Coverage Polygons for DEMs of the North-Central California Coast (DEM_coverage_areas.shp)

(Summary) Performed by Amy Foxgrover and Patrick Barnard: ArcGIS was the primary software used for DEM construction. For each individual DEM, the native datasets were mosaicked into a single grid to preserve the original surfaces as closely as possible. Prior to mosaicking, datasets were gridded and (or) resampled to 2 m resolution (if necessary), and their spatial extents modified according to the following guidelines: 1. Datasets of comparable quality (for example, overlapping multibeam data), collected over the same time period 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. The exception to this is for topographic data along the shoreline. Multiple high-resolution aerial lidar surveys were collected along the shoreline in 2010. Since the nearshore is a very dynamic region that can be modified greatly by a single storm event, rather than blending multiple high-resolution datasets (which could produce unrealistic beach morphology), data from a single time period were selected for use. Where possible, we used data collected in the fall for nearshore elevations to minimize the potential of winter storm effects. 2. In overlapping regions where the quality of one dataset was clearly inferior to the other (for example, regional 10-m resolution DEMs overlapping with 2-m resolution lidar), the spatial extent of the inferior dataset was clipped so there was minimal overlap, typically about ~20 m, with the superior dataset. 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 datasets while minimizing the use of lower quality data. The spatial extent of each dataset used is included as a GIS shapefile. In addition, the areas of overlap were typically well outside of the dynamic coastal zone, which was typically covered by a single lidar pass, so any blending should have minimal impact for this important region.

(Detailed DEM Construction Procedures) Performed by Amy Foxgrover and Patrick Barnard:

1. Divide study area into ~10 km alongshore segments
    A. Define DEM coverage area/polygon that extends ~10 km alongshore, from 3 nautical
       miles offshore inland beyond the +20 m topographic contour
    B. Ensure that adjacent DEM coverage areas overlap by ~250 m
2. Acquire most recent or highest resolution data sets in DEM coverage areas
    A. Lidar
    B. Multibeam bathymetry
    C. Local high-resolution beach topography (usually ATV-acquired) and nearshore bathymetry
       (usually PWC-acquired).
3. Fill gaps with older/lower resolution datasets
    A. Lower resolution DEMs - for example, NGDC's 10-m resolution tsunami inundation DEM,
       (Carignan and others, 2011) in Bodega Harbor
    B. Bathymetric data derived from single beam bathymetry - for example, 1980s survey in Drakes
       Estero and 1998 bathymetry in Bolinas Lagoon
4. Convert all datasets into identical horizontal coordinate system, vertical datum, and grid resolution
    A. Horizontal coordinate system: UTM NAD83 Zone 10 North
    B. Vertical Datum: NAVD88
        I.   If different [usually Mean Lower Low Water(MLLW)], convert using local NOAA tide station information
             [http://tidesandcurrents.noaa.gov/ (last accessed December 12, 2011)] based on survey metadata
    C. Grid resolution: 2 m
        I.   If already gridded at higher (<2 m) resolution, resample to 2 m using bilinear interpolation
        II.  If already gridded at a lower resolution (> 2m), export as xyz file, reimport as xyz point data, create TIN
             (triangular irregular network), create 2-m grid from TIN using linear interpolation of the TIN triangles,
             and clip to survey extent
        III. Ungridded:
             a) Lower resolution surveys (for example, PWC-collected bathymetry): create TIN from points then
                convert to 2-m grid using linear interpolation of the TIN triangles
5. Clip datasets to DEM/coverage needs, if necessary
    A. Useful for data management and processing efficiency
    B. Necessary for very large datasets, such as county-wide lidar datasets (for example, Golden Gate Lidar Project data)
    C. Remove ocean water surfaces and offshore rocky outcrops/islands
        I.   Aerial topographic lidar from 2010 was provided as bare-earth hydro-flattened DEMs.  The breakline polygons provided
             with aerial lidar data were used to generate 2-m resolution grids of water surfaces over the ocean or tidal embayments
             where bathymetric data was to be inserted.  Use this grid to mask out water surfaces in the topographic DEM using the
             Set Null tool in Arc Toolbox.
        II.  Hydro-flattened surfaces of small inland water bodies were retained in the final DEM.  Since these areas are of less
             importance for this research, no attempt was made to obtain bathymetric depths for these inland ponds or lakes (for example,
             Lake Merced in San Francisco). Hydro-flattened features that were retained in the final DEM are provided in shapefile format.
        III. Extract small islands and rocky outcrops from topographic lidar datasets using breaklines provided.  These features are
             not included in the nearshore interpolation, but are incorporated into the final DEM in step 8.
6. Manage overlapping datasets
    A. Data sets were allowed to overlap extensively only if they are from the same time period, of comparable quality, and not within
       the dynamic nearshore region, otherwise allow only minimal (~10-30 m) overlap to ensure smooth DEM transitions
    B. Clip low-resolution datasets pushed to 2-m resolution, such as Personal Watercraft data and regional DEMs, to minimal overlap
       with adjacent high-resolution data sets (usually multibeam and topographic lidar)
    C. Clip topographic lidar so that only a single dataset is used for the coastal zone.  Where it exists, the USGS lidar is given highest
       preference in the nearshore zone because it was collected in the summer and fall of 2010 when the beach morphology was less likely to
       influenced by winter storm events.  The Golden Gate Lidar Project data are used for all reaches landward of the USGS lidar coverage (roughly
       10-m elevation and higher) and along the coastline where USGS lidar was not collected.  The OPC lidar is present only in two small sections
       that are not covered by USGS or GGLP lidar (within DEM sections 1 and 14).
7. Fill in data gaps between high-resolution data sets
    A. If no high-resolution data are available between the offshore multibeam bathymetry and coastal topographic lidar in protected
       harbors/embayments, or in other areas where interpolation from surrounding data sets will create a surface unlikely to reflect actual
       bathymetry/topography accurately, fill in gaps with regional DEMs or other low-resolution data sets. Otherwise, interpolate across gaps.
        I.   Filling in harbors or embayments using regional DEMs/other low-resolution data:
             a) Clip best available regional DEM or bathymetry to gap area, allowing only minimal overlap (~20 m) with adjacent high-resolution
                data sets
             b) Export clipped grid as xyz, reimport as points, create TIN, create 2-m grid from TIN, clip to gap extent
        II.  Interpolation across nearshore gaps:
             a) Create preliminary DEM using Mosaic tool with the following settings:
                Coordinate System: UTM Zone 10 North
                Pixel Type: 32 Bit Float
                Cell Size:  2
                Mosaic Method: Blend
                Mosaic Color Map: Last
             b) Create polygon of data gap(s) to fill within the preliminary DEM surface
             c) Buffer the data gap polygon with a linear distance of 20 m using the Buffer tool in Arc Toolbox
             d) Clip preliminary DEM using the buffered polygon, export clipped grid as xyz file, reimport as points (fig. 3B), create TIN, create 2-m
                grid from TIN, clip to buffered gap extent
        III. Interpolation around perimeter of Bolinas Lagoon and Drakes Estero:
             a) Fill any narrow gaps between bathymetry grids of Bolinas Lagoon and Drakes Estero and the nearest high-resolution topography
                using the same procedure as used above for interpolating across nearshore gaps.
8. Compile final DEMs
    A. Load all datasets for DEM
    B. Verify all significant data gaps filled (few missing cells allowed) in DEM coverage area
    C. Build interim DEM using Mosaic to New Raster tool in ArcGIS with same setting as noted above in Step 7
    D. Build final DEM using Mosaic to New Raster tool in ArcGIS.  Input rasters are the above interim DEM and a grid of small islands or rocky
       outcrops obtained from lidar.  The islands are given top priority in the mosaicking algorithm so that island elevations from the lidar overwrite
       elevations from the nearshore interpolation.
    E. Clip output to DEM coverage area
    F. Create contours and plot cross-shore profiles to verify data quality and consistency

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