Sanborn Map Company, Inc. 20240109 Lidar point cloud Product: These lidar data are processed Classified LAS 1.4 files, formatted to 4025 individual 1500 m x 1500 m tiles clipped to the DPA; used to create intensity images, 3D breaklines, hydro-flattened DEMs, and all-return MSHRs as necessary. Geographic Extent: Columbia, Jefferson, Lewis, Rensselaer, Saratoga, Warren, and Washington Counties New York, covering approximately 3279 square miles. Dataset Description: The 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 2022, Revision A. The data was developed based on a horizontal projection/datum of NAD83(2011), UTM Zone 18N, Meters and vertical datum of NAVD88 (GEOID18), Meters. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 4025 individual 1500 m x 1500 m tiles clipped to the DPA, as tiled intensity images, as tiled bare-earth DEMs, as tiled all-return MSHRs; all tiled to the same 1500 m x 1500 m schema. Ground Conditions: Lidar was collected in fall 2022 and spring 2023, 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, Sanborn Map Company, Inc., established a total of 41 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. An additional 139 independent accuracy check points, 96 in Bare Earth and Urban landcovers (96 NVA points), 43 in Tall Grass and Brushland/Low Trees categories (43 VVA points), were used to assess the vertical accuracy of the data. These check points 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 DEM. The purpose of these lidar data was to produce high accuracy 3D hydro-flattened Digital Elevation Model (DEM) with a 1 m cell size. These lidar point cloud data were used to create intensity images, 3D breaklines, hydro-flattened DEMs, and all-return MSHRs as necessary. CONTRACTOR: Sanborn Map Company, Inc. U.S. Geological Survey (USGS) - National Geospatial Program (NGP) Lidar Base Specification 2022, Revision A Leica TerrainMapper 1 0.66 2.23 0.52 3.6 3350 160 15 86.9 730 4 0.78 1064 1 0.25 2439 20 National Geodetic Survey (NGS) Geoid18 U.S. Geological Survey (USGS) - National Geospatial Program (NGP) Lidar Base Specification 2022, Revision A Riegl VQ-1560 II 1 0.67 2.2 0.52 3.6 2190 170 58.52 178 856 4 0.41 1064 1 0.25 2453 20 National Geodetic Survey (NGS) Geoid18 0 0 0 1.4 6 Withheld (ignore) points were identified in these files using the standard LAS Withheld bit. Swath "overage" points were not identified in these files using the standard LAS overlap bit. 16 1 Processed, but Unclassified 2 Bare Earth Ground 7 Low Noise 9 Water 17 Bridge Decks 18 High Noise 20 Ignored Ground 20221108 20230415 ground condition Complete None planned -76.08359028 -73.21516608 44.26170203 41.97111802 4901000.000 4648000.000 413500.000 642500.000 None Model LAS Point Cloud Remote Sensing Elevation Data Lidar None New York Columbia County Jefferson County Lewis County Rensselaer County Saratoga County Warren County Washington 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 its limitations. Acknowledgement of the U.S. Geological Survey would be appreciated for products derived from these data. Leica HexMap; Riegl RiProcess; GeoCue; Windows 10 Data covers the DPA specified for this project. 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 of good quality and data passes Non-Vegetated Vertical Accuracy specifications. This dataset was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a __cm RMSEx / RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuract = +/- __cm at a 95% confidence level. This data set was tested to meet ASPRS Positional Accuracy Standard for Digital Geospatial Data (2014) for a 10cm RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz = __cm, equating to +/- __cm at 95% confidence level. Actual VVA accuracy was found to be +/- __cm at the 95th percentile. The boresight was completed prior to project execution. The following steps describe the Raw Data Processing process: 1) Technicians processed the raw data to LAS format flight lines using the final GNSS/IMU solution. This LAS data set was used as source data for lidar matching. 2) 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. 3) Once all lifts were completed with lidar matching, 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 6 cm RMSEz within individual swaths and less than or equal to 8 cm RMSEz or within swath overlap (between adjacent swaths). 4) The technicians ran a final vertical accuracy check of the 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, and breaklines were collected for water features. Bare-earth DEMs were exported from the classified point cloud using collected breaklines for hydroflattening. 2467_USGS_NY_Hudson_Lidar_ControlSurvey 2023 LAS Point Classification: The point classification is performed as described below. The bare-earth surface is then manually reviewed to ensure correct classification on the Class 2 (Ground) points. After the bare-earth surface is finalized, it is then used to generate all hydro-breaklines through heads-up digitization. All Class 2 (Ground) lidar data inside of the Lake Pond and Double Line Drain hydro-flattened breaklines were then classified to Class 9 (Water) using LP360 functionality. A buffer of 1 m was also used around each hydro-flattened feature to classify these Class 2 (Ground) points to Class 20 (Ignored Ground). All Lake Pond Island and Double Line Drain Island features were checked to ensure that the Class 2 (Ground) points were reclassified to the correct classification after the automated classification was completed. All data was manually reviewed and any remaining artifacts removed using functionality provided by LP360, 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. Sanborn Map Company, 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. 2023 Data was tested at 0.52 meter aggregate nominal pulse spacing and at 3.6 aggregate points per meter. The aggregate nominal pulse spacing was tested on classified tiled LAS using geometrically reliable first-return points without overlap. ANPS was tested using Delaunay Triangulation that produced average point spacing between all nearest neighbors. 2023 Maximum Surface Height Rasters were produced as ancillary data from the classified lidar point cloud in order to evaluate the withheld bit flag proof of performance for points that cannot be reasonably interpreted as valid surface returns. These were produced using all returns, withheld flagged points excluded, and using the highest elevation point value from each pixel. These rasters are 32-bit, floating point format and delivered as GeoTIFF files per tile. Cell size of the MSHR is 1 m MSHR are generated from the point cloud data and will not be altered after creation nor will there be further maintenance on this product. 2023 Swath Separation Imagery was produced for the entire project area. Swath separation images use color-coding to illustrate differences in elevation (z-) values where swaths overlap. The color-coded images are semi-transparent and overlay the lidar intensity image. They are ancillary data used as visual aids to more easily identify regions within point cloud datasets that may have suspect interswath alignment or other geometric issues. Imagery was created using last returns with all classification and bit flags, except for noise and withheld bit flag are included. Images are derived from a TIN and have a 50% transparent RGB layer over lidar intensity. Color intervals are as follows for QL2 data: 0-8cm, green; 8-16cm, yellow; >16cm, red. These files were produced as GeoTIFF tiles using a cell size of 2 m. SSI are generated from the point cloud data and will not be altered after creation nor will there be further maintenance on this product. 2023 Supplemental Project Information lidar_gnd_ctrl 2023 Point Point 47,789,796,401 NAD 1983 2011 UTM Zone 18N 0.9996 -75.0 0.0 500000.0 0.0 coordinate pair 0.001 0.001 meter NAD 1983 2011 GRS 1980 6378137.0 298.257222101 North American Vertical Datum of 1988, Geoid 18 0.001 meter Explicit elevation coordinate included with horizontal coordinates 20240109 20240109 Sanborn Map Company, Inc. mailing and physical

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Colorado Springs CO 80920 USA (866)726-2676 FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 None. None. None. Unclassified. None. None. None.