Authors

S. Medeiros; S. Hagen; J. Weishampel;J. Angelo

Comments

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Abbreviated Journal Title

Remote Sens.

Keywords

SEA-LEVEL RISE; ACCURACY ASSESSMENT; SALT MARSHES; WETLANDS; IMPACT; RADAR; 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%.

Journal Title

Remote Sensing

Volume

7

Issue/Number

4

Publication Date

1-1-2015

Document Type

Article

Language

English

First Page

3507

Last Page

3525

WOS Identifier

WOS:000354789300005

ISSN

2072-4292

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