Pulaski County 2010 - 2011 2 foot contours

The contours are smoothed according to project specifications. Smoothing is accomplished by removing sharp corners and jagged bends in the contour data. Depending on the level of aesthetics required, multiple iterations of smoothing may be performed. Proprietary tools in an ESRI environment are used to perform the smoothing iterations.

Data for the PAgis LiDAR project was acquired by Fugro EarthData, Inc. LiDAR collected at 1.0 points per square meter (1.0m GSD) for the Pulaski County Arkansas covering or portions of Pulaski and Faulkner Counties AR. This area was flown during snow free and leaf-off conditions. Fugro EarthData, Inc. flew and collected the LiDAR data. The project area requires LiDAR to be collected on average of 1.0 meter point spacing or better and vertical accuracy of 12.5 centimeters RMSE. Classified LAS were tested by Fugro EarthData for both vertical and horizontal accuracy. All data are seamless from one tile to the next. TerraSurv under contract to Fugro EarthData, Inc. successfully established ground control for the Pulaski AOI. A total of 26 ground control points in the Pulaski AOI were acquired. GPS was used to establish the control network. The horizontal datum was the North American Datum of 1983, 2007 adjustment (NAD83/2007). The vertical datum was the North American Vertical Datum of 1988 (NAVD88). The Fugro EarthData, Inc. acquisition team collected ALS60 derived lidar over the Pulaski AOI in the State of Arkansas with a 1m, nominal post spacing using a Piper Navajo aircraft. The collection for the entire project area was accomplished from December 27, 2011 through January 27, 2011. The collection was performed using a Leica ALS60 MPiA lidar system, serial numbers ALS142 and ALS113, including an inertial measuring unit (IMU) and a dual frequency GPS receiver. This project required 5 lifts of flight lines to be collected. The lines were flown at an average of 6,000 feet above mean terrain using a maximum pulse rate frequency of 123,700 Hz. The sensor had a 34 degree FOV and a scan rate of 40. 1. Lidar, GPS, and IMU data was processed together using lidar processing software. 2. The lidar data set for each flight line was checked for project area coverage and lidar post spacing was checked to ensure it meets project specifications. 3. The lidar collected at the calibration area and project area were used to correct the rotational, atmospheric, and vertical elevation differences that are inherent to lidar data. 4. Intensity rasters were generated to verify that intensity was recorded for each lidar point. 5. Lidar data was transformed to the specified project coordinate system. 6. By utilizing the ground survey data collected at the calibration site and project area, the lidar data was vertically biased to the ground. 7. Comparisons between the biased lidar data and ground survey data within the project area were evaluated and a final RMSE value was generated to ensure the data meets project specifications.

Contours created from LiDAR data often contain large amounts of noise. This noise is reduced by using contour model key points. However, additional noise is removed by removing small closed contours that do not represent the tops of hills or bottoms of depressions.

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 (10,000 ft x 10,000 ft). 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. Before the actual ground routine is run points with scan angles greater than plus or minus 19 degrees are classified to class 11, Withheld. Due to higher scan angles these points have the potential to introduce issues into the ground and are therefore not used in the final 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 3 ft of the hydrographic features are moved to class 10, an ignored ground due to breakline proximity. In addition to classes 1, 2, 9, 10 and 11, 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 Class 11 = Withheld Points The LAS header information was verified to contain the following: Class (Integer) GPS Week Time (0.0001 seconds) Easting (0.01 foot) Northing (0.01 foot) Elevation (0.01 foot) Echo Number (Integer 1 to 4) Echo (Integer 1 to 4) Intensity (8 bit integer) Flight Line (Integer) Scan Angle (Integer degree)

Using ArcGIS software, the contours are validated for correct topology, including must not intersect, must not self intersect, and must not have dangles. Contours are then manually reviewed with the 3D breaklines to ensure complete coverage, data integrity and that contours behave correctly around water bodies, water crossings, and elevated features such as overpasses.

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 and Inland Streams and Rivers were collected according to specifications for the USGS PAgis LiDAR Project.

2 FT contours were generated from the ESRI Terrain using ArcGIS software. Contours are labeled as intermediate or index with index contours set to every 10 feet.

Dewberry used GeoCue software to develop raster stereo models from the LiDAR intensity. The raster resolution was 1ft.

Contour model key points are generated from the final LAS tiles. Model key points are intelligently thinned points that still depict all necessary breaks and changes in a surface but remove unnecessary or redundant points. The contour model key points are converted to a multipoint file and stored in an Arc Geodatabase (GDB). The 3D breaklines, Inland Lakes and Ponds and Inland Streams and Rivers, are imported into the same GDB. An ESRI Terrain is generated from these inputs. The surface type of each input is as follows: Model key point (multipoints): Masspoints Inland Lakes and Ponds: Hard Replace Inland Streams and Rivers: Hard Line

2ft Contours

USGS PAgis LiDAR Project Data Dictionary