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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.
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, 8p.Online Links:
This is a Raster data set. It contains the following raster data types:
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.
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 Geologial Survey (USGS)
from Pete Dartnell and from David Finlayson;
University of Texas at Austin (UT)
from Randy Bucciarielli and from Robert Gutierrez.
(831) 427-4756 (voice)
(831) 427-4748 (FAX)
pbarnard@usgs.gov
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.
California State University, Monterey Bay, Unknown, Multibeam bathymetry.Online Links:
Fugro Pelagos, Inc. for California State Waters Map, Unknown, Multibeam bathymetry.
Fugro Pelagos, Inc., Unknown, Scanning Hydrographic Operational Airborne Lidar Survey (SHOALS).
County, Los Angeles , Unknown, Lidar (topo).
National Geophysical Data Center, Unknown, Regional Digital Elevation Model (DEM).Online Links:
National Oceanic and Atmospheric Administration, Unknown, IfSAR, LIDAR (topo), multibeam bathymetry, and tsunami DEM.Online Links:
San Diego Association of Governments, Unknown, Multibeam bathymetry.
Scripps Institution of Oceanography, Unknown, ATV/PWC and CHARTS Lidar (Topo+Bathy).Online Links:
United States Geologial Survey, Unknown, Z-2-06-SC, Z-1-07-SC, and S-8-08-SC multibeam bathymetry; S-V2-06-CA and S-V1-07-CA personal watercraft (PWC).Online Links:
- <http://walrus.wr.usgs.gov/infobank/z/z206sc/html/z-2-06-sc.meta.html>
- <http://walrus.wr.usgs.gov/infobank/z/z107sc/html/z-1-07-sc.meta.html>
- <http://walrus.wr.usgs.gov/infobank/s/s808sc/html/s-8-08-sc.meta.html>
- <http://walrus.wr.usgs.gov/infobank/s/sv206ca/html/s-v2-06-ca.meta.html>
- <http://walrus.wr.usgs.gov/infobank/s/sv107ca/html/s-v1-07-ca.meta.html>
University of Texas at Austin, Unknown, Lidar (topo).Online Links:
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
_________________
(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 mosaiced into a single grid
to preserve the original surfaces as closely as possible.
Prior to mosaicing, 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.
(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 waterscraft-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
United States Geological Survey, 2009, Southern California Coastal Hazards.Online Links:
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.
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.
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.
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.
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.
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 full 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://pubs.usgs.gov/ds/487/>.
This information is not intended for navigational purposes.
(831) 427-4756 (voice)
(831) 427-4748 (FAX)
pbarnard@usgs.gov
U.S. Geological Survey Data Series 487
Please recognize the U.S. Geological Survey (USGS) as the source of this information.Although these data have been used by the U.S. Geological Survey, U.S. Department of the Interior, no warranty expressed or implied is made by the U.S. Geological Survey as to the accuracy of the data.
The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the U.S. Geological Survey in the use of this data, software, or related materials.
| Data format: | Compressed file including Arcinfo grid and metadata. (version 7.2) Arcinfo grid Size: 0.526 |
|---|---|
| Network links: |
<https://pubs.usgs.gov/ds/487/> |
(831) 427-4756 (voice)
(831) 427-4748 (FAX)
pbarnard@usgs.gov