The detection and prediction of sea level changes on coastal wetlands using satellite imagery and a geographic information system

Abstract

Abstract This research summarizes the use of remote sensor data and high resolution digital elevation models (DEMs) to predict the effect of sea level rise on the Fort Moultrie coastal region near Charleston, South Carolina. In situ and remotely sensed data were used to construct and densify the DEM. Landsat Thematic Mapper (TM) images obtained on multiple dates were used to inventory the Spartina alterniflora and other land cover in the region. It was then possible to a) determine the effect of tidal stage on remotely sensed classification/change detection products, and b) predict the impact of various sea level rise scenarios on the coastal region. This study used several geographic information system (GIS) functions to predict the effects of sea level rise. The research also demonstrates the utility of using remotely sensed data for detecting water level changes, using both visual interpretation and change detection techniques.