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Towards Predicting Coastal Vulnerability to Natural Hazards: Brian H. Bossak
Project Title: Towards Predicting Coastal Vulnerability to Natural Hazards: A GIS-Based Approach utilizing NASA’s Experimental Airborne Advanced Research LIDAR (EAARL)
Mendenhall Fellow: Brian H. Bossak, (727) 803-8747, x. 3046,
Duty Station: St. Petersburg, FL
Start Date: October 1, 2003
Education: Ph.D. (Geography), Florida State University, 2003
Research Advisor: Robert Morton, (727) 803-8747, x. 3080,; Asbury Sallenger, (727) 803-8747, x. 3015,
  Brian Bossak

Project Description: Coastal storms on the Atlantic coast include tropical cyclones, such as hurricanes, and extratropical systems such as Nor’easters. These storms are responsible for damage to structures, dune erosion, and shoreline reshaping along coastal regions. Although coastal damage from tropical cyclones is widely publicized and can be extreme (as in Hurricane Camille of 1969), the spatial extent of the most serious damage is relatively small. In contrast, Nor’easters are capable of extensive coastal damage over much larger sections of coastline than tropical cyclones, as in the 1962 Ash Wednesday and 1991 All Hallows Eve storms.

This research project is a step towards predicting the effect of coastal storms on shorelines and dune structures. The U.S. Geological Survey has been working on the development of coastal change prediction algorithms; this work will use some of these models in a GIS environment, due to the many benefits of GIS for coastal research purposes, including simplified data access, ease of editing and updating, and on-the-fly visualization of coastal hazards. This pilot project will focus on Assateague Island, Maryland/Virginia.

Assateague Island has been selected as a test site partly because it has near full-island EAARL coverage. The EAARL LIDAR dataset (from surveys flown in 2002) is generated from an experimental NASA airborne sensor that is capable of detecting 2nd returns from the laser pulse, and it therefore provides the most accurate topographic information available for the island (± 15 cm vertical accuracy). This LIDAR dataset for Assateague was preceded by near-full-island Airborne Topographic Mapper (ATM) LIDAR surveys (based on the 1st return of the laser pulse) that were flown in 1997 and 1998. Moreover, much of the dune structure on the island allows for the selection of dune crests/bases, and Sallenger Storm Impact Scales can then be used to characterize coastal changes following storms. Dune high/low positions can be somewhat difficult to assess via remotely-sensed data; therefore, the research will also examine the effectiveness of an alternate coastal impact prediction methodology that utilizes gridded elevation and beach slope datasets derived from EAARL LIDAR surveys.

The end result of the project will be a GIS-based tool called the Coastal Impact Assessment Tool (CIAT), which will predict Sallenger Storm Impact Scales based on input parameters such as wave height, period, and tidal records. The tool will also allow for the rapid access of multiple data layers, including USGS Digital Elevation Models (DEMs), Digital Raster Graphics (DRGs) – digitized USGS topographic maps, and Aerial Photography (both newer and historical). Data pertaining to the historical storm of record for this island, the Ash Wednesday storm of March, 1962, will also be included in the project. In addition to using the model for prediction purposes based on the 2002 EAARL data, hindcasts will be run on the ATM LIDAR data that exists before and after two strong Nor’easters that affected the island in the winter of 1998. Parameter input to the CIAT via a user-manipulated dialog box is expected to be minimal in order to facilitate ease of use. Another key component is likely to be the 3-dimensional visualization of shorelines and the storm impact scale layer. It is anticipated that the CIAT will be applicable to additional coastal regions with minor modifications, and that migration to a web-enabled tool will be future possibility.

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Last modified: 16:08:26 Thu 13 Dec 2012