Paper No. 17
Presentation Time: 1:15 PM

HIGH RESOLUTION CRITICAL HABITAT MAPPING AND CLASSIFICATION OF TIDAL FRESHWATER WETLANDS IN THE ACE BASIN


STRICKLAND, Melissa A., College of Charleston, Charleston, SC 29403, LEVINE, Norman, Geology and Environmental Geosciences, College of Charleston, 66 George St, Charleston, SC 29424 and UPCHURCH, Saundra, South Carolina Department of Natural Resources, Charleston, SC 29412, mastrick@g.cofc.edu

In collaboration with the South Carolina Department of Natural Resources ACE Basin National Estuarine Research Reserve (ACE Basin NERR), the tidal freshwater ecosystems along the South Edisto River in the ACE Basin have been accurately mapped and classified using a LIDAR-Remote Sensing Fusion technique that integrates LAS LIDAR data into texture images and then merges the elevation textures and multispectral imagery for very high resolution mapping. This project discusses the development of an ArcGIS Toolbox capable of automating protocols and procedures for marsh delineation and microhabitat identification. The result is a high resolution habitat vegetation and land use map used for the identification of threatened habitat. Tidal freshwater wetlands are also critical habitat for colonial wading birds and an accurate assessment of community diversity and acreage of this habitat type in the ACE Basin will support SCDNR’s conservation and protection efforts. The maps developed by this study will be used to better monitor the freshwater/saltwater interface and establish a baseline for an ACE NERR monitoring program to track the rates and extent of alterations due to projected environmental stressors. The habitat data generated will update the 1999 habitat characterization of the area performed by the South Carolina Gap Analysis Program (GAP). The maps developed in this study are being validated by three separate methods, visual inspection of the 2011 aerial orthophotos, visual correlation from airborne oblique photography, and finally will include ground-truthing in the field. Current estimates of marsh accuracies are near 90% at a 3-5 meter accuracy throughout the study area.