Data from: LiDAR-derived digital elevation model of Whale's Tail Marsh, San Francisco Bay, 2019
Data files
Sep 26, 2023 version files 9.02 MB
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2019_combined_raster_converted_to_m.tif
9.02 MB
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README.md
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Abstract
Data presented are a geospatially-aligned (NAD83) raster image with raster values as bare-earth elevation values (NAVD88) of mudflats, marsh, and levees around Whale's Tail Marsh, South San Francisco Bay (Hayward/Union City). Data presented are a subset of a larger LiDAR survey of the region contracted by the Alameda County Public Works Agency, trimmed to the region of study by Lukas WinklerPrins.
While these data have been tested for accuracy and are properly functioning, Alameda County and the Alameda County Flood Control and Water Conservation District disclaims any responsibility for the accuracy or correctness of the data. In addition, the use and/or reliance of the information by any other party shall be at their own risk.
Data published are a geotiff (i.e. georeferenced raster data) of elevation values (in NAVD88 datum) of Whale’s Tail Marsh in San Francisco Bay, with the surrounding mudflats, levees, ponds, and channels. These data were produced via LiDAR survey collected by the Alameda County Public Works Agency and were compiled and clipped to the region of interest by Lukas WinklerPrins, so as to contribute to a study of marsh-edge morphodynamics at the site. These data were set in context with other LiDAR surveys from 2004 and 2010, in addition to structure-from-motion derived digital surface models over a 2021-2022 study year, and generally used to identify retreat rates and heterogeneity of the marsh-mudflat interface.
Description of the data and file structure
Data presented are in a single .tif file which includes additional metadata for georeferencing. We recommend loading the data into GIS software (e.g. QGIS or ESRI ArcGIS/ArcMAP) where it can be analyzed and manipulated as a raster surface in the correct geographic context. The file has a resolution of approximately 3 US Survey Feet (0.9144 m) to the side of each pixel.
This earth surface is heterogeneous and mostly intertidal. Small perturbations in the surface due to vegetation or channels may be difficult to distinguish from measurement error in some places, and LiDAR returns from wet regions (generally low elevations and in the ponds on the eastern edge of the image) should be interpreted conservatively.
Sharing/Access information
Additional data generated from this LiDAR survey may be available via Alameda County Public Works Agency upon request.
While the data published here have been tested for accuracy and are properly functioning, Alameda County and the Alameda County Flood Control and Water Conservation District disclaims any responsibility for the accuracy or correctness of the data. In addition, the use and/or reliance of the information by any other party shall be at their own risk.
Code/Software
Data were generally manipulated using QGIS 3.24.3 software, with some additional processing in python 3.10 using various common libraries but especially tifffile.
ADF files of the study area were merged into a continuous raster and clipped to the region of interest using QGIS software. Methods for data collection and creation as reported by the contractor are as follows:
1. Flightlines and data were reviewed to ensure complete coverage of the study area and positional accuracy of the laser points.
2. Laser point return coordinates were computed using POSPac MMS 8.3 and RiProcess 1.8.5 software based on independent data from the LiDAR system, IMU, and aircraft.
3. The raw LiDAR file was assembled into flightlines per return with each point having an associated x, y, and z coordinate.
4. Visual inspection of swath to swath laser point consistencies within the study area were used to perform manual refinements of system alignment.
5. Custom algorithms were designed to evaluate points between adjacent flightlines. Automated system alignment was computed based upon randomly selected swath to swath accuracy measurements that consider elevation, slope, and intensities. Specifically, refinement in the combination of system pitch, roll, and yaw offset parameters optimize internal consistency.
6. Noise (e.g., pits and birds) was filtered using post-processing software, based on known elevation ranges and included the removal of any cycle slips.
7. Using TerraScan and Microstation, ground classifications utilized custom settings appropriate to the study area.
8. The corrected and filtered return points were compared to the ground survey points collected to verify the vertical accuracy.
9. TIN processing of the ground point returns was used to create this bare earth DEM.