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Mapping Marsh Vegetation and Elevation


PIs: Christine Hladik (Department of Geology and Geography, Georgia Southern University, Stateboro, GA) former affiliation: University of Georgia

Support: Georgia Coastal Management Program, Coastal Incentive Grant

Timeframe: 2010-2012

Project Ojectives:
(1) Evaluate the accuracy of a digital elevation model (DEM) derived from light detection and ranging (LIDAR) with real time kinematic (RTK) GPS. (2) Develop species-specific correction factors for 10 marsh cover classes. (3) Use hyperspectral imagery (HSI) to classify salt marsh vegetation and apply correction factors to DEM.

Findings:

  • The unmodified DEM over-predicted elevations and resulted in mean errors of 0.03 to 0.28 m.
  • The modified DEM resulted in overall reduction of mean error and slightly under-predicted elevations.
  • None of the DEM elevations were significantly different from RTK.
  • The author concluded that DEM over-predicts ground elevations. She found that error increases with plant height and is species-specific. These results are consistent with previous studies that reported offsets ranging from 0.07 to 0.13 m for S. alterniflora. Application of correction factors reduces DEM error and greatly improves accuracy.

 

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This page was updated February 28, 2014