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

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%.

The Impact of Lidar Elevation Uncertainty on Mapping Intertidal Habitats on Barrier Islands

“…Our results confirm findings of others, which suggest that lidar DEMs can have a substantial level of vertical uncertainty in intertidal areas [17][18][19], and this uncertainty should be accounted for if data are directly used in classification algorithms for habitat mapping or for use in sea-level rise modeling efforts [42,43]. Our findings highlighted that optimal results with regards to the maximum identification of actual intertidal areas (i.e., highest producer's accuracy) are likely produced when site-specific RTK GPS data are used.…”

“…For this reason, we chose to use a simple method of introducing spatial autocorrelation into the Monte Carlo processing by using a low-pass filter rather than a more complex approach, such as the weighted spatial dependence approach [26]. A more systematic sampling of lidar error in intertidal areas similar to the approaches applied by Medeiros et al [17] or Buffington et al [18] would allow for a more complex treatment of spatial autocorrelation. As stated earlier, analyses in this effort were restricted to intertidal areas above MSL due to the use of topographic lidar.…”

Dynamic simulation and numerical analysis of hurricane storm surge under sea level rise with geomorphologic changes along the northern Gulf of Mexico

“…NGOM3 mesh was applied and spans the western north Atlantic tidal (WNAT) model domain with model resolution down to 20 m along the NGOM coast [ Bilskie et al , b] The high model resolution was included to incorporate high topographic accuracy as well as provide high spatial resolution in the model result [ Bilskie and Hagen , ; Bilskie et al , a]. A new feature added for this work was the inclusion of biomass‐corrected topographic elevations within the lower Apalachicola River marsh system [ Medeiros et al , ]. The NGOM3 mesh was developed to represent ca.…”

The Challenges of Remote Monitoring of Wetlands

“…Their approach identified numerous small wetlands that had previously not been included in a statewide database. Medeiros and colleagues [81] incorporated lidar data with data from a passive optical sensor (MODIS) and interferometric SAR to tackle improvements needed for digital elevation models in coastal salt marshes. They adjusted initial bare-earth elevation estimates based on vegetation canopy heights and densities to generate an improved bare-earth elevation layer for their study area in northwestern Florida, USA.…”