2018 USGS Lidar DEM: Southern California Wildfires

Product: 1-meter bare-earth raster digital elevation model (DEM) data tiles in GeoTIFF format.

Geographic Extent:

QL2 Area - Approximately 8,146 square miles in portions of Los Angeles, Orange, Riverside, San Bernardino, Kern, San Luis Obispo, Santa Barbara, Ventura Counties

QL1 Area - Approximately 1,343 square miles in portion of Santa Barbara County.

Dataset Description:

QL2 Area: The CA SoCal Wildfires 2018 D18 lidar project called for the planning, acquisition, processing, and production of derivative products of QL2 lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications were based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.3. The data was developed based on a horizontal datum/projection of NAD83 (2011) Albers Equal Area, meters, and a vertical datum of NAVD88 (GEOID12B) meters. DEM data was delivered as processed GeoTIFF files formatted to 24,518 individual 1,000-meter x 1,000-meter tiles.

QL1 Area: The CA SoCal Wildfires 2018 D18 lidar project called for the planning, acquisition, processing, and production of derivative products of QL1 lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications were based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.3. The data was developed based on a horizontal datum/projection of NAD83 (2011) Albers Equal Area, meters, and a vertical datum of NAVD88 (GEOID12B) meters. DEM data was delivered as processed GeoTIFF files formatted to 3,479 individual 1,000-meter x 1,000-meter tiles.

Ground Conditions:

QL2 Area: Lidar was collected from May 27, 2018 through October 12, 2018 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, Woolpert established 275 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. An additional 351 independent accuracy checkpoints (205 NVA points and 146 VVA points), were collected and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.

QL1 Area: Lidar was collected from June 13, 2018 through August 6, 2018 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, Woolpert established 275 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. An additional 351 independent accuracy checkpoints (205 NVA points and 146 VVA points), were collected and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.

Hydro breaklines are also available. These data are available for download at the link provided in the URL section of this metadata record. Please note that these products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA or OCM.

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.

Lidar data are used in predicting wildfire risk, and in post-wildfire hazards analyses. For example, lidar data provide 3D information about forest canopy and vegetation structure that is used to map wildfire fuel, a key risk factor for fire occurrence and intensity. Lidar maps the local topographic conditions (elevation, slope, and aspect), which are critical components to understanding and predicting fire behavior. After wildfires occur, lidar data are used to develop predictive models of flood and mudflow hazards that can result from steep terrain that has been stripped of vegetation. Conducting these analyses and understanding the vulnerability of California communities, farms, and infrastructure to future wildfires relies on the availability of high resolution, accurate lidar data. Wildfire applications for high resolution elevation data include: assessment of wildfire hazards, estimates of wildfire fuel loads, flood and mudflow hazard models, development of plans and site engineering documents to support reconstruction activities, 3D data to support ecological assessments and other long-term science requirements.

USGS Contract No. G16PC00022. Contractor: Woolpert. Raster File Type = TIFF Bit Depth/Pixel Type = 32-bit float Raster Cell Size = 1 Meter Interpolation or Re-sampling 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 Woolpert, USGS, 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.

Microsoft Windows 10 Version 1607 (Build 14393.2189); ArcMap 10.3; ArcCatalog 10.3; TerraScan ver. 17; TerraModeler ver. 17; Geocue 2017.2.20.0.

This project required Non-Vegetated Accuracy (NVA) and Vegetated Vertical Accuracy (VVA) testing of the digital elevation model (DEM) dataset. The calculated NVA value was required to meet 19.6 cm at a 95% confidence level using an RMSEz target value of 10 cm x 1.9600. VVA was required to meet 0.30 cm at the 95th percentile error. Testing was assessed and reported using guidelines developed by the National Digital Elevation Program (NDEP) and the American Society for Photogrammetry and Remote Sensing (ASPRS). Testing was performed using the bare earth DEM created as part of this task order. For each checkpoint, an elevation value was derived from the DEM at the point’s x,y location. This value was compared to the checkpoint’s surveyed elevation value. The NVA was to be calculated with a minimum of 190 independent checkpoints falling on bare earth and urban (non-vegetated) classes. VVA had a minimum of checkpoints requirement of 135 points falling in brush/tall grass/weeds (vegetated) land cover classes. These points were not used in the calibration or post processing of the lidar point cloud data and distributed throughout the project area. Checkpoints were surveyed using GPS techniques. See the survey report for acquisition methodologies.

The DEM NVA measured 0.112 meters using an RMSEz of 0.057 meters x 1.9600 using 205 checkpoints. The VVA tested 0.211 meters at the 95th percentile using 146 checkpoints.

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 DEM is of good quality and data passes Non-Vegetated and Vegetated Vertical Accuracy specifications.

Data covers 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.