2023 - 2024 USGS Lidar DEM: North Central Idaho & Northeast Oregon

Original Product: These are Digital Elevation Model (DEM) data for the required deliverables for the ID NCentral D22 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: A total of 46,763 tiles were produced for the project encompassing an area of approximately 17,297 sq. miles in north central Idaho and northeast Oregon.

ID_NCentral_1: covering approximately 2326 square miles in Idaho

ID_NCentral_2: covering approximately 2080 square miles in Idaho

ID_NCentral_3: covering approximately 3807 square miles in Idaho

ID_NCentral_4: covering approximately 2080 square miles in Idaho and Wallowa counties in Idaho and in Oregon

ID_NCentral_5: covering approximately 2,847 square miles in Idaho County, Idaho

ID_NCentral_6: covering approximately 3892 square miles in Idaho

Original Dataset Description: ID NCentral D22 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 meter. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 2024 rev. A. The data was developed based on a horizontal datum/projection of NAD83 (2011) UTM Zone 11N, Universal Transverse Mercator, meters and vertical datum of NAVD88 (GEOID18), meters. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to individual 1,000 m x 1,000 m tiles and as tiled bare earth DEMs; all tiled to the same 1,000 m x 1,000 m schema.

Ground Conditions: Lidar was collected in 2023 and 2024 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 Breaklines and Raster DEM. The purpose of these lidar data was to produce high accuracy 3D hydro-flattened Digital Elevation Model (DEM) with a 0.5 meter cell size. These raw lidar point cloud data were used to create classified lidar LAS files, 3D breaklines, hydro-flattened DEMs as necessary.

Raster File Type = TIFF

Bit Depth/Pixel Type = 32-bit float

Raster Cell Size = 0.5 Meter

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 NOAA, the Office for Coastal Management or its partners.

ID_NCentral_1: covering approximately 2326 square miles in Idaho

ID_NCentral_2: covering approximately 2080 square miles in Idaho

ID_NCentral_3: covering approximately 3807 square miles in Idaho

ID_NCentral_4: covering approximately 2080 square miles in Idaho and Wallowa counties in Idaho and in Oregon

ID_NCentral_5: covering approximately 2,847 square miles in Idaho County, Idaho

ID_NCentral_6: covering approximately 3892 square miles in Idaho

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.

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 vendors calibrate their lidar systems 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 41 cm RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 1 meter at a 95% confidence level

This data set was produced to meet ASPRS Positional Accuracy Standard for Digital Geospatial Data (2014) for a 10-cm RMSEz Vertical Accuracy Class.

USGS Determined DEM Vertical Accuracy

Tested NVA RMSEz =6.15 cm

Tested 95th percentile value for VVA is : 19.62 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 passes Non-Vegetated Vertical Accuracy specifications.

Data covers 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.