Bare_Earth_2015 2015-01-01 1.0 raster digital data OCTO District of Columbia Office of the Chief Technology Officer Bare Earth 2015 - 1 meter: This metadata record describes the data products derived from the LiDAR data for the DC OCTO 2015 LiDAR project covering approximately 80 square miles, in which its extents cover Arlington County in Washington DC. This project consists of deliverables in accordance with USGS v1.2 specifications and meets or exceeds the level of quality for QL1 (8 points per meter). The District of Columbia government requires a comprehensive range of GIS data and photogrammetric mapping to support a wide variety of applications through the DC GIS program. Due to technology advances, expanding user base needs, and aging data, DC GIS acquired new LIDAR data in spring 2015 to establish a more thorough and better quality core LIDAR dataset The LiDAR data products are suitable for 1 foot (or less) contour generation. Project Projection, Datums and Units. Projection - Maryland State Plane, FIPS 1900. Horizontal datum - North American Datum of 1983 (NAD83). Vertical datum - North American Vertical Datum of 1988 (NAVD88) using the latest geoid (Geoid12a). Units - METERS Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.4.0.5524 Digital Elevation Model (DEM) Bare Earth 2015 ALS70 Digital Surface Model (DSM) Washington DC point cloud Grid mapping LAS United States ground points LiDAR Water points Digital Elevation Model (DEM) Bare Earth ALS70 Digital Surface Model (DSM) point cloud Grid mapping LAS ground points LiDAR Water points DC Washington DC United States DC 2015 -180 180 -90 90 2015-04-01 2015-04-24 ground condition -77.122732 -76.900835 38.785485 39.001812 1 -77.137238 -76.891680 38.778050 39.009483 Mario Field Office of the Chief Technology Officer GIS IT Specialist - Data Team Leader mario.field@dc.gov 200 I Street SE 5th Floor District of Columbia Washington DC 20003 U.S.A. (202) 727-1761 Unknown 8:00 AM - 5:00 PM For data terms and conditions, go to http://dc.gov/page/terms-and-conditions-use-district-data The raw swath point cloud data was then calibrated using TerraMatch, a TerraSolid software, to correct relative bias in conjoining swaths that include roll, pitch, heading, Scale, and elevation. The swath data is then compared against the calibration control points and adjusted vertically to exceed the vertical accuracy requirements for the project. 2015-05-01 The classified point cloud was then subjected to water and ignored ground (breakline buffer) classification using the hydro features (breaklines) that were vectorized by Sanborn. The ignored ground (class 10) was buffered to 1ft. 2015-07-01 Leica's CloudPro software then combined the SBET and Raw Laser (.scn) files to produce raw point cloud swath data in LAS v1.2 format. 2015-05-01 Using a Leica Light Detection And Ranging (LiDAR) system, (>0.35 meter ground sample distance) data was collected over the DC OCTO AOI. Multiple returns were recorded for each laser pulse along with an intensity value for each return. The data acquisition occurred in 13 missions between April 1st and April 24th, 2015. During the LIDAR campaign, the Sanborn field crew conducted a GPS field survey to establish final coordinates of the ground base stations for final processing of the base-remote GPS solutions. 2015-04-01 The georeferenced lidar data is then classified and edited in Terrasolid (Terrascan) software. Data is classified to produce: Class 1: unclassified points, Class 2: ground points, Class 7: low point, Class 9: water points, Class 10: ignored ground, Class 11: Wihheld, Class 17: bridges, Class 18: high noise 2015-06-01 Airborne GPS data was differentially processed and integrated with the post processed IMU data to derive a Smoothed Best Estimate of Trajectory (SBET). IMU data provides information concerning roll, pitch and yaw of collection platform during collection event. IMU information allows the pulse vector to be properly placed in 3D space allowing the distance from the aircraft reference point to be properly positioned on the elevation model surface The SBET was used to reduce the LiDAR slant range measurements to a raw reflective surface for each flight line. Airborne GPS is differentially processed using the Inertial Explorer software by NovAtel Inc. 2015-04-01 The bare earth points of the processed lidar data are manually checked for quality- removing bridges, structures, filling culverts, and manually analyzing the Bare Earth surface by classifying features that belong in non-erroneous classification codes. 2015-06-01 Using LP360 software – a powerful software extension of ArcGIS, the Digital Elevation Models (DEMs) were autonomously processed using interpolated ground points from the edited bare earth within the LiDAR files to produce formatted, floating point 32 Bit IMAGINE Image files each with a cell size of 1 meter. The DEMs were created on a tile-by-tile bases conforming to an 800m by 800m grid. Pyramids were then created using the resampling of Nearest Neighbor. 2016-12-20 The tile definition defines discreet non-overlapping rectangular areas used as cut lines to break up the large classified lidar dataset into smaller, more manageable data tiles. 1200 Tile Definition 2015-01-01 ground condition The post processed lidar data has been projected and oriented in the specified coordinate system as an un-classified point cloud. The LAS v1.2 point cloud is then classified according to specifications and manually QC'd. 1200 Post processed lidar 2015-01-01 ground condition Post processed GPS/INS is applied to the lidar point data to georeference each point in the project coordinate system 1200 Post processed GPS/INS 2015-01-01 ground condition Aerial LiDAR and GPS/IMU data are recorded for the defined project area at an altitude, flight speed, scanner swath width and scanner pulse frequency to achieve the design goals of the project. LiDAR Data 2015-01-01 ground condition The classified lidar point cloud is used to derive the LAS v1.4 files. 1200 DEM 2015-01-01 ground condition Targeted ground control is used to create a digital control file and control report as well as QC check of LiDAR accuracy. Predefined points (NGS when available) within the project area are targeted. Ground control 2015-01-01 2015-01-01 ground condition LiDAR data is collected within the project area was processed and verified against control. LiDAR data is collected for the project area. Post processing of the simultaneously acquired GPS/INS is performed and applied to the laser returns to output a point cloud in the specified project coordinate system and datum's. The point cloud data is then subjected to automated classification routines to assign all points in the point cloud to ground, water, overlap and unclassified point classes. Anomalous laser returns that occur infrequently are removed entirely from the data set. Once clean bare earth points are established, DEMs are created using bare earth points and hydro-flattened using collected hydro features. The DEM surface is then compared to the NVA and VVA survey checkpoints. These accuracies must pass the specifications as defined by the SOW, as well as USGS v1.2 specifications for a QL1 dataset. The all returns point cloud was evaluated using a collection of 22 NVA class GPS surveyed checkpoints for the NVA report. The surface was compared to this checkpoint class yielding a better result than was required for the project. All NVA points were surveyed in areas of open terrain and represent a network of true bare earth surface checkpoints. DC OCTO Accuracy Report- NVA (Meters) --------- Report Disclaimer --------- This report does not guarantee accuracy. The report only reflects one statistical representation of the control points, LIDAR data and surface used. --------- Report Summary --------- Average dz -0.008 Minimum dz -0.050 Maximum dz +0.060 Average magnitude 0.023 Root mean square 0.028 Std deviation 0.027 ---------------------------------------------------------------------------------------- The DEM was evaluated using a collection of 22 NVA class GPS surveyed checkpoints. The DEM was compared to this checkpoint class yielding a better result than was required for the project. DC OCTO Accuracy Report- NVA (Meters) --------- Report Disclaimer --------- This report does not guarantee accuracy. The report only reflects one statistical representation of the control points, LIDAR data and surface used. --------- Report Summary --------- Average dz -0.013 Minimum dz -0.050 Maximum dz +0.050 Average magnitude 0.025 Root mean square 0.029 Std deviation 0.027 ---------------------------------------------------------------------------------------- The DEM was evaluated using a collection of 5 VVA class GPS surveyed checkpoints. The DEM was compared to this checkpoint class yielding a better result than was required for the project. DC OCTO Accuracy Report- VVA (Meters) --------- Report Disclaimer --------- This report does not guarantee accuracy. The report only reflects one statistical representation of the control points, LIDAR data and surface used. --------- Report Summary --------- Average dz -0.002 Minimum dz -0.020 Maximum dz +0.020 Average magnitude 0.014 Root mean square 0.015 Std deviation 0.016 Horizontal positional accuracy for LiDAR is dependent upon the quality of the GPS/INS solution, sensor calibration and ground conditions at the time of data capture. The standard system results for horizontal accuracy meet or exceed the project specified RMSE. Horizontal positional accuracy for LiDAR is dependent upon the quality of the GPS/INS solution, sensor calibration and ground conditions at the time of data capture. 0.5 Using the all returns point cloud and DEM data derived from the classified point cloud, the NVA and VVA values were computed. The vertical accuracy was tested with independent survey check points located in various terrain types within the DC OCTO AOI. The NVA was tested using 22 independent survey check points located in open, flat terrain types against the Raw Point Cloud. The survey checkpoints were distributed throughout the AOI. 0.028m RMSE, or 5.5cm NVA @ 95 percent confidence level in open terrain using RMSEz x 1.9600 http://opendata.dc.gov SDE Raster Dataset NA NA 2000 2000 DC OCTO 2015 LiDAR project LAS 1.4 Mario Field Office of the Chief Technology Officer GIS IT Specialist - Data Team Leader mario.field@dc.gov 5th Floor 200 I Street SE District of Columbia Washington DC 20003 U.S.A. (202) 727-1761 Unknown 8:00 AM - 5:00 PM NA 2015-01-01 NA unknown N/A USGS v1.2 Specifications EPSG 4.5(3.0.1) FGDC CSDGM Metadata 1200 1200 20230926 13395800 2016-12-20 15:16:04.71 FALSE 2016-12-20 14423900 1.0 FGDC editor:esri.dijit.metadata.editor 002 IMAGE.BARE_EARTH_2004 388113.707000 409381.707000 123376.928000 149058.928000 1 Server=sde; Service=sde:oracle$sde:oracle11g:dcgisprd; User=image; Version=SDE.DEFAULT ArcSDE Connection Projected GCS_North_American_1983 NAD_1983_StatePlane_Maryland_FIPS_1900 Linear Unit: Meter (1.000000) <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/10.4'><WKT>PROJCS[&quot;NAD_1983_StatePlane_Maryland_FIPS_1900&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,400000.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-77.0],PARAMETER[&quot;Standard_Parallel_1&quot;,38.3],PARAMETER[&quot;Standard_Parallel_2&quot;,39.45],PARAMETER[&quot;Latitude_Of_Origin&quot;,37.66666666666666],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,26985]]</WKT><XOrigin>-36747100</XOrigin><YOrigin>-29091500</YOrigin><XYScale>121236910.21292362</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>2</ZTolerance><MTolerance>2</MTolerance><HighPrecision>true</HighPrecision><WKID>26985</WKID><LatestWKID>26985</LatestWKID></ProjectedCoordinateSystem> Copy C:\Users\brian.putz\Downloads\BARE_EARTH_2015\BareEarth2015.tif E:\ProductionFiles\Lidar_2015\BareEarth2015.tif "Raster Dataset" # dataset 2016-12-20 1482263679553r38642336214331907 Shawn Benham Sanborn Map Co P.M. sbenham@sanborn.com Suite 100 1935 Jamboree Dr Colorado Springs CO 80920 U.S.A. 719.502.1296 8:00 AM - 5:00 PM MST None None