2016 - 2019 USGS Lidar DEM: Alabama 25 County

This dataset produced high accuracy 3D hydro-flattened Digital Elevation Model (DEM) with a 1 meter X 1 meter cell posting.

USGS NGTOC task order G17PD00243 required Spring 2017 LiDAR surveys to be collected over 18,845 square miles covering part or all of 25 counties in Alabama. These counties are Autauga, Baldwin, Barbour, Bullock, Butler, Chambers, Cherokee, Clarke, Conecuh, Covington, Crenshaw, Elmore, Etowah, Henry, Houston, Lamar, Limestone, Macon, Monroe, Pike, Randolph, Russell, Shelby, Tallapoosa, and Winston. Aerial LiDAR data for this task order was planned, acquired, processed, and produced at an aggregate nominal pulse spacing (ANPS) of 0.7 meters and in compliance with USGS National Geospatial Program LiDAR Base Specification version 1.2.

The data are divided up in 9 blocks. Please see the kmz provided in the URL section of this metadata record for the block footprints.

Block 1 - Lamar, Limestone, Winston Counties

Block 2 - Cherokee, Etowah, Shelby Counties

Block 3 - Chambers, Randolph, Tallapoosa (partial) Counties

Block 4 - Autauga, Barbour (partial), Bullock (partial), Elmore, Macon, Russell Counties

Block 5 - Barbour (partial), Bullock (partial), Henry, Houston Counties

Block 6 - Barbour (partial), Bullock, (partial), Butler (partial), Conecuh (partial), Covington, Crenshaw, Pike Counties

Block 7 - Baldwin (partial), Butler (partial), Clarke, Conecuh (partial), Monroe Counties

Block 8 - Baldwin County (partial)

Block TL - 1 file in Monroe County and 3 files in Elmore County

Isolated gaps in GPS data were identified in several missions covering this project. As both, the IMU data and pulse data, were present across these gaps, using the fixed positions of the GPS on either end, the aircraft velocity across the gaps, and the IMU data, LiDAR calibration staff were able to reach an effective solution to address the GPS voids. Because these gaps were not uniform in size or correction, this extended the iterative LiDAR calibration efforts on this project. Subsequent rigorous data checking confirmed adequate results to meet the required accuracy specs. The USGS QA Team already reviewed affected data (blocks) for this project and found no QA/QC discrepancies to report regarding those gaps.

Geographic Extent: This data set is consisting of lidar point cloud, classified lidar, digital elevation model, and lidar intensity images which all pieces encompasses the 2016 Alabama 25 County lidar (Pilot) area of interest (AOI), approximately 18,845 square miles or 48,408 square kilometers.

Data set Description: This data set consists of lidar point cloud LAS swath files and tiled LAS files. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Each file represents a separate swath of lidar.

Ground Conditions: water at normal levels; no unusual inundation; no snow; leaf off

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 primary purpose of the lidar survey was to establish measurements of the bare earth surface, as well as top surface feature data for providing geometric inputs for modeling, other numerical modeling and economic related assessments.

All lidar data was acquired, calibrated, and used in the creation of lidar derived products by Atlantic.

Lidar tiles and associated derived products for USGS

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

Overall data set, including all 9 blocks.

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.

CloudPro 1.2.0 Build 85620; GeoCue Version 2014.1.21.2; Windows 7 Operating System

\\lidarsrv\GC_Warehouse_5\80658\30\*.las

184 GB

Horizontal accuracy values were provided by Atlantic for the following blocks:

Block 1:

As described in Section 7.5 of the ASPRS Positional Accuracy Standards for Digital Geospatial Data the horizontal errors in lidar data are largely a function of GNSS positional error, INS angular error, and flying altitude. Therefore, lidar data collected with GNSS error of 8cm and the IMU error of 0.00427 degrees at an altitude of 2,000m; the expected radial horizontal positional error will be RMSEr = 29.0cm.

Block 2:

As described in Section 7.5 of the ASPRS Positional Accuracy Standards for Digital Geospatial Data the horizontal errors in collected with GNSS error of 8cm and the IMU error of 0.00427 degrees at an altitude of 2,000m; the expected radial horizontal positional error will be RMSEr = 29.0cm.

Block 4:

As described in Section 7.5 of the ASPRS Positional Accuracy Standards for Digital Geospatial Data the horizontal errors in lidar data are largely a function of GNSS positional error, INS angular error, and flying altitude. Therefore, lidar data collected with GNSS error of 8cm and the IMU error of 0.00427 degrees at an altitude of 2162m; the expected radial horizontal positional error will be RMSEr = 31.0cm.

Block 5:

As described in Section 7.5 of the ASPRS Positional Accuracy Standards for Digital Geospatial Data the horizontal errors in lidar data are largely a function of GNSS positional error, INS angular error, and flying altitude. Therefore, lidar data collected with GNSS error of 8cm and the IMU error of 0.00427 degrees at an altitude of 2162m; the expected radial horizontal positional error will be RMSEr = 31.0cm.

A total of 761 ground survey points were collected in support of this project, including 136 LiDAR Control Points (LCP), 340 Non-vegetated Vertical Accuracy (NVA) and 285 Vegetated Vertical Accuracy (VVA).

Point cloud data accuracy was tested against a Triangulated Irregular Network (TIN) constructed from LiDAR points in clear and open areas. A clear and open area can be characterized with respect to topographic and ground cover variation such that a minimum of five (5) times the Nominal Pulse Spacing (NPS) exists with less than 1/3 of the RMSEZ deviation from a low-slope plane. Slopes that exceed ten (10) percent were avoided.

The NVA value is a requirement that must be met, regardless of any allowed “busts” in the VVA(s) for individual land cover types within the project. Checkpoints for each assessment (NVA and VVA) are required to be well-distributed throughout the land cover type, for the entire project area.

Each land cover type representing ten (10) percent or more of the total project area were tested and reported with a VVA. In land cover categories other than dense urban areas, the tested points did not have obstructions forty-five (45) degrees above the horizon to ensure a satisfactory TIN surface. The VVA value is provided as a target. It is understood that in areas of dense vegetation, swamps, or extremely difficult terrain, this value may be exceeded.

Vertical Accuracy of the point cloud and bare-earth lidar data was assessed and reported in accordance with the ASPRS Positional Accuracy Standards for Digital Geospatial Data;

Required Non Vegetated Vertical Accuracy (NVA) : 0.196m

Required Vegetated Vertical Accuracy (VVA): 0.294 m.

This data set was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10.0 (cm) RMSEz Vertical Accuracy Class. Actual NVA accuracy of the bare-earth was found to be RMSEz = 0.0817 m, equating to +/- 0.1601 m at 95% confidence level.

Actual VVA accuracy was found to be RMSEz = 0.1192 m, equating to +/- 0.2335 m at the 95th percentile.

The raw LAS data files included all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. The raw point cloud is of good quality and data passes Fundamental Vertical Accuracy specifications.Void areas (i.e., areas outside the project boundary but within the tiling scheme) are coded using a unique NODATA value. This value is identified in the appropriate location within the file header.

All lidar data and lidar derived data covers the entire 18,845 square miles area of interest for the pilot area. All lidar point cloud tiles show no edge artifacts or mismatches from tile to tile. Void areas (i.e. areas outside the project boundary but within the tiling scheme) are coded using a unique NODATA value. This value is identified in the appropriate location within the file header. Data cover 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.