2019 - 2020 USGS Lidar DEM: Columbia Valley, WA

Original Product: These are Digital Elevation Model (DEM) data for Washington as part of the required deliverables for the Washington Columbia Valley 2018 D19 Lidar project. Class 2 (ground) LiDAR points in conjunction with the hydro breaklines were used to create a 0.5 meter hydro-flattened Raster DEM.

Original Geographic Extent:

WA_ColumbiaValley 1 (Work Unit 183633): 6 counties covering approximately 1880 total square miles. The counties are: Ferry, Grant, Lincoln, Okanogan, Spokane, Stevens

WA_ColumbiaValley 2 (Work Unit 198145): 5 counties covering approximately 1950 total square miles. The counties are: Adams, Grant, Lincoln, Spokane, Whitman

WA_ColumbiaValley 3 (Work Unit 207582): 8 counties covering approximately 1896 total square miles. The counties are: Adams, Benton, Columbia, Franklin, Grant, Walla Walla, Whitman, Yakima

WA_ColumbiaValley 4 (Work Unit 210002): 7 counties covering approximately 1769 total square miles. The counties are: Benton, Franklin, Klickitat, Morrow, Umatilla, Walla Walla, Yakima

Original Dataset Description: The Washington Columbia Valley 2018 D19 Lidar project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 2011 UTM Zone 11N, Meter and vertical datum of NAVD88 Geoid 12b, Meter. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to individual 750 m x 750 m tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 750 m x 750 m schema. Continuous breaklines were produced in Esri file geodatabase format.

Ground Conditions: LiDAR was collected in fall and winter 2019 and winter 2020, while no snow was on the ground and rivers were at or below normal levels.

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 0.5 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 = GeoTIFF; Bit Depth/Pixel Type = 32-bit float; Raster Cell Size = 0.5 meter; Interpolation or Resampling Technique = Triangulated Irregular Network (TIN), Linear Interpolation, Proprietary; Required Vertical Accuracy = 0.196

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

WA_ColumbiaValley_3 (Work Unit 207582): 8 counties covering approximately 1896 total square miles. The counties are: Adams, Benton, Columbia, Franklin, Grant, Walla Walla, Whitman, Yakima

WA_ColumbiaValley 1 (Work Unit 183633): 6 counties covering approximately 1880 total square miles. The counties are: Ferry, Grant, Lincoln, Okanogan, Spokane, Stevens

WA_ColumbiaValley 2 (Work Unit 198145): 5 counties covering approximately 1950 total square miles. The counties are: Adams, Grant, Lincoln, Spokane, Whitman

WA_ColumbiaValley 4 (Work Unit 210002): 7 counties covering approximately 1769 total square miles. The counties are: Benton, Franklin, Klickitat, Morrow, Umatilla, Walla Walla, Yakima

To the extent possible under law, the U.S. Government has waived all copyright and related or neighboring rights to this dataset.

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.

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. 2. Vegetated Vertical Accuracy (VVA): VVA shall be reported for "tall weeds" 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. 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.

USGS Determined DEM Vertical Accuracy

Tested NVA RMSEz = 2.6 cm

Tested 95th percentile value for VVA is : 26.95 cm

For more information see the USGS project report and the lidar reports. The links to these reports are provided in the URL section of this metadata record.

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 pass Non-Vegetated Vertical Accuracy specifications.

Data cover the entire area specified for this project.

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.