2019 - 2021 USGS Lidar DEM: Alameda County, CA

Original Product: Hydro-flattened Digital Elevation Model (DEM) data covering the QL1 and QL0 portions of the Alameda County Lidar 2021 project area.

Original Geographic Extent:

CA_AlamedaCo_1 (Work Unit 221238): This is the 2021 QL1 collection area and it covers approximately 376 square miles in Alameda County, CA.

CA_AlamedaCo_2 (Work Unit 225021): This is the 2019 QL1 collection upgraded to 3DEP specifications area and it covers approximately 216 square miles in Alameda County, CA

CA_AlamedaCo_3 (Work Unit 225024): This is the 2021 QL0 collection area and it covers approximately 186 square miles in Alameda County, CA

Original Dataset Description: This dataset is the combination of three lidar collections over Alameda County, CA. These are: 1) a 2019 QL1 collection upgraded to 3DEP specifications; 2) a 2021 QL1 collection; and 3) a 2021 QL0 collection.

The Alameda County Lidar 2019 Upgrade Lidar project called for the reprocessing of lidar data collected in a 2019 acquisition to meet current 3DEP specifications outlined in the U.S. Geological Survey National Geospatial Program Lidar Base Specification 2020, Revision A document. The QL1 and QL0 Alameda County Lidar 2021 Lidar projects called for the planning, acquisition, and processing of lidar data collected to Quality Level 1 (QL1) and Quality Level 0 (QL0) standards, also based on the U.S. Geological Survey National Geospatial Program Lidar Base Specification 2020, Revision A. Lidar data was delivered as calibrated and classified LAS 1.4 files. Class 2 (ground) lidar points in conjunction with the hydro breaklines were used to create 1.0 foot hydro-flattened raster DEMs delineated in 3000ft x 3000ft tiles tiles.

Ground Condition: Ground condition was free of snow and acquisition occurred free of smoke, fog and cloud cover.

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 purpose of the lidar data was to produce a high accuracy 3D dataset that meets all necessary standards laid out by the 3D Elevation Program and the Alameda County Lidar 2021 contract.

Raster File Type = TIFF Bit Depth/Pixel Type = 32-bit float Raster Cell Size = 1.0 foot Interpolation or Resampling Technique = Triangulated Irregular Network Required Vertical Accuracy = 9.8 cm NVA

Users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. This product is for informational purposes and may not have been prepared for or be suitable for legal, engineering, surveying, or site specific purposes. Users of this information should review or consult the primary data and information sources to ascertain the usability of the information.

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

QL0 Area - CA_AlamedaCo_3

QL1 2021 Area - CA_AlamedaCo_1

2019 QL1 Upgraded Collection Area - CA_AlamedaCo_2

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.

Applanix PosPac MMS, RiProcess, RiWorld, Microstation CONNECT, TerraScan Version 21, TerraModeler Version 21, ESRI ArcGIS 10.7, LAS Product Creator (NV5 Proprietary), LAS Projector (NV5 Proprietary), LAS Monkey (NV5 Proprietary), Windows 10 Operating System

Lidar horizontal accuracy is a function of Global Navigation Satellite System (GNSS) derived positional error, flying altitude, and INS derived attitude error. The obtained RMSEr value is multiplied by a conversion factor of 1.7308 to yield the horizontal component of the National Standards for Spatial Data Accuracy (NSSDA) reporting standard where a theoretical point will fall within the obtained radius 95 percent of the time.

All QL0 areas surveyed at a flying altitude of 1,100 meters, with an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.019 meters, were produced to meet 0.40 ft (0.12 m) horizontal accuracy at the 95% confidence level.

All QL1 areas surveyed at a flying altitude of 2,196 meters, with an IMU error of 0.002 decimal degrees, and a GNSS positional error of 0.019 meters, were produced to meet 0.79 ft (0.24 m) horizontal accuracy at the 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. The specifications require that classified Non-vegetated Vertical Accuracy (NVA) be computed from the derived DEMs. The NVA was tested with 66 independent check points located in open terrain and distributed throughout the project as feasible. These check points were not used in the calibration or post processing of the lidar point cloud data. Specifications for this project require that the NVA be 0.196 meters or better AccuracyZ at 95% confidence level. Vegetated Vertical Accuracy (VVA) is also to be computed from the derived DEMS. The VVA was tested with 48 check points in Tall Grass, Forest, and Shrub land cover types. These check points were also withheld from the calibration and post processing of the lidar point cloud data and distributed throughout the project area as feasible. Specifications for this project require that the VVA be 0.300 meters or better AccuracyZ at the 95th percentile.

USGS Determined DEM Vertical Accuracy

Non-Vegetated Vertical Accuracy (NVA) = 2.1 cm RMSE

Vegetated Vertical Accuracy (VVA) = 9.57 cm at the 95th Percentile

Refer to the USGS project report in the URL section of this metadata record.

A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications.

DEM files were tested by NV5 Geospatial for vertical accuracy. All data is seamless from one tile to the next, no gaps or no data areas.

Data is backed up 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.