Quantum Spatial, Inc. 20190617 Lidar point cloud Product: This lidar data set includes unclassified swath LAS 1.4 files, classified LAS 1.4 files, breaklines, digital elevation models (DEMs), and intensity imagery. Geographic Extent: One county in Indiana, covering approximately 434 total square miles. Dataset Description: The Hamilton County, Indiana 2016 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD83 (2011), Indiana State Plane East, US survey feet and vertical datum of NAVD88 (GEOID12B), US survey feet. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 1,936 individual 2,500 feet x 2,500 feet tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 2,500 feet x 2,500 feet schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in spring of 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 39 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 53 independent accuracy checkpoints, 32 in Bare Earth and Urban landcovers (32 NVA points), 21 in Tall Weeds categories (21 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data. To acquire detailed surface elevation data for use in conservation planning, design, research, floodplain mapping, dam safety assessments and elevation modeling, etc. Classified LAS files are used to show the manually reviewed bare earth surface. This allows the user to create intensity images, breaklines and raster DEMs. The purpose of these LiDAR data was to produce high accuracy 3D hydro-flattened digital elevation models (DEMs) with a 3.125-foot cell size. These raw LiDAR point cloud data were used to create classified LiDAR LAS files, intensity images, 3D breaklines, and hydro-flattened DEMs as necessary. CONTRACTOR: Quantum Spatial; Lidar data were acquired and calibrated by Quantum Spatial. All follow-on processing was completed by the prime contractor. USGS-NGP Base Specification v1.2 Leica ALS 70 4 0.68 2.14 0.68 2.14 2000 170 20 53.4 273 4 0.44 1064 1 0.22 1455.88 10.94 GEOID12B NAD83 (2011) Indiana State Plane East, US survey feet 0 0.104 32 1.4 6 Withheld (ignore) points were identified in these files using the standard LAS Withheld bit Swath "overage" points were identified in these files using the standard LAS overlap bit 16 1 Processed, but Unclassified 2 Bare-Earth Ground 7 Low Noise 8 Model Key Points 9 In-land Water 10 Ignored Ground 17 Bridge Decks 20160321 20160322 ground condition Complete None planned -86.25069095 -85.85593198 40.22440278 39.92113439 None Model LAS Point Cloud Remote Sensing Elevation Data Lidar Hydrology Breaklines Raster DEM Intensity Image Tile Index None Indiana Hamilton County No restrictions apply to these data. None. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of their limitations. Data cover the entire area specified for this project. All files are inspected to ensure that they conform to the specified file naming conventions, all files load in their correct geographic position, all files conform to the project specifications for file standard and content. The project specifications require that only Non-Vegetated Vertical Accuracy (NVA) be computed for raw LiDAR point cloud swath files. The required accuracy (ACCz) is: 19.6 cm at a 95% confidence level, derived according to NSSDA, i.e., based on RMSE of 10 cm in the "bare earth" and "urban" land cover classes. The NVA was tested with 32 checkpoints located in bare earth and urban (non-vegetated) areas. These checkpoints were not used in the calibration or post processing of the LiDAR point cloud data. The checkpoints were distributed throughout the project area and were surveyed using GPS techniques. See survey report for additional survey methodologies. Elevations from the unclassified LiDAR surface were measured for the x,y location of each checkpoint. Elevations interpolated from the LiDAR surface were then compared to the elevation values of the surveyed control points. AccuracyZ has been tested to meet 19.6 cm or better Non-Vegetated Vertical Accuracy at 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines. The project specifications require the accuracy (ACCz) of the derived DEM be calculated and reported in two ways: 1. The required NVA is: 19.6 cm at a 95% confidence level, derived according to NSSDA, i.e., based on RMSE of 10 cm in the "bare earth" and "urban" land cover classes. This is a required accuracy. The NVA was tested with 32 checkpoints located in bare earth and urban (non-vegetated) areas. 2. Vegetated Vertical Accuracy (VVA): VVA shall be reported for "tall weeds" land cover classes. The target VVA is: 29.4 cm at the 95th percentile, derived according to ASPRS Guidelines, Vertical Accuracy Reporting for LiDAR Data, i.e., based on the 95th percentile error in all vegetated land cover classes combined. This is a target accuracy. The VVA was tested with 21 checkpoints located in forested and tall weeds (vegetated) areas. The checkpoints were distributed throughout the project area and were surveyed using GPS techniques. See survey report for additional survey methodologies. AccuracyZ has been tested to meet 19.6 cm or better Non-Vegetated Vertical Accuracy at 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines. 0.104 Tested 0.104 meters NVA at a 95% confidence level using 32 independent survey points located in open terrain. The survey check points were distributed throughout the project area. The 32 independent check points were surveyed using GPS techniques. See survey report for additional survey methodologies. Elevations from the unclassified LiDAR surface were measured for the x,y location of each checkpoint. Elevations interpolated from the LiDAR surface were then compared to the elevation values of the surveyed control points. The root mean square error vertical (RMSEz) was computed to be 0.053 meters. AccuracyZ has been tested to meet 19.6 cm NVA at 95-percent confidence level using (RMSEz * 1.9600) as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using American Society of Photogrammetry and Remote Sensing (ASPRS) Guidelines. 0.095 Tested 0.095 meters NVA at a 95% confidence level using 32 independent survey points located in open terrain. The survey check points were distributed throughout the project area. The 32 independent check points were surveyed using GPS techniques. See survey report for additional survey methodologies. Elevations from the unclassified LiDAR surface were measured for the x,y location of each checkpoint. Elevations interpolated from the LiDAR surface were then compared to the elevations values of the surveyed control points. The root mean square error vertical (RMSEz) was computed to be 0.049 meters. AccuracyZ has been tested to meet 19.6 cm NVA at 95-percent confidence level using (RMSEz * 1.9600) as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using American Society of Photogrammetry and Remote Sensing (ASPRS) Guidelines. 0.206 Tested 0.206 meters VVA was calculated using 21 checkpoints located in vegetation at the 95th percentile, derived according to ASPRS Guidelines, Vertical Accuracy Reporting for LiDAR Data. Tested against the DEM. Raw Data and Boresight Processing: The boresight for each lift was done individually as the solution may change slightly from lift to lift. The following steps describe the Raw Data Processing and Boresight process: 1) Technicians processed the raw data to LAS format flight lines using the final GPS/IMU solution. This LAS data set was used as source data for boresight. 2) Technicians first used Quantum Spatial, Inc. proprietary and commercial software to calculate initial boresight adjustment angles based on sample areas selected in the lift. These areas cover calibration flight lines collected in the lift, cross tie, and production flight lines. These areas are well distributed in the lift coverage and cover multiple terrain types that are necessary for boresight angle calculation. The technician then analyzed the results and made any necessary additional adjustment until it was acceptable for the selected areas. 3) Once the boresight angle calculation was completed for the selected areas, the adjusted settings were applied to all of the flight lines of the lift and checked for consistency. The technicians utilized commercial and proprietary software packages to analyze how well flight line overlaps matched for the entire lift and adjusted as necessary until the results met the project specifications. 4) Once all lifts were completed with individual boresight adjustment, the technicians checked and corrected the vertical misalignment of all flight lines and also the matching between data and ground truth. The relative accuracy was less than or equal to 7 cm RMSEz within individual swaths and less than or equal to 10 cm RMSEz or within swath overlap (between adjacent swaths). 5) The technicians ran a final vertical accuracy check of the boresighted flight lines against the surveyed checkpoints after the z correction to ensure the requirement of NVA = 19.6 cm 95% Confidence Level (Required Accuracy) was met. 2016 LAS Point Classification: The point classification was performed as described below. The bare earth surface was manually reviewed to ensure correct classification on the Class 2 (Ground) points. After the bare-earth surface was finalized, it was then used to generate all hydro-breaklines through heads-up digitization. All ground (ASPRS Class 2) LiDAR data inside of the Lake Pond and Double Line Drain hydro-flattened breaklines were then classified to Water (ASPRS Class 9) using TerraScan macro functionality. A buffer of 1 meter was also used around each hydro-flattened feature to classify these ground (ASPRS Class 2) points to Ignored ground (ASPRS Class 10). All Lake Pond Island and Double Line Drain Island features were checked to ensure that the ground (ASPRS Class 2) points were reclassified to the correct classification after the automated classification was completed. All overlap data was processed through automated functionality provided by TerraScan to classify the overlapping flight line data to approved classes by USGS. The overlap data was classified using standard LAS overlap bit. These classes were created through automated processes only and were not verified for classification accuracy. Due to software limitations within TerraScan, these classes were used to trip the withheld bit within various software packages. All data were manually reviewed and any remaining artifacts removed using functionality provided by TerraScan and TerraModeler. Global Mapper was used as a final check of the bare earth dataset. GeoCue was then used to create the deliverable industry-standard LAS files for both the All Point Cloud Data and the Bare Earth. Quantum Spatial, Inc. proprietary software was used to perform final statistical analysis of the classes in the LAS files, on a per tile level to verify final classification metrics and full LAS header information. 2016 Hydro-Flattened Breakline Processing: Class 2 (ground) LiDAR points were used to create a bare earth surface model. The surface model was then used to heads-up digitize 2D breaklines of inland streams and rivers with a 100-foot nominal width and inland ponds and lakes of 2 acres or greater surface area. Elevation values were assigned to all Inland Ponds and Lakes, Inland Pond and Lake Islands, Inland Stream and River Islands, using TerraModeler functionality. Elevation values were assigned to all inland streams and rivers using Quantum Spatial, Inc. proprietary software. All Ground (ASPRS Class 2) LiDAR data inside of the collected inland breaklines were then classified to Water (ASPRS Class 9) using TerraScan macro functionality. A buffer of 1 meter was also used around each hydro-flattened feature. These points were moved from ground (ASPRS Class 2) to Ignored Ground (ASPRS Class 10). The breakline files were then translated to Esri file geodatabase format using Esri conversion tools. Breaklines were reviewed against LiDAR intensity imagery to verify completeness of capture. All breaklines were then compared to TINs (triangular irregular networks) created from ground only points prior to water classification. The horizontal placement of breaklines was compared to terrain features and the breakline elevations were compared to LiDAR elevations to ensure all breaklines matched the LiDAR within acceptable tolerances. Some deviation was expected between breakline and LiDAR elevations due to monotonicity, connectivity, and flattening rules that were enforced on the breaklines. Once completeness, horizontal placement, and vertical variance were reviewed, all breaklines were reviewed for topological consistency and data integrity using a combination of Esri Data Reviewer tools and proprietary tools. 2016 Hydro-Flattened Raster DEM Processing: Class 2 (Ground) LiDAR points in conjunction with the hydro-breaklines were used to create a 3.125 feet hydro-flattened raster DEM. Using automated scripting routines within ArcMap, an ERDAS Imagine .IMG file was created for each tile. Each surface was reviewed using Global Mapper to check for any surface anomalies or incorrect elevations found within the surface. 2016 Intensity Image Generation Processing: GeoCue software was used to create the deliverable intensity images. All overlap classes were ignored during this process. This helps to ensure a more aesthetically pleasing image. The GeoCue software was then used to verify full project coverage as well. TIF/TWF files were then provided as the deliverable for this dataset requirement. 2016 Tile Index Processing: Tiles were created using a 0,0 origin point to ensure proper divisibility of raster and image cells. A 2,500 feet x 2,500 feet tile size was used as called for in the Task Order. Tile index was output in Esri shapefile format. 2016 Point State Plane Coordinate System 1983 1301 0.9999666666666667 -85.66666666666667 37.5 328083.3333333333 820208.3333333333 coordinate pair 0.01 0.01 US survey feet NAD83 (2011) Geodetic Reference System 80 6378137.0 298.257222101 NAVD88 (GEOID12B) 0.01 US survey feet Explicit elevation coordinate included with horizontal coordinates 20190617 Quantum Spatial mailing and physical

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Lexington KY 40503 USA 859-277-8700 859-277-8901 jbowen@quantumspatial.com Monday through Friday 8:00 AM to 5:00 PM (Eastern Time) If unable to reach the contact by telephone, please send an email. You should get a response within 24 hours. FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 None. None. None. Unclassified NONE