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Adjusting Lidar-Derived Digital Terrain Models in Coastal Marshes Based on Estimated Aboveground Biomass Density

S. Medeiros,S. Hagen,J. Weishampel,J. J. Angelo

Published 2015 in Remote Sensing

ABSTRACT

Digital elevation models (DEMs) derived from airborne lidar are traditionally unreliable in coastal salt marshes due to the inability of the laser to penetrate the dense grasses and reach the underlying soil. To that end, we present a novel processing methodology that uses ASTER Band 2 (visible red), an interferometric SAR (IfSAR) digital surface model, and lidar-derived canopy height to classify biomass density using both a three- class scheme (high, medium and low) and a two-class scheme (high and low). Elevation adjustments associated with these classes using both median and quartile approaches were applied to adjust lidar-derived elevation values closer to true bare earth elevation. The performance of the method was tested on 229 elevation points in the lower Apalachicola River Marsh. The two-class quartile-based adjusted DEM produced the best results, reducing the RMS error in elevation from 0.65 m to 0.40 m, a 38% improvement. The raw mean errors for the lidar DEM and the adjusted DEM were 0.61 ± 0.24 m and 0.32 ± 0.24 m, respectively, thereby reducing the high bias by approximately 49%.

PUBLICATION RECORD

  • Publication year

    2015

  • Venue

    Remote Sensing

  • Publication date

    2015-03-25

  • Fields of study

    Geology, Computer Science, Environmental Science

  • Identifiers
    DOI 10.3390/RS70403507
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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