2018 USGS Lidar DEM: Upper St. Johns, FL

Original Product: These are Digital Elevation Model (DEM) data for Upper St. Johns LiDAR as part of the required deliverables for the 2018 Upper St. Johns LiDAR project. Class 2 (ground) lidar points in conjunction with the hydro breaklines were used to create a 2.5 feet hydro-flattened Raster DEM.

Original Geographic Extent: Upper St. Johns LiDAR, covering approximately 687 square miles.

Original Dataset Description: Upper St. Johns 2018 LiDAR project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.25 meter. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011), State Plane Florida East, U.S. survey feet and vertical datum of NAVD88 (GEOID12B), U.S. survey feet. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 973 individual 5000 ft x 5000 ft tiles, as tiled Intensity Imagery, and as tiled bare earth DEMs; all tiled to the same 5000 ft x 5000 ft schema.

Original Dataset Ground Conditions: Lidar was collected in early 2018, while 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, Dewberry established a total of 30 ground control points that were used to calibrate the lidar to known ground locations established throughout the Upper St. Johns LiDAR project area. An additional 90 independent accuracy checkpoints, 50 in Bare Earth and Urban landcovers (50 NVA points), 40 in Tall Grass and Brushland/Low Trees categories (40 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.

This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the GeoTIFF files hosted by USGS on Amazon Web Services.

The purpose of this Lidar project was 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 2.5 feet cell size. These lidar point cloud data were used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary. All products follow and comply with USGS Lidar Base Specification, Techniques and Methods 11-B4, Version 1.3.

Raster File Type = IMG Bit Depth/Pixel Type = 32-bit float Raster Cell Size = 2.5 Feet Interpolation or Resampling Technique = Triangulated Irregular Network Required Vertical Accuracy = 19.6 cm NVA

Any conclusions drawn from the analysis of this information are not the responsibility of Dewberry, USGS, NOAA, the Office for Coastal Management or its partners.

Data is available online for bulk and custom downloads.

None

Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations.

Horizontal accuracy testing requires well-defined checkpoints that can be identified in the dataset. Elevation datasets, including lidar datasets, do not always contain well-defined checkpoints suitable for horizontal accuracy assessment. However, the ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) recommends at least half of the NVA vertical check points should be located at the ends of paint stripes or other point features visible on the lidar intensity image, allowing them to double as horizontal check points.

Nineteen checkpoints were determined to be photo-identifiable in the intensity imagery and were used to test the horizontal accuracy of the lidar dataset. As only nineteen (19) checkpoints were photo-identifiable, the results are not statistically significant enough to report as a final tested value, but the results of the testing are provided. Using NSSDA methodology (endorsed by the ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014)), horizontal accuracy at the 95% confidence level (called ACCURACYr) is computed by the formula RMSEr * 1.7308 or RMSExy * 2.448. No horizontal accuracy requirements or thresholds were provided for this project. However, lidar datasets are generally calibrated by methods designed to ensure a horizontal accuracy of 1 meter or less at the 95% confidence level.

This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 1.34 ft (41 cm) RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 3.28 ft (1 meter) at a 95% confidence level. Nineteen (19) checkpoints were photo-identifiable but do not produce a statistically significant tested horizontal accuracy value. Using this small sample set of photo-identifiable checkpoints, positional accuracy of this dataset was found to be RMSEx = 0.35 ft (11 cm) and RMSEy = 0.40 ft (12 cm) which equates to +/- 0.92 ft (28 cm) at 95% confidence level. While not statistically significant, the results of the small sample set of checkpoints are within the produced to meet horizontal accuracy.

The same 90 checkpoints that were used to test the vertical accuracy of the lidar were used to validate the vertical accuracy of the final DEM products as well. Accuracy results may vary between the source lidar and final DEM deliverable. DEMs are created by averaging several lidar points within each pixel which may result in slightly different elevation values at each survey checkpoint when compared to the source LAS, which does not average several lidar points together but may interpolate (linearly) between two or three points to derive an elevation value. The vertical accuracy of the DEM is tested by extracting the elevation of the pixel that contains the x/y coordinates of the checkpoint and comparing these DEM elevations to the surveyed elevations. Dewberry typically uses LP360 software to test the swath lidar vertical accuracy, Terrascan software to test the classified lidar vertical accuracy, and Esri ArcMap to test the DEM vertical accuracy so that three different software programs are used to validate the vertical accuracy for each project.

This DEM dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 0.33 ft (10 cm) RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz =0.27 ft (8.2 cm), equating to +/ 0.52 ft (15.8 cm) at 95% confidence level. Actual VVA accuracy was found to be +/ 0.54 ft (16.5) cm at the 95th percentile.

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.

Data covers the entire area specified for this project.

Data is backed up to tape and to cloud storage.

The NOAA Office for Coastal Management (OCM) ingested references to the USGS GeoTIFF files that are hosted on Amazon Web Services (AWS), into the Digital Coast Data Access Viewer (DAV). The DAV accesses the raster data as it resides on AWS.