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Ayres Associates
(608) 443-1200
5201 E Terrace Drive, Suite 200
Madison
Wisconsin
53718
U.S.A.
20200619
ArcGIS Metadata
1.0
2020 LiDAR DEM
2020-06-19
Ayres Associates
raster digital data
The Grant County lidar project area covers approximately 1250 square miles which includes a 100 meter buffer around the county boundary. The lidar data was acquired at a nominal point spacing (NPS) of 0.7 meters and a aggregate nominal point density (ANPD) of 2.0. Project specifications are based on Grant County requirements and on the U.S. Geological Survey National Geospatial Program LiDAR Base Specification, Version 2.1. The data was developed based on a horizontal projection/datum of NAD83(2011) / WISCRS Grant (ftUS) (EPSG Code: 7607), and vertical datum of NAVD88 - Geoid12B (Feet). LiDAR data was acquired using two Riegl VQ 1560 sensors with serial numbers SN754 and SN1264 from April 19, 2020 to April 30, 2020 in 5 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.
This data, along with its derivatives, is the result of a countywide elevation mapping with cooperative partnerships from Grant County, Wisconsin DOA, and the USGS 3DEP program. This data was produced from lidar data collected in April 2020, which was processed and delivered in 2021.
Wisconsin
Grant County
Grant County
Model
Raster
DEM
Remote Sensing
Elevation
Lidar
Model
Raster
DEM
Remote Sensing
Elevation
Lidar
Wisconsin
Grant County
Grant County
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be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions.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.
No restrictions apply to these data.
true
-91.168849
-90.408537
43.214261
42.497460
ground conditions
2020-04-19
2020-04-30
Raster File Type = TIFF Bit Depth/Pixel Type = 32-bit float Raster Cell Size = 2 foot Interpolation or Resampling Technique = Triangulated Irregular Network Required Vertical Accuracy = 19.6 cm NVA
Esri ArcGIS 13.5.5.57366
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Last metadata review date: 2020-06-19
None.
None.
Data covers the entire area specified for this project.
Datasets contain complete coverage of tiles. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. There are no void areas or missing data. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications.
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 70 checkpoints located in bare earth and urban (non-vegetated) areas. 2. Vegetated Vertical Accuracy (VVA): VVA shall be reported for "brushlands/low trees" and "tall weeds/crops" 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 55 checkpoints located in tall weeds/crops and brushlands/low trees (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.
Tested 0.052 meters NVA at a 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA). The NVA of the DEM was calculated using 70 independent checkpoints located in the Bare Earth and Urban land cover categories.
0.052
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 70 checkpoints located in bare earth and urban (non-vegetated) areas. 2. Vegetated Vertical Accuracy (VVA): VVA shall be reported for "brushlands/low trees" and "tall weeds/crops" 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 55 checkpoints located in tall weeds/crops and brushlands/low trees (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.
Tested 0.136 meters VVA was calculated using 55 checkpoints located in the Brushlands and Low Trees and Tall Weeds and Crops land cover categories at the 95th percentile, derived according to ASPRS Guidelines, Vertical Accuracy Reporting for Lidar Data. Tested against the DEM.
0.136
LiDAR processing utilizes several software packages, including GeoCue and the TerraSolid suite of processing components. The GeoCue software is a database management system for housing the LiDAR dataset (usually multiple gigabytes in size). GeoCue incorporates a thorough checklist of processing steps and quality assurance/quality control (QA/QC) procedures that assist in the LiDAR workflow. The TerraSolid software suite is used to automate the initial classification of the LiDAR point cloud based on a set of predetermined parameters. Lidar technicians refer to ground cover research (natural and cultural features) within the project area and determine algorithms most suitable for the initial automated LiDAR classification. (Some algorithms/filters recognize the ground in forests well, while others have greater capability in urban areas). During this process each point is given an initial classification (e.g., as ground, vegetation, or noise) based on the point's coordinates and the relation to its neighbors. Classifications to be assigned include all those outlined by ASPRS standards. The initial classifications produce a coarse and inexact dataset, but offer an adequate starting point for the subsequent manual classification procedure. During this step, "overlap" points are automatically classified (those originating from neighboring flightlines) using information gathered from the ABGPS and IMU data. Any duplicate points existing from adjacent flightlines are removed during this process. Hydrographic breaklines are collected using LiDARgrammetry to ensure hydroflattened water surfaces. This process involves manipulating the LiDAR data's intensity information to create a metrically sound stereo environment. From this generated "imagery", breaklines are photogrammetrically compiled. Breakline polygons are created to represent open water bodies. The LiDAR points that fall within these areas are classified as "water." All hydrographic breaklines include a 3.125 foot buffer, with the Class 2 (bare earth) points being re-classified as Class 20 (ignored ground). TerraSolid is further used for the subsequent manual classification of the LiDAR points allowing technicians to view the point cloud in a number of ways to ensure accuracy and consistency of points and uniformity of point coverage. The TIN was processed to create a GRID or digital elevation model (DEM) with 2 foot pixels.
2020-06-19
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None.
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