ABSTRACT

This chapter introduces a hybrid approach that integrated object-based segmentation, stratified classification, combination of visual identification and manual selection for mapping salt marshes in the lagoon and estuarine environment of the Long Island, New York. The approach engaged multisource data including Landsat-8 Operational Land Imagers (OLI) data acquired in July 2018, the land cover data of estuarine classes, e.g., estuarine emergent wetland and estuarine scrub/shrub wetland, from the 2010 NOAA’s Coastal Change Analysis Program (C-CAP) data, and the fine spatial resolution geospatial data as references. The advantages of this hybrid approach include that it values the existing coastal land cover mapping efforts, keeps the classification scheme consistent, meets the goal of updating salt marsh maps for a particular coastal section, and is valid for change analysis and monitoring. This hybrid approach is practical for future mapping replications and helpful for coastal change analysis, monitoring, and management practices.