2017 SWFWMD Lidar DEM: Hillsborough County, FL

Dewberry collected 1200 square miles of lidar data in Hillsborough County, Florida. The nominal pulse spacing for this project was 1 point every 0.25 meters or a nominal pulse density of 16 points per square meter. Dewberrry used proprietary procedures to classify the LAS according to project specifications: 1-Unclassified, 2-Ground, 6-Building Rooftops, 7-Low Noise, 9-Water, 17- Bridge Decks, 18-High Noise. Geometrically unreliable points, ground points within 2 feet of breaklines, and ground points within 3 feet of buiding rooftops have been identified with the Withheld Flag. Overage points have been identified with the Overlap Flag. The lidar data were combined with 3D breaklines compiled by Dewberry to create hydro-enforced bare-earth DEMs. The data were tiled according to the Florida Statewide Lidar Index tiling scheme with each tile covering an area of 5,000 feet by 5,000 ft.

The DEMs model the bare-earth surface and are enforced with the 3D breaklines created for this project.

Translation of files to formats other than those described here is the sole responsibility of individuals downloading these data.

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

Data is available online for bulk and custom downloads.

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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be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions.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.

Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.3.

The DEMs are derived from the source lidar and 3D breaklines created from the lidar. Horizontal accuracy is not performed on the DEMs or breaklines.

Only checkpoints photo-identifiable in the intensity imagery can be used to test the horizontal accuracy of the lidar. Photo-identifiable checkpoints in intensity imagery typically include checkpoints located at the ends of paint stripes on concrete or asphalt surfaces or checkpoints located at 90 degree corners of different reflectivity, e.g. a sidewalk corner adjoining a grass surface. The xy coordinates of checkpoints, as defined in the intensity imagery, are compared to surveyed xy coordinates for each photo-identifiable checkpoint. These differences are used to compute the tested horizontal accuracy of the lidar. As not all projects contain photo-identifiable checkpoints, the horizontal accuracy of the lidar cannot always be tested.

Lidar systems are calibrated during installation of the system and then again for every project acquired. Typical calibrations include cross flights that capture features from multiple directions that allow adjustments to be performed so that the captured features are consistent between all swaths and cross flights from all directions.

This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 1.35 ft (41 cm) RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 3.28 ft (100 cm) at a 95% confidence level. Eleven (11) 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 = 1.09 ft (33.2 cm) and RMSEy = 0.70 ft (21.3 cm) which equates to +/- 2.23 ft (68 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 DEMs are derived from the source lidar and 3D breaklines created from the lidar. The DEMs are created using controlled and tested methods to limit the amount of error introduced during DEM production so that any differences identified between the source lidar and final DEMs can be attributed to interpolation differences. DEMs are created by averaging several lidar points within each pixel which may result in slightly different elevation values at a given location when compared to the source LAS, which is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the lidar ground points. TINs do not average several lidar points together but interpolate (linearly) between two or three points to derive an elevation value.

The vertical accuracy of the final bare earth DEMs was tested by Dewberry with 178 independent checkpoints. The same checkpoints that were used to test the source lidar data were used to validate the vertical accuracy of the final DEM products. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain (147 checkpoints), including bare earth, open terrain, and urban terrain, and vegetated terrain (31 checkpoints), including forest, brush, tall weeds, crops, and high grass. The vertical accuracy 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.

All checkpoints located in non-vegetated terrain were used to compute the Non-vegetated Vertical Accuracy (NVA). Project specifications required a NVA of 0.64 ft (19.6 cm) at the 95% confidence level based on RMSEz (0.33 ft/10 cm) x 1.9600. All checkpoints located in vegetated terrain were used to compute the Vegetated Vertical Accuracy (VVA). Project specifications required a VVA of 0.96 ft (29.4 cm) based on the 95th percentile.

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 =0.12 ft (3.6 cm), equating to +/- 0.23 ft (7.0 cm) at 95% confidence level. 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 VVA accuracy was found to be +/- 0.50 ft (15.2 cm) at the 95th percentile.

A visual qualitative assessment was performed to ensure data completeness and bare earth data refinement. No void or missing data.

Data covers the project tiling scheme.

The NOAA Office for Coastal Management (OCM) downloaded the DEM .img file from the Southwest Florida Water Management District (SWFWMD).