Corrected digital elevation model in coastal wetlands in Nassau and Duval Counties, Florida, 2018

High-resolution elevation data provide a foundational layer needed to understand regional hydrology and ecology under contemporary and future-predicted conditions with accelerated sea-level rise. While the development of digital elevation models (DEMs) from light detection and ranging data has enhanced the ability to observe elevation in coastal zones, the elevation error can be substantial in densely vegetated coastal wetlands. In response, we developed a machine learning model to reduce vertical error in coastal wetlands for a 1-m DEM from 2018 that covered Nassau and Duval Counties, Florida. Error was reduced by using a random forest regression model within situ observations and predictor variables from optical...

Tags: Duval, Ecology, Florida, Geography, Nassau, All tags... Remote Sensing, South Atlantic, Timucuan Ecological And Historic Preserve, USGS Science Data Catalog (SDC), United States, coastal ecosystems, coastal elevation error reduction, digital elevation models, elevation, elevation error, geoscientificInformation, imageryBaseMapsEarthCover, machine learning, random forest regression model, wetland ecosystems, Fewer tags