2018 - 2019 State of Maine Lidar DEM: Crown of Maine

Original Dataset Product: These are Digital Elevation Model (DEM) data for Northern Maine as part of the required deliverables for the Crown of Maine 2018 QL2 LiDAR project. Class 2 (ground) lidar points in conjunction with the hydro breaklines were used to create a 1-meter hydro-flattened raster DEM. This lidar data set includes unclassified swath LAS 1.4 files, classified LAS 1.4 files, hydro and bridge breaklines, hydro-flattened digital elevation models (DEMs), and intensity imagery.

Original Dataset Geographic Extent: 4 partial counties in Northern Maine, covering approximately 6,732 total square miles. The counties are: Aroostook, Penobscot, Piscataquis, Somerset.

Original Dataset Description: The Crown of Maine 2018 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 19, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 8,056 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format.

Original Dataset Ground Conditions: LiDAR was collected in spring of 2018 and 2019, 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, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 256 independent accuracy checkpoints, 149 in Bare Earth and Urban landcovers (149 NVA points), 107 in Tall Weeds categories (107 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.

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 DEMs. The purpose of these LiDAR data was to produce high accuracy 3D hydro-flattened digital elevation models (DEMs) with a 1-meter cell size. These raw LiDAR point cloud data were used to create classified LiDAR LAS files, intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.

Raster File Type = IMG Bit Depth/Pixel Type = 32-bit float Raster Cell Size = 1.0 Meter Interpolation or Resampling Technique = Triangulated Irregular Network (TIN), Linear Interpolation, Proprietary

In no event shall the creators, custodians, or distributors of these data be liable for any damages arising out of its use, or from the inability of the customer to use these data for their intended application. All deliverable data and documentation shall be free from restrictions regarding use and distribution. Data and documentation shall be freely distributable by government agencies.

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.

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.

Quantum Spatial Vertical Accuracy DEM Determination

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 149 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 107 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. 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 NVA = 8.7 cm at 95% Confidence Level (4.4 cm RMSE)

Tested VVA = 16.2 cm at the 95th Percentile

USGS Vertical Accuracy DEM Determination

Tested NVA = 8.72 cm at 95% Confidence Level (4.4 cm RMSE)

Tested VVA = 18.05 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 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.