Digital Shoreline Analysis 4.4 used to evaluate bluff recession rates in Erie, PA, using LiDAR data.

Session: 61. - Remote Sensing, Visualization, and Spatial Data Applications for the Great Lakes

Michael Naber, Penn State Behrend, [email protected]
Sean Rafferty, Pennsylvania Sea Grant College Program, [email protected]
Anthony Foyle, Penn State Erie, The Behrend College, [email protected]

Abstract

The Digital Shoreline Analysis System (DSAS) was released in 1992 to aid scientists and managers in assessing shoreline change in a multitude of coastal settings using statistical techniques.  In our research, we evaluate a new method of bluff recession analysis using DSAS 4.4 with current and historical LiDAR data and orthoimagery. Whereas DSAS has been traditionally used to estimate linear shoreline change rates by automating measurement and computation processes, we used DSAS to evaluate another linear phenomenon, bluff crest retreat.  We used current and historical LiDAR data and stereoscopic bluff crest delineation methods to identify 3 different bluff crest-lines (2008, 2012, and 2015). DSAS was then used to generate measurement transects based on our parameters. We then used DSAS to calculate rates of bluff crest-line change. DSAS then computed bluff crest-line rates of change using four different methods: endpoint rate, simple linear regression, weighted linear regression, and least median of squares. Though DSAS’s implied intent is to evaluate shoreline change and provide rate-of-change analysis, the software proved its robustness by allowing us to calculate the positional change of bluff crest-line retreat and the statistical data needed to assess the reliability of the calculated results.

1. Keyword
GIS

2. Keyword
remote sensing

3. Keyword
Lake Erie

4. Additional Keyword
Spatial Analysis

5. Additional Keyword
Monitoring

6. Additional Keyword
Bluff Retreat