Subpixel Mapping of Wetland Inundation Using Time-Series Landsat Data: An Assessment of Its Sensitivity to Climate Change Indices

Thursday, 18 December 2014
Huiran Jin1, In-Young Yeo1, Chengquan Huang1 and Megan W Lang1,2, (1)University of Maryland, College Park, MD, United States, (2)USDA-ARS, Silver Spring, MD, United States
Wetland inundation and saturation dynamics are the most important abiotic factor controlling the extent and functioning of wetlands. Remote sensing provides a major data source for monitoring wetland dynamics. In this study, we developed a new approach to map wetland inundation in the Delmarva Peninsula from 1985 to 2011. Highly accurate subpixel inundation percentage (SIP) maps were first derived at the 30 m resolution from LiDAR intensity data. These SIP maps were used as reference to establish statistical relationships between SIP and Landsat data. Regional wetland inundation was then mapped by applying the constructed model to Landsat scenes acquired in different years. Results showed that accurate maps of wetland inundation can be created using this approach, and that Landsat data can be calibrated to reveal the inundation state of wetlands and the long-term trend of wetland dynamics at the regional scale. Substantial changes in wetland inundation among dry, average, and wet years were observed, and the changes were found correlated with local drought conditions, particularly in highly inundated areas. Given the fact that Landsat data are globally available and LiDAR data are becoming increasingly affordable and available, the approach developed in this study has the potential for deriving historical inundation changes over the past decades and for monitoring ongoing changes over much larger areas.