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Advances in Topobathymetric Mapping

In coastal environments, elevation is perhaps the most fundamental variable determining vulnerability. Accurate high-resolution digital elevation models (DEMs) that show both land and submerged topography (bathymetry) are key in coastal wetlands mapping and monitoring, storm surge and sea-level-rise modeling, benthic habitat mapping, coral reef-ecosystem mapping, and a host of related activities.I

This article is part of the January-February 2017 issue of the Sound Waves newsletter.

A special issue of the Journal of Coastal Research, “Advances in Topobathymetric Mapping, Models, and Applications,” edited by USGS scientists, provides a broad array of recent research findings on data, processing methods, applications, and physical processes that are critical for increased understanding of the dynamic coastal environment.

The issue offers current information for coastal-zone resource managers and provides the impetus for future research and advances in data, methods, models, and applications for the elevation mapping in a changing coastal environment.

The issue is available online at:

Articles by USGS authors

Introduction: Special Issue on Advances in Topobathymetric Mapping, Models, and Applications

Dean B. Gesch, John C. Brock, Christopher E. Parrish, Jeffrey N. Rogers, and C. Wayne Wright

Abstract: Detailed knowledge of nearshore topography and bathymetry is required for many geospatial data applications in the coastal environment. New data sources and processing methods are facilitating development of seamless, regional-scale topobathymetric digital elevation models. These elevation models integrate disparate multi-sensor, multi-temporal topographic and bathymetric datasets to provide a coherent base layer for coastal-science applications such as wetlands mapping and monitoring, sea-level-rise assessment, benthic habitat mapping, erosion monitoring, and storm-impact assessment. The focus of this special issue is on recent advances in the source data, data processing and integration methods, and applications of topobathymetric datasets.

Depth Calibration and Validation of the Experimental Advanced Airborne Research Lidar, EAARL-B

C. Wayne Wright, Christine Kranenburg, Timothy A. Battista, and Christopher E.  Parrish

Abstract: The original National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), was extensively modified to increase the spatial sampling density and improve performance in water ranging from 3–44 m. The new (EAARL-B) sensor features a 300% increase in spatial density, which was achieved by optically splitting each laser pulse into 3 pulses spatially separated by 1.6 m along the flight track and 2.0 m across-track on the water surface when flown at a nominal altitude of 300 m. Improved depth capability was achieved by increasing the total peak laser power by a factor of 10, and incorporating a new “deep-water” receiver, optimized to exclusively receive refracted and scattered light from deeper water (15–44 m). Two clear-water missions were conducted to determine the EAARL-B depth calibration coefficients. The calibration mission was conducted over the U.S. Navy’s South Florida Testing Facility (SFTF), an established lidar calibration range located in the coastal waters southeast of Fort Lauderdale, Florida. A second mission was conducted over Lang Bank, St. Croix, U.S. Virgin Islands. The EAARL-B survey was spatially and temporally coincident with multibeam sonar surveys conducted by the National Oceanic and Atmospheric Administration (NOAA) ship Nancy Foster. The NOAA depth data range from 10–100 m, whereas the EAARL-B captured data from 0–41 m. Coefficients derived from the SFTF calibration mission were used to correct the EAARL-B data from both missions. The resulting calibrated EAARL-B data were then compared with the original reference dataset, a jet-ski-based single beam sonar dataset from the SFTF site, and the deeper NOAA data from St. Croix. Additionally, EAARL-B depth accuracy was evaluated by comparing the depth results to International Hydrographic Organization (IHO) standards. Results show good agreement between the calibrated EAARL-B data and all three reference datasets, with 95% confidence levels well within the maximum allowable total vertical uncertainty for IHO Order 1 surveys.

Creating a Coastal National Elevation Database (CoNED) for Science and Conservation Applications

Cindy A. Thatcher, John C. Brock, Jeffrey J. Danielson, Sandra K. Poppenga, Dean B. Gesch, Monica E. Palaseanu-Lovejoy, John A. Barras, Gayla A. Evans, and Ann E. Gibbs

Abstract: The USGS is creating the Coastal National Elevation Database, an expanding set of topobathymetric elevation models that extend seamlessly across coastal regions of high societal or ecological significance in the United States that are undergoing rapid change or are threatened by inundation hazards. Topobathymetric elevation models are raster datasets useful for inundation prediction and other earth science applications, such as the development of sediment-transport and storm surge models. These topobathymetric elevation models are being constructed by the broad regional assimilation of numerous topographic and bathymetric datasets, and are intended to fulfill the pressing needs of decision makers establishing policies for hazard mitigation and emergency preparedness, coastal managers tasked with coastal planning compatible with predictions of inundation due to sea-level rise, and scientists investigating processes of coastal geomorphic change. A key priority of this coastal elevation mapping effort is to foster collaborative lidar acquisitions that meet the standards of the USGS National Geospatial Program’s 3D Elevation Program, a nationwide initiative to systematically collect high-quality elevation data. The focus regions are located in highly dynamic environments, for example in areas subject to shoreline change, rapid wetland loss, hurricane impacts such as overwash and wave scouring, and/or human-induced changes to coastal topography.

Topobathymetric Elevation Model Development using a New Methodology: Coastal National Elevation Database

Jeffrey J. Danielson, Sandra K. Poppenga, John C. Brock, Gayla A. Evans, Dean J. Tyler, Dean B. Gesch, Cindy A. Thatcher, and John A. Barras

Abstract: During the coming decades, coastlines will respond to widely predicted sea-level rise, storm surge, and coastal inundation flooding from disastrous events. Because physical processes in coastal environments are controlled by the geomorphology of over-the-land topography and underwater bathymetry, many applications of geospatial data in coastal environments require detailed knowledge of the near-shore topography and bathymetry. In this paper, an updated methodology used by the U.S. Geological Survey Coastal National Elevation Database (CoNED) Applications Project is presented for developing coastal topobathymetric elevation models (TBDEMs) from multiple topographic data sources with adjacent intertidal topobathymetric and offshore bathymetric sources to generate seamlessly integrated TBDEMs. This repeatable, updatable, and logically consistent methodology assimilates topographic data (land elevation) and bathymetry (water depth) into a seamless coastal elevation model. Within the overarching framework, vertical datum transformations are standardized in a workflow that interweaves spatially consistent interpolation (gridding) techniques with a land/water boundary mask delineation approach. Output gridded raster TBDEMs are stacked into a file storage system of mosaic datasets within an Esri ArcGIS geodatabase for efficient updating while maintaining current and updated spatially referenced metadata. Topobathymetric data provide a required seamless elevation product for several science application studies, such as shoreline delineation, coastal inundation mapping, sediment-transport, sea-level rise, storm surge models, and tsunami impact assessment. These detailed coastal elevation data are critical to depict regions prone to climate change impacts and are essential to planners and managers responsible for mitigating the associated risks and costs to both human communities and ecosystems. The CoNED methodology approach has been used to construct integrated TBDEM models in Mobile Bay, the northern Gulf of Mexico, San Francisco Bay, the Hurricane Sandy region, and southern California.

Hydrologic Connectivity: Quantitative Assessments of Hydrologic-Enforced Drainage Structures in an Elevation Model

Sandra K. Poppenga and Bruce B. Worstell

Abstract: Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal regions.

Modeling and Simulation of Storm Surge on Staten Island to Understand Inundation Mitigation Strategies

Michael E. Kress, Alan I. Benimoff, William J. Fritz, Cindy A. Thatcher, Brian O. Blanton, and Eugene Dzedzits

Abstract: Hurricane Sandy made landfall on October 29, 2012, near Brigantine, New Jersey, and had a transformative impact on Staten Island and the New York Metropolitan area. Of the 43 New York City fatalities, 23 occurred on Staten Island. The borough, with a population of approximately 500,000, experienced some of the most devastating impacts of the storm. Since Hurricane Sandy, protective dunes have been constructed on the southeast shore of Staten Island. ADCIRC+SWAN model simulations run on The City University of New York’s Cray XE6M, housed at the College of Staten Island, using updated topographic data show that the coast of Staten Island is still susceptible to tidal surge similar to those generated by Hurricane Sandy. Sandy hindcast simulations of storm surges focusing on Staten Island are in good agreement with observed storm tide measurements. Model results calculated from fine-scaled and coarse-scaled computational grids demonstrate that finer grids better resolve small differences in the topography of critical hydraulic control structures, which affect storm surge inundation levels. The storm surge simulations, based on post-storm topography obtained from high-resolution lidar, provide much-needed information to understand Staten Island’s changing vulnerability to storm surge inundation. The results of fine-scale storm surge simulations can be used to inform efforts to improve resiliency to future storms. For example, protective barriers contain planned gaps in the dunes to provide for beach access that may inadvertently increase the vulnerability of the area.

Automatic Delineation of Seacliff Limits using Lidar-derived High-resolution DEMs in Southern California

Monica Palaseanu-Lovejoy, Jeff Danielson, Cindy Thatcher, Amy Foxgrover, Patrick Barnard, John Brock, and Adam Young

Abstract: Seacliff erosion is a serious hazard with implications for coastal management and is often estimated using successive hand-digitized cliff tops or bases (toe) to assess cliff retreat. Even if efforts are made to standardize manual digitizing and eliminate subjectivity, the delineation of cliffs is time-consuming and depends on the analyst’s interpretation. An automatic procedure is proposed to extract cliff edges from high-resolution lidar-derived bare-earth digital elevation models, generalized coastal shoreline vectors, and approximate measurements of distance between the shoreline and the cliff top. The method generates orthogonal transects and profiles with a minimum spacing equal to the digital elevation model resolution. The method also extracts the xyz coordinates for each profile for the cliff top and toe, as well as second major inflections along the profile. Over 75% of the automated cliff top points and 78% of the toe automated points are within 95% confidence interval of the hand-digitized top and toe lines, and over 79% of the digitized top points and 84% of the digitized toe points are within the 95% confidence interval of the automated top and toe lines along a stretch of coast in Del Mar, California. Outlier errors were caused by either the failure to remove all vegetation from the bare-earth digital elevation model or errors of interpretation. The automatic method was further applied between Point Conception and Los Angeles Harbor, California. This automatic method is repeatable, takes advantage of detailed topographic information within high-resolution digital elevation models, and is more efficient than hand-digitizing.

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