Mapping freshwater deltaic wetlands and aquatic habitats at multiple scales with high-resolution multispectral WorldView-2 imagery and Indicator Species Analysis

Remote sensing technology has long been used in wetland inventory and monitoring though derived wetland maps were limited in applicability and often unsatisfactory largely due to the relatively coarse spatial resolution of conventional satellite imagery. The advent of high-resolution multispectral satellite systems presents new and exciting capabilities in mapping wetland systems with unprecedented accuracy and spatial detail. This research explores and evaluates the use of high-resolution WorldView-2 (WV2) multispectral imagery in identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta, a Ramsar Wetland of International Importance that drains into Lake Baikal, Russia - a United Nations World Heritage site. A hybrid approach was designed and applied for WV2 image classification consisting of initial unsupervised classification, training data acquisition and analysis, indicator species analysis, and final supervised classification. A hierarchical scheme was defined and adopted for classifying aquatic habitats and wetland vegetation at genus and community levels at a fine scale, while at a coarser scale representing wetland systems as broad substrate and vegetation classes for regional comparisons under various existing wetland classification systems. Rigorous radiometric correction of WV2 images and orthorectification based on GPS-derived ground control points and an ASTER global digital elevation model resulted in 2- to 3-m positional accuracy. We achieved overall classification accuracy of 86.5% for 22 classes of wetland and aquatic habitats at the finest scale and >91% accuracy for broad vegetation and aquatic classes at more generalized scales. At the finest scale, the addition of four new WV2 spectral bands contributed to a classification accuracy increase of 3.5%. The coastal band of WV2 was found to increase the separation between different open water and aquatic habitats, while yellow, red-edge, and near-infrared 2 bands were more useful for discriminating between different vegetated habitats. Analyses demonstrated that the Normalized Difference Vegetation Index was valuable for improving the classification accuracy and image texture was particularly useful for separating scrub/shrub wetland from various emergent herbaceous wetlands. Our analysis resulted in the first-ever detailed, quantitative wetland inventory map of the Selenga River Delta, and provides a benchmark for future wetland change detection studies and baseline information for wetland conservation and management efforts for this region.