Topographic Metrics for Improved Mapping of Forested Wetlands

Abstract

We investigated the predictive strength of forested wetland maps produced using digital elevation models (DEMs) derived from Light Detection and Ranging (LiDAR) data and multiple topographic metrics, including multiple topographic wetness indices (TWIs), a TWI enhanced to incorporate information on water outlets, normalized relief, and hybrid TWI/relief in the Coastal Plain of Maryland. LiDAR DEM based wetland maps were compared to maps of inundation and existing wetland maps. TWIs based on the most distributed FD8 (8 cells) and somewhat distributed D∞ (1–2 cells) flow routing algorithms were better correlated with inundation than a TWI based on a non-distributed D8 (1 cell) flow routing algorithm, but D∞ TWI class boundaries appeared artificial. The enhanced FD8 TWI provided good prediction of wetland location but could not predict periodicity of inundation. Normalized relief provided good prediction of inundation periodicity but was less able to map wetland boundaries. A hybrid of these metrics provided good measurement of wetland location and inundation periodicity. Wetland maps based on topographic metrics included areas of flooded forest that were similar to an aerial photography based wetland map. These results indicate that LiDAR based topographic metrics have potential to improve accuracy and automation of wetland mapping.