A seamless, high-resolution, coastal digital elevation model (DEM) for Southern California

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What does this data set describe?

Title:
A seamless, high-resolution, coastal digital elevation model (DEM) for Southern California
Abstract:
A seamless, three-meter digital elevation model (DEM) was constructed for the entire Southern California coastal zone, extending 473 km from Point Conception to the Mexican border. The goal was to integrate the most recent, high-resolution datasets available (for example, Light Detection and Ranging (Lidar) topography, multibeam and single beam sonar bathymetry, and Interferometric Synthetic Aperture Radar (IfSAR) topography) into a continuous surface from at least the 20-m isobath to the +20-m elevation contour.
Supplemental_Information:
Additional information about the USGS field activities from which some of these data were derived is available online at:
https://cmgds.marine.usgs.gov/fan_info.php?fan=Z206SC https://cmgds.marine.usgs.gov/fan_info.php?fan=Z107SC https://cmgds.marine.usgs.gov/fan_info.php?fan=S808SC https://cmgds.marine.usgs.gov/fan_info.php?fan=SV206CA https://cmgds.marine.usgs.gov/fan_info.php?fan=SV107CA
Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Although this Federal Geographic Data Committee-compliant metadata file is intended to document the data set in nonproprietary form, as well as in ArcInfo format, this metadata file may include some ArcInfo-specific terminology.
  1. How might this data set be cited?
    Barnard, Patrick L., and Hoover, Daniel, 2009, A seamless, high-resolution, coastal digital elevation model (DEM) for Southern California.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -120.511
    East_Bounding_Coordinate: -117.033
    North_Bounding_Coordinate: 34.494
    South_Bounding_Coordinate: 32.518
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 1996
    Ending_Date: 2008
    Currentness_Reference:
    topography at time underlying data set was collected (See Source Information)
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: ARC Ascii Grids (for conversion to raster grids)
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Raster data set. It contains the following raster data types:
      • Dimensions 8160 x 7317 x 1, type Grid Cell
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 11
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.999600
      Longitude_of_Central_Meridian: -117.000000
      Latitude_of_Projection_Origin: 0.000000
      False_Easting: 500000.000000
      False_Northing: 0.000000
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 3.000000
      Ordinates (y-coordinates) are specified to the nearest 3.000000
      Planar coordinates are specified in meters
      The horizontal datum used is North American Datum of 1983.
      The ellipsoid used is Geodetic Reference System 80.
      The semi-major axis of the ellipsoid used is 6378137.000000.
      The flattening of the ellipsoid used is 1/298.257222.
  7. How does the data set describe geographic features?
    Entity_and_Attribute_Overview:
    Raster surface showing elevation/bathymetry data for southern California.
    Entity_and_Attribute_Detail_Citation:
    The entity and attribute information was generated by the individual and/or agency identified as the originator of the data set. Please review the rest of the metadata record for additional details and information.

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Patrick L. Barnard
    • Daniel Hoover
  2. Who also contributed to the data set?
    California State University, Monterey Bay (CSUMB) and Fugro Pelagos, Inc. for California State Waters Mapping Project (CSWMP) from Pat Iampietro; Fugro Pelagos, Inc. (Fugro); Los Angeles County from Drew Decker; National Geophysical Data Center (NGDC); National Oceanic and Atmospheric Administration (NOAA); San Diego Association of Governments (SANDAG)/Fugro; Scripps Institution of Oceanography (Scripps) from Darren Wright; United States Geological Survey (USGS) from Pete Dartnell and from David Finlayson; University of Texas at Austin (UT) from Randy Bucciarielli and from Robert Gutierrez.
  3. To whom should users address questions about the data?
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    Attn: PCMSC Science Data Coordinator
    2885 Mission Street
    Santa Cruz, CA
    USA

    831-427-4747 (voice)
    pcmsc_data@usgs.gov

Why was the data set created?

This dataset was produced to provide critical boundary conditions (bathymetry and topography) for a modeling effort designed to predict the impacts of severe winter storms on the Southern California coast (Barnard and others, 2009). The hazards model, run in real-time or with prescribed scenarios, incorporates atmospheric information (wind and pressure fields) with a suite of state-of-the-art physical process models (tide, surge, and wave) to enable detailed prediction of water levels, run-up, wave heights, and currents. Research-grade predictions of coastal flooding, inundation, erosion, and cliff failure are also included. The DEM was constructed to define with the general shape of nearshore, beach and cliff surfaces as accurately as possible, with less emphasis on fine-scale (meters to tens of meters) variations in elevation and on bathymetry inside harbors. As a result this DEM should not be used for navigation purposes.

How was the data set created?

  1. From what previous works were the data drawn?
    CSUMB (source 1 of 10)
    California State University, Monterey Bay, Unknown, Multibeam bathymetry.

    Online Links:

    Other_Citation_Details: contact Pat Iampietro, <pat_iampietro@csumb.edu>
    Type_of_Source_Media: digital data - raster grids or ascii xyz text files
    Source_Contribution:
    Provided data for coverage areas: nearshore bathymetry, La Jolla Canyon, nearshore Santa Monica Bay, and nearshore in Ventura County.
    Fugro for CSWMP (source 2 of 10)
    Fugro Pelagos, Inc. for California State Waters Mapping Project, Unknown, Multibeam bathymetry.

    Other_Citation_Details: contact Pat Iampietro, <pat_iampietro@csumb.edu>
    Type_of_Source_Media: digital data - raster grids or ascii xyz text files
    Source_Contribution:
    Provided data for coverage areas: offshore Coal Oil and Pt. Conception region, nearshore San Diego County, nearshore Orange County, Los Angeles Harbor, nearshore Santa Monica Bay, west of Pt. Dume, and east of Mugu.
    Fugro (source 3 of 10)
    Fugro Pelagos, Inc., Unknown, Scanning Hydrographic Operational Airborne Lidar Survey (SHOALS).

    Other_Citation_Details: contact Pete Dartnell, <pdartnell@usgs.gov>
    Type_of_Source_Media: digital data - raster grids or ascii xyz text files
    Source_Contribution:
    Provided data for coverage area: Orange County nearshore western half.
    Los Angeles County (source 4 of 10)
    County, Los Angeles, Unknown, Lidar (topo).

    Other_Citation_Details: contact Drew Decker, <ddecker@usgs.gov>
    Type_of_Source_Media: digital data - raster grids or ascii xyz text files
    Source_Contribution: Provided data for coverage area: all Los Angeles County.
    NGDC (source 5 of 10)
    National Geophysical Data Center, Unknown, Regional Digital Elevation Model (DEM).

    Online Links:

    Type_of_Source_Media: digital data - raster grids or ascii xyz text files
    Source_Contribution: Provided data for coverage area: all Southern California.
    NOAA (source 6 of 10)
    National Oceanic and Atmospheric Administration, Unknown, IfSAR, LIDAR (topo), multibeam bathymetry, and tsunami DEM.

    Online Links:

    Type_of_Source_Media: digital data - raster grids or ascii xyz text files
    Source_Contribution:
    Provided data for coverage areas: all land, Mugu to Los Angeles County border, El Segundo nearshore, Los Angeles Harbor, and Santa Barbara Channel
    SANDAG/Fugro (source 7 of 10)
    San Diego Association of Governments, Unknown, Multibeam bathymetry.

    Other_Citation_Details: contact Pete Dartnell, <pdartnell@usgs.gov>
    Type_of_Source_Media: digital data - raster grids or ascii xyz text files
    Source_Contribution:
    Provided data for coverage area: inside 40 m isobath, San Diego County.
    Scripps (source 8 of 10)
    Scripps Institution of Oceanography, Unknown, ATV/PWC and CHARTS Lidar (Topo+Bathy).

    Online Links:

    Other_Citation_Details: contact Darren Wright, Scripps
    Type_of_Source_Media: digital data - raster grids or ascii xyz text files
    Source_Contribution:
    Provided data for coverage areas: Camp Pendleton, Cardiff, Torrey Pines, Imperial Beach, and most of San Diego County
    USGS (source 9 of 10)
    Other_Citation_Details:
    contact Patrick Barnard <pbarnard@usgs.gov>; Pete Dartnell, <pdartnell@usgs.gov>; and David Finlayson, <dfinlayson@usgs.gov>
    Type_of_Source_Media: digital data - raster grids or ascii xyz text files
    Source_Contribution:
    Provided data for coverage areas: East of Gaviota, El Capitan, nearshore Carpinteria, Coal Oil, nearshore Gaviota and Naples, Tijuana Estuary, Los Angeles and San Diego County, Orange County nearshore western half, Ventura nearshore, nearshore east Carpinteria plus offshore bathymetry for Santa Barbara Channel, Ventura region, Mugu region, Rincon region, Carpinteria, and Goleta.
    UT (source 10 of 10)
    University of Texas at Austin, Unknown, Lidar (topo).

    Online Links:

    Other_Citation_Details:
    contact Randy Bucciarielli, <rbucciarelli@ucsd.edu>, and Robert Gutierrez, UT
    Type_of_Source_Media: digital data - raster grids or ascii xyz text files
    Source_Contribution:
    Provided data for coverage areas: San Diego County, Orange County, Seal Beach to Long Beach, and Point Conception to Point Mugu coastal strip.
  2. How were the data generated, processed, and modified?
    Date: 15-Jun-2009 (process 1 of 6)
    ESRI geoprocessing history
      Tool location:
        C:\ArcGIS\ArcToolbox\Toolboxes\Spatial Analyst Tools.tbx\ExtractByMask
      Command issued:
        ExtractByMask la1unclip DEMFullCoverageAreas\la1_fullcoveragearea D:\HazardsModel\DEM\FinalDEMs\CoastalHighRes\DEMs_3m\FinalMosaics\la1final
      _________________
      Spatial data description
      Raster dataset information
      Raster format: GRID
      SDTS raster type: Grid Cell
      Number of raster bands: 1
      Raster properties
      Origin location: Upper Left
      Has pyramids: FALSE
      Has colormap: FALSE
      Data compression type: Default
      Display type: matrix values
      Cell information
      Number of cells on x-axis: 7317
      Number of cells on y-axis: 8160
      Number of cells on z-axis: 1
      Number of bits per cell: 32
      Cell Size
      X distance: 3.000000
      Y distance: 3.000000
      _________________
    
    Date: 2009 (process 2 of 6)
    (Summary) Performed by Patrick Barnard and Dan Hoover:
    
      ArcGIS was the primary software used for DEM construction.
      For each individual DEM, the native data sets were mosaicked into a single grid
      to preserve the original surfaces as closely as possible.
      Prior to mosaicking, data sets were gridded and/or resampled to 3 m resolution (if necessary),
      and their spatial extents modified according to the following guidelines:
    
      1. Data sets of comparable quality
         (for example, overlapping multibeam data) or
         where relative data quality could not be determined
         (for example, older multibeam and recent but lower resolution personal-watercraft data,
         were not clipped.
         In these instances the overlapping regions were blended together
         using the Blend algorithm in the Mosaic to New Raster tool in Arc Toolbox.
    
      2. In overlapping regions where the quality of one data set was clearly inferior
         to the other (for example, IfSAR overlapping with Lidar),
         the spatial extent of the inferior data set was clipped so there was minimal overlap,
         typically about ~10-30 m, with the superior data set.
         The overlapping regions then were smoothed together using the Blend algorithm.
         This range of overlap was found to be the most efficient
         for ensuring a smooth transition between data sets
         while minimizing the use the of data set of inferior quality.
    
    Date: 2009 (process 3 of 6)
    (Detailed) Performed by Patrick Barnard and Dan Hoover:
    
      1. Divide study area into ~10 km alongshore segments
         A. Define DEM coverage area/polygon that extends
            ~10 km alongshore from -20 m isobath to 20 m topographic contour or
            750 m from back beach, whichever is longer
         B. Ensure that adjacent DEM coverage areas overlap by ~ 250 m
         C. Cut off DEMs at county boundaries with ~500 m overlap
    
      2. Acquire most recent or highest resolution data sets in DEM coverage areas (Figure 2)
         A. Lidar
         B. Multibeam bathymetry
         C. Local high-resolution beach topography (usually ATV-acquired) and
            nearshore bathymetry (usually PWC-acquired)
         D. IfSAR
    
      3. Fill gaps with older/lower resolution data sets
         A. Lidar (for example, NOAA Digital Coast, 1997-98)
         B. NOAA lower-resolution multibeam (for example, Los Angeles Harbor entrance)
         C. Regional, lower resolution DEMs (for example, NOAA Santa Barbara Channel 10-m DEM)
    
      4. Convert all data sets into identical
         horizontal coordinate system, vertical datum, and grid resolution
         A. Horizontal coordinate system: UTM NAD 83 Zone 11 North
         B. Vertical Datum: NAVD88
            -If different (usually MLLW), convert using local NOAA tide station information
            (http://tidesandcurrents.noaa.gov/) based on survey metadata
         C. Grid resolution: 3 m
            -If already gridded at higher or < 10 m resolution,
             resample to 3 m using bilinear interpolation
            -If already gridded at resolution of =10 m, export as xyz,
             re-import as xyz, create TIN (triangular irregular network),
             create 3 m grid from TIN using linear interpolation of the TIN triangles,
             clip to survey extent
            -If ungridded then for:
            -Lidar (topography):
             3 m grid using natural neighbor interpolation
             to preserve abrupt elevation changes (for example, beaches backed by cliffs)
            -Multibeam:
             3 m grid using inverse distance weighting using "Average Gridder"
             in Fledermaus- ideal for data sets >   10 million points
            -Lower resolution surveys (for example, personal watercraft-collected bathymetry):
             create TIN from points then convert to 3 m grid
             using linear interpolation of the TIN triangles
    
      5. Clip data sets to DEM/coverage needs, if necessary
         A. Useful for data management and processing efficiency
         B. Necessary for very large data sets, such as county-wide IfSAR or
            very large Lidar data sets (for example, Los Angeles County)
         C. Clip ocean and waves from topographic Lidar and IfSAR
            -Clip water level by determining sea level at time of survey then
             using "Extract by Attributes" tool in Arc Toolbox
            -Clip wave crests manually with mask
    
      6. Manage overlapping data sets
         A. Data sets allowed to overlap extensively only if they are of comparable quality,
            otherwise minimal (~10-30 m) overlap to ensure smooth DEM transitions
         B. Clip IfSAR data (lower quality)
            to minimal overlap with topographic Lidar (better quality)
         C. Clip low-resolution data sets gridded to higher resolution,
            such as Personal Watercraft data and regional DEMs,
            to minimal overlap with adjacent high-resolution data sets
            (usually multibeam and topographic Lidar)
         D. Extensive overlap between adjacent Lidar and multibeam data sets rare but
            allowed as quality is comparable
    
      7. Fill in data gaps between high-resolution data sets
         A. If no high-resolution data exist between the 10 m isobath and coastal Lidar, or
            in protected harbors/embayments or other areas where interpolation
            from surrounding data sets will create a surface unlikely
            to accurately reflect actual bathymetry/topography,
            fill in with regional DEMs or other low-resolution data sets.
            Otherwise interpolate across gaps.
            -Filling in with regional DEMs/other low-resolution data:
            -Clip best available regional DEM to fill gap with minimal overlap (~10-30 m)
             with adjacent high resolution data sets
            -Export clipped grid as xyz, reimport as points, create tin,
             create 3 m grid from tin, clip to gap extent
            -Interpolation
            -Create preliminary DEM using Mosaic tool with the following settings:
             Coordinate System: UTM Zone 11 North
             Pixel Type: 32_Bit_Float
             Cell Size:  3
             Mosaic Method: Blend
             Mosaic Color Map: Last
            -Create mask of data gap(s) to fill with minimal overlap
             with preliminary DEM surface
            -Clip preliminary DEM with mask, export clipped grid as xyz,
             reimport as points, create tin, create 3 m grid from tin, clip to gap extent
    
      8. Compile final DEMs
         A. Load all data sets for DEM
         B. Verify all significant data gaps filled (few missing cells OK) in DEM coverage area
         C. Build DEM using Mosaic to New Raster tool in ArcGIS with same setting as in Item #7
         D. Clip DEM to DEM coverage area
         E. Create contours and plot cross-shore profiles to verify data quality and consistency
    
    Date: 24-Sep-2009 (process 4 of 6)
    First draft of metadata created by Patrick Barnard using .txt template
    Date: 19-Oct-2020 (process 5 of 6)
    Edited metadata to add keywords section with USGS persistent identifier as theme keyword. No data were changed. Person who carried out this activity:
    U.S. Geological Survey
    Attn: VeeAnn A. Cross
    Marine Geologist
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 x2251 (voice)
    508-457-2310 (FAX)
    vatnipp@usgs.gov
    Date: 20-Oct-2021 (process 6 of 6)
    Edited metadata to add USGS Thesaurus keywords and perform minor edits to bring the metadata up to current PCMSC standards. No data were changed. The metadata available from a harvester may supersede metadata bundled within a download file. Users are advised to compare the metadata dates to determine which metadata file is most recent. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Susan Cochran
    Geologist
    2885 Mission Street
    Santa Cruz, CA

    831-460-7545 (voice)
    scochran@usgs.gov
  3. What similar or related data should the user be aware of?

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    Refer to the DEM Accuracy and Limitations section in this Data Series for an explanation of the accuracy of the identification of the entities and assignments of values in the data set and a description of the tests used.
  2. How accurate are the geographic locations?
    Refer to the DEM Accuracy and Limitations section in this Data Series for an explanation of the accuracy of the horizontal coordinate measurements and a description of the tests used.
  3. How accurate are the heights or depths?
    Refer to the DEM Accuracy and Limitations section in this Data Series for an explanation of the accuracy of the vertical coordinate measurements and a description of the tests used.
  4. Where are the gaps in the data? What is missing?
    Refer to the DEM Construction Methods section in this Data Series for information about omissions, selection criteria, generalization, definitions used, and other rules used to derive the data set.
  5. How consistent are the relationships among the observations, including topology?
    Refer to the DEM Construction Methods section in this Data Series for an explanation of the fidelity of relationships in the data set and tests used.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints: None
Use_Constraints:
Majority of data (that is, Lidar, multibeam bathymetry, IfSAR) derived from topographic/bathymetry data collected at 1-3 m horizontal resolution, with vertical uncertainty at time of data collection ranging from 10 cm to 1 m, Use at greater scales not advised. See accompanying Data Series report for more information: Barnard, P.L. and Hoover, D., 2009, A seamless, high-resolution, coastal digital elevation model (DEM) for southern California: U.S. Geological Survey Data Series 487, 8 p., https://doi.org/10.3133/ds487.
This information is not intended for navigational purposes.
  1. Who distributes the data set? (Distributor 1 of 1)
    United States Geological Survey (USGS)
    Attn: Patrick L Barnard
    Research Geologist
    2885 Mission Street
    Santa Cruz, CA
    USA

    (831) 427-4756 (voice)
    pbarnard@usgs.gov
  2. What's the catalog number I need to order this data set? U.S. Geological Survey Data Series 487
  3. What legal disclaimers am I supposed to read?
    Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
  4. How can I download or order the data?
    • Availability in digital form:
      Data format: Compressed file including Arcinfo grid and metadata. (version 7.2) Arcinfo grid Size: 0.526
      Network links: https://doi.org/10.3133/ds487
    • Cost to order the data: none


Who wrote the metadata?

Dates:
Last modified: 20-Oct-2021
Metadata author:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Attn: PCMSC Science Data Coordinator
2885 Mission Street
Santa Cruz, CA
USA

831-427-4747 (voice)
pcmsc_data@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)

This page is <https://cmgds.marine.usgs.gov/catalog/pcmsc/SeriesReports/DS_DDS/DS_487/DEM_fullmetadata.faq.html>
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