>PROJCS["NAD_1983_2011_StatePlane_Michigan_North_FIPS_2111",GEOGCS["GCS_NAD_1983_2011",DATUM["D_NAD_1983_2011",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",8000000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-87.0],PARAMETER["Standard_Parallel_1",45.48333333333333],PARAMETER["Standard_Parallel_2",47.08333333333334],PARAMETER["Latitude_Of_Origin",44.78333333333333],UNIT["Meter",1.0]]</WKT><XOrigin>-28338200</XOrigin><YOrigin>-30062900</YOrigin><XYScale>123935682.76278117</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision></ProjectedCoordinateSystem>20160425190607002013041708405800FGDC CSDGM MetadataFALSEdatasetESRI10.1.0SimpleFALSE11FALSETRUELiDAR-derived ContourQuantum SpatialSt_Marys_00001Feature Class11FIDFIDOID400Internal feature number.EsriSequential unique whole numbers that are automatically generated.ShapeShapeGeometry000Feature geometry.EsriCoordinates defining the features.ElevationElevationElevation Quantum SpatialElevation in Meters, NAVD88, Geoid 12BDouble1900TypeTypeType Quantum SpatialType of contour, major (5m) or basic (0.5m)String25400ConfidConfidenceConfidence of the contour elevationQuantum SpatialContour lines over well covered areas with high confidence in the elevation data have a confidence code of high. Areas over small voids with lower confidence in the elevation data have a confidence code of low.String50011