2014 USGS QL1 Lidar DEM: San Diego, CA

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Bulk download of data files in GeoTIFF format, CA State Plane Zone 6 NAD83(2011), U.S. feet coordinates and elevations in NAVD88 (Geoid12A) feet.

The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.

Appendices to the dataset report

Summary report from the contractor.

Link to the Quantum Spatial FOCUS report.

This data source was used (along with the airborne GPS/IMU Data) to aid in the georeferencing of the lidar point cloud data.

This data source was used to populate the lidar point cloud data.

Lidar Pre-Processing: Airborne GPS and IMU data were merged to develop a Single Best Estimate (SBET) of the lidar system trajectory for each lift. Lidar ranging data were initially calibrated using previous best parameters for this instrument and aircraft. Relative calibration was evaluated using advanced plane-matching analysis and parameter corrections derived. This was repeated iteratively until residual errors between overlapping swaths, across all project lifts, was reduced to acceptable levels. Data were then block adjusted to match surveyed calibration control. Raw data FVA were checked using independently surveyed checkpoints. Swath overage points were identified and tagged within each swath file. The results of the final calibration, FVA and horizontal accuracy assessments, and the "raw" swaths were forwarded to the client to obtain a Notice To Proceed on classification and derivative product generation.

Lidar Post-Processing: The calibrated and controlled lidar swaths were processed using automatic point classification routines in proprietary software. These routines operate against the entire collection (all swaths, all lifts), eliminating character differences between files. Data were then distributed as virtual tiles to experienced lidar analysts for localized automatic classification, manual editing, and peer-based QC checks. Supervisory QC monitoring of work in progress and completed editing ensured consistency of classification character and adherence to project requirements across the entire project area.

All classification tags are stored in the original swath files.

After completion of classification and final QC approval, the FVA, SVAs, and CVA for the project are calculated. Sample areas for each land cover type present in the project area were extracted and forwarded to the client, along with the results of the accuracy tests. Upon acceptance, the complete classified lidar swath files were delivered to the client.

Classified LAS Processing: The bare earth surface is then manually reviewed to ensure correct classification on the Class 2 (Ground) points. After the bare-earth surface is finalized, it is then used to generate all hydro-breaklines through heads-up digitization.

All ground (ASPRS Class 2) LiDAR data inside of the Lake Pond and Double Line Drain hydro flattening breaklines were then classified to water (ASPRS Class 9) using TerraScan macro functionality. A buffer of 3 feet was also used around each hydro-flattened feature to classify these ground (ASPRS Class 2) points to Ignored ground (ASPRS Class 10). All Lake Pond Island and Double Line Drain Island features were checked to ensure that the ground (ASPRS Class 2) points were reclassified to the correct classification after the automated classification was completed.

All overlap data was processed through automated functionality provided by TerraScan to classify the overlapping flight line data to approved classes by USGS. The overlap data was classified to Class 21 (Overlap Default), Class 22 (Overlap Ground), and Class 25 (Overlap Water). These classes were created through automated processes only and were not verified for classification accuracy. Due to software limitations within TerraScan, these classes were used to trip the withheld bit within various software packages. These processes were reviewed and accepted by USGS through numerous conference calls and pilot study areas.

All data was manually reviewed and any remaining artifacts removed using functionality provided by TerraScan and TerraModeler. Global Mapper us used as a final check of the bare earth dataset. GeoCue was then used to create the deliverable industry-standard LAS files for both the All Point Cloud Data and the Bare Earth. Photo Science proprietary software was used to perform final statistical analysis of the classes in the LAS files, on a per tile level to verify final classification metrics and full LAS header information.

Hydro Flattening Breakline Processing:

Class 2 LiDAR was used to create a bare earth surface model. The surface model was then used to heads-up digitize 2D breaklines of inland streams and rivers with a 100 foot nominal width and Inland Ponds and Lakes of 2 acres or greater surface area.

Elevation values were assigned to all Inland Ponds and Lakes, Inland Pond and Lake Islands, Inland Stream and River Islands, using TerraModeler functionality.

Elevation values were assigned to all Inland streams and rivers using Photo Science proprietary software.

All ground (ASPRS Class 2) LiDAR data inside of the collected inland breaklines were then classified to water (ASPRS Class 9) using TerraScan macro functionality. A buffer of 3 feet was also used around each hydro-flattened feature. These points were moved from ground (ASPRS Class 2) to Ignored Ground (ASPRS Class 10).

The breakline files were then translated to ESRI File-Geodatabase format using ESRI conversion tools.

Hydro Flattened Raster DEM Process: Class 2 LiDAR in conjunction with the hydro breaklines were used to create a 2.5 foot Raster DEM. Using automated scripting routines within ArcMap, an ERDAS Imagine IMG file was created for each tile. Each surface is reviewed using Global Mapper to check for any surface anomalies or incorrect elevations found within the surface. Class 2 LiDAR in conjunction with the hydro breaklines were used to create a 2.5 foot hydro-flattened Raster DEM. Using automated scripting routines within ArcMap, an ERDAS Imagine IMG file was created for each tile. Each surface is reviewed using Global Mapper to check for any surface anomalies or incorrect elevations found within the surface.

The NOAA Office for Coastal Management (OCM) created references to the USGS GeoTIFF files that were ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the raster data as it resides on Amazon Web Services (AWS).

These are the GeoTIFF files that are being accessed:

https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/OPR/Projects/San_Diego_CA_2014_LiDAR/CA_SanDiegoQL1_2014/TIFF/