20220319 10180900 1.0 FALSE TerrainToRaster G:\WillCo_IL_Lidar_2021\Will_DTM.gdb\DTM\DTM_Terrain G:\WillCo_IL_Lidar_2021\rasters\Will_DTM FLOAT NATURAL_NEIGHBORS "CELLSIZE 1.0" 0 will_dtm file://U:\Workarea\Will\1st_Delivery\rasters\will_dtm Local Area Network 1002589.415572 1207209.415572 1650355.564475 1845260.564475 1 002 Projected GCS_NAD_1983_2011 Linear Unit: Foot_US (0.304801) NAD_1983_2011_StatePlane_Illinois_East_FIPS_1201_Ft_US <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/10.8'><WKT>PROJCS[&quot;NAD_1983_2011_StatePlane_Illinois_East_FIPS_1201_Ft_US&quot;,GEOGCS[&quot;GCS_NAD_1983_2011&quot;,DATUM[&quot;D_NAD_1983_2011&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,984250.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-88.33333333333333],PARAMETER[&quot;Scale_Factor&quot;,0.999975],PARAMETER[&quot;Latitude_Of_Origin&quot;,36.66666666666666],UNIT[&quot;Foot_US&quot;,0.3048006096012192]],VERTCS[&quot;NAVD88_height_(ftUS)&quot;,VDATUM[&quot;North_American_Vertical_Datum_1988&quot;],PARAMETER[&quot;Vertical_Shift&quot;,0.0],PARAMETER[&quot;Direction&quot;,1.0],UNIT[&quot;Foot_US&quot;,0.3048006096012192]]</WKT><XOrigin>-17463800</XOrigin><YOrigin>-46132600</YOrigin><XYScale>137244822.07846552</XYScale><ZOrigin>-100000</ZOrigin><ZScale>3048.0060960121923</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.0032808333333333331</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>103037</WKID><LatestWKID>6455</LatestWKID><VCSWKID>105703</VCSWKID><LatestVCSWKID>6360</LatestVCSWKID></ProjectedCoordinateSystem> 32 FALSE None 1 GRID TRUE continuous floating point -3.4028235e+38 20220331 13333800 20220726 9241500 FGDC 150000000 5000 Ayres Associates (608) 443-1200 5201 E Terrace Drive, Suite 200 Madison Wisconsin 53718 US 20220331 ArcGIS Metadata 1.0 IL_Will_DTM_2021 2021-08-13 Ayres Associates Lidar point cloud <DIV STYLE="text-align:Left;"><DIV><P><SPAN>The Will County, IL lidar project area covers approximately 887 square miles. The lidar data was acquired at an aggregate nominal point density (ANPD) of 10. Project specifications are based on Will County requirements. The data was developed based on a horizontal projection/datum of NAD83(2011) / Illinois State Plane East Zone (ftUS) (EPSG Code: 3435), and vertical datum of NAVD88 - Geoid18 (US Survey Feet)--ISGS comment: all the data uses Geoid 18--. LiDAR data was acquired using a Optech Galaxy T2000 sensor from March 29, 2021 to April, 13, 2021 in 8 total lifts. Acquisition occurred with leaves absent from deciduous trees, when no snow was present on the ground, and with rivers at or below normal levels. Note: ISGS QAQC review found that there are numerous noise points on the DSM, making that DSM unusable in some areas.</SPAN></P></DIV></DIV> Will County City of Joilet Illinois ISO 19115 Topic Categories elevation Elevation Data Lidar LAS Point Cloud Remote Sensing Model Elevation Data Lidar LAS Point Cloud Remote Sensing Will County City of Joilet Model Illinois elevation No restrictions apply to this data. <DIV STYLE="text-align:Left;"><DIV><P><SPAN>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 its limitations.</SPAN></P></DIV></DIV> Terrasolid ground condition 2021-03-29 2021-04-13 -88.266693 -87.516512 41.195142 41.732882 1 -88.266693 -87.516512 41.732882 41.195142 Will County is located to the south and west of the city of Chicago in northeastern Illinois. Will County is bordered by Cook, DuPage, Kendall, Grundy and Kankakee counties in Illinois, and Lake County in Indiana. The latest Census projection estimates Will County’s population as just under 691,000. Will County is 849 square miles where just over 12 square miles is not land based. Our project area will consist of approximately 887 square miles as referenced by the county buffer polygon. Will County agencies that will directly benefit from this effort to acquire LiDAR include the Information, Communication, & Technology (ICT) Department, 9-1-1, Assessor’s Office, Board of Review, Geographic Information Systems Division, Division of Transportation, Emergency Management Agency (EMA), Land Use Department, Forest Preserve District, Health Department, and Sheriff. As part of Will County’s ongoing regional collaborative presence, external agencies and the general public will also realize benefits and access to this data as well. Will County, Ayers Inc. Last metadata review date: 20220331 None None Data covers the entire area specified for this project. There are numerous noise points that make the DSM unusable in some areas. These LAS data files include all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is complete and data passes Vertical Accuracy specifications. 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. These 63 points 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. Elevations from the unclassified lidar surface were measured for the x,y location of each check point. Elevations interpolated from the lidar surface were then compared to the elevation values of the surveyed control points. AccuracyZ has been prepared 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. Tested 0.059 meters NVA at a 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA). These 63 survey points were not used in the calibration or post processing of the lidar point cloud data 0.059 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 Leica 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 is 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 match 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 check points after the z correction to ensure the requirement of NVA = 19.6 cm 95% Confidence Level (Required Accuracy) was met. Point classification was performed according to USGS Lidar Base Specification 2.1, and breaklines were collected for water features. Bare earth DEMs were exported from the classified point cloud using collected breaklines for hydroflattening. 2021-08-13 LAS Point Cloud Classification: LiDAR data processing for the point cloud deliverable consists of classifying the LiDAR using a combination of automated classification and manual edit/reclassification processes. On most projects the automated classification routines will correctly classify 90-95 percent of the LiDAR points. The remaining 5-10 percent of the bare earth ground class must undergo manual edit and reclassification. Because the classified points serve as the foundation for the Terrain, DEM and breakline products, it is necessary for the QA/QC supervisor to review the completed point cloud deliverables prior to the production of any additional products. The following workflow steps are followed for automated LiDAR classification: 1. Lead technicians review the group of LiDAR tiles to determine which automated classification routines will achieve the best results. Factors such as vegetation density, cultural features, and terrain can affect the accuracy of the automated classification. The lead technicians have the ability to edit or tailor specific routines in order to accommodate the factors mentioned above, and achieve the best results and address errors. 2. Distributive processing is used to maximize the available hardware resources and speed up the automated processing as this is a resource-intensive process. 3. Once the results of the automated classification have been reviewed and passed consistent checks, the supervisor then approves the data tiles for manual classification. The following workflow steps are followed for manual edits of the LiDAR bare earth ground classification: 1. LiDAR technicians review each tile for errors made by the automated routines and correctly address errors any points that are in the wrong classification. By methodically panning through each tile, the technicians view the LiDAR points in profile, with a TIN surface, and as a point cloud. 2. Any ancillary data available, such as Google Earth, is used to identify any features that may not be identifiable as points so that the technician can make the determination to which classification the feature belongs. The QA/QC processes for the LiDAR processing phase consist of: 1. The lead technician reviews all automated classification results and adjust the macros as necessary to achieve the optimal efficiency. This is an iterative process, and the technician may need to make several adjustments to the macros, depending upon the complexity of the features in the area being processed.  During the manual editing process, the LiDAR technicians use a system of QA, whereby they check each other’s edits. This results in several benefits to the process:  There is a greater chance of catching minor blunders  It increases communication between technicians on technique and appearance  Solutions to problems are communicated efficiently  To ensure consistency across the project area, the supervisor reviews the data once the manual editing is complete. For this phase of a project, the following specifications are checked against: • Point cloud – all points must be classified according to the USGS classification standard for LAS. The all-return point cloud must be delivered in fully-compliant LAS version 1.4. • LAS files will use the Spatial Reference Framework according to project specification and all files shall be projected and defined. • General Point classifications:  Class 1. Processed, but unclassified  Class 2. Bare Earth  Class 7. Noise  Class 9. Water  Class 17. Bridge Decks  Class 18. High Noise  Class 20. Ignored ground (Breakline proximity)--ISGS comment: points are in classes 0,5,6,10,14 and 15 and not identified | All of the class 7 points should be flagged as withheld -- • Outliers, noise, blunders, duplicates, geometrically unreliable points near the extreme edge of the swath, and other points deemed unusable are to be identified using the "Withheld" flag. This applies primarily to points which are identified during pre-processing or through automated post-processing routines. Subsequently identified noise points may be assigned to the standard Noise Classes (Class 7). • Point classification shall be consistent across the entire project. 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