Submerged aquatic vegetation habitat product development: On-screen digitizing and spatial analysis of Core Sound

Abstract

A hydrophyte of high relevance, submerged aquatic vegetation (SAV) is of great importance to estuarine environments. SAV helps improve water quality, provides food and shelter for waterfowl, fish, and shellfish, as well as protects shorelines from erosion. In coastal bays most SAV was eliminated by disease in the 1930's. In the late 1960's and 1970's a dramatic decline of all SAV species was correlated with increasing nutrient and sediment inputs from development of surrounding watersheds (MDNP et. al 2004). Currently state programs work to protect and restore existing wetlands, however, increasing development and population pressure continue to degrade and destroy both tidal and non-tidal wetlands and hinder overall development of SAV growth.The focus of this research was to utilize spatial referencing software in the mapping of healthy submerged aquatic vegetation (SAV) habitats. In cooperation with the United States Fish and Wildlife Service (USFWS), and the National Oceanic and Atmospheric Administration (NOAA), students from Elizabeth City State University (ECSU) developed and applied Geographic Information Systems (GIS) skills to evaluate the distribution and abundance of SAV in NorthCarolina's estuarine environments.Utilizing ESRI ArcView, which includes ArcMap, ArcCatalog and ArcToolbox, and the applications of on-screen digitizing, an assessment of vegetation cover was made through the delineation of observable SAV beds in Core Sound, North Carolina. Aerial photography of the identified coastal water bodies was taken at 12,000 feet above mean terrain (AMT) scale 1:24,000. The georeferenced aerial photographs were assessed for obscurities and the SAV beds were digitized. Through the adoption of NOAA guidelines and criteria for benthic habitat mapping using aerial photography for image acquisition and analysis, students delineated SAV beds and developed a GIS spatial database relevant to desired results. This newly created database yielded products in the form of usable shapefiles of SAV polygons, as well as attribute information with location information, area in hectares, and percent coverage of SAV.