GEOBIA Vegetation Mapping in Great Smoky Mountains National Park with Spectral and Non-spectral Ancillary Information

摘要

Vegetation mapping was performed using geographic object-based image analysis (GEOBIA) and very high spatial resolution (VHR) imagery for two study areas in Great Smoky Mountains National Park. This study investigated how accurately GEOBIA with ancillary data emulates manual interpretation in rugged mountain areas for multi-level vegetation classes of the National Vegetation Classification System (NVCS). It was discovered that the incorporation of texture and topographic variables with spectral datafrom scanned color infrared aerial photographs increased the overall accuracy of GEOBIA vegetation classification by 2.8 percent and 5.0 percent Kappa. In a separate study using multispectral Ikonos imagery, the use of elevation, aspect, slope and proximity to streams produced NVCS macro-group vegetation segmentations that resembled manual interpretation and significantly improved the overall accuracy to 76.6 percent, Kappa 0.57. Ancillary information may thus aid in GEOBIA vegetation mapping for updating vegetation inventories in rugged mountain areas.