Description: This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the United States and its Territories. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979). The National Wetlands Inventory - Version 2, Surface Waters and Wetlands Inventory was derived by retaining the wetland and deepwater polygons that compose the NWI digital wetlands spatial data layer and reintroducing any linear wetland or surface water features that were orphaned from the original NWI hard copy maps by converting them to narrow polygonal features. Additionally, the data are supplemented with hydrography data, buffered to become polygonal features, as a secondary source for any single-line stream features not mapped by the NWI and to complete segmented connections. Wetland mapping conducted in WA, OR, CA, NV and ID after 2012 and most other projects mapped after 2015 were mapped to include all surface water features and are not derived data. The linear hydrography dataset used to derive Version 2 was the U.S. Geological Survey's National Hydrography Dataset (NHD). Specific information on the NHD version used to derive Version 2 and where Version 2 was mapped can be found in the 'comments' field of the Wetlands_Project_Metadata feature class. Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery. By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps. This dataset should be used in conjunction with the Wetlands_Project_Metadata layer, which contains project specific wetlands mapping procedures and information on dates, scales and emulsion of imagery used to map the wetlands within specific project boundaries.
Description: High resolution (0.15 m (0.05 ft)) four-band orthoimagery was acquired from December 2012 to January 2013 as part of the Coastal Imagery Project for Chatham, Bryan, Liberty, McIntosh, and Glynn counties. Camden County separately acquired three-band, 0.15 m (0.5 ft) resolution orthoimagery from February to March 2012. All orthoimagery data have a horizontal accuracy of ≤ 0.76 m (2.5 ft). For this project, the orthoimagery was subsetted by county and resampled to a 4 m (13.12 ft) spatial resolution. Orthoimagery for each county was classified using the random forest classifier using the R (version 3.2.1) package randomForest. Three raster image products were used as predictor variables in random forest to produce classified maps of habitat distributions: orthoimagery reflectance (3 or 4 bands), DEM elevations, and NWI Plus class. Four orthoimagery bands (blue, green, red, near infrared (NIR)) were used in the classification of Chatham, Bryan, Liberty, McIntosh, and Glynn counties. As Camden County orthoimagery was acquired without the NIR band, three bands (blue, green, red) were used for its classification. Training data for random forest were generated by digitizing vegetation areas from field maps at 596 randomly selected ground control points. In the field at each sampling location, large-scale maps of the site and surrounding area where annotated with vegetation boundaries and notes on the distribution of marsh vegetation. Polygons were digitized from the field maps using the resampled 4 m (13.12 ft) orthophotography at a minimum scale of 1:500. All dominant tidal marsh covers were classified, including non-vegetated areas. This resulted in eight classes for which training data were generated: three height classes of Spartina alterniflora (tall, medium, short); Juncus roemerianus/Schoenoplectus spp.; Spartina cynosuroides/Schoenoplectus tabernaemontani; marsh meadow (Salicornia virginica(Sarcoconia sp.), Distichlis spicata, Batis maritima); mud; and unvegetated areas. The mud class included both mud found at higher elevations on the marsh platform and lower elevations along creek banks and exposed tidal flats. Unvegetated areas were comprised of highly reflective surfaces including shell, sand, beach, pavement, and docks. Classification accuracy was calculated based on the out-of-bag error estimate. Each county was classified independently and mosaicked together post-classification. Focal statistics (3x3 window) were used to remove the salt and pepper appearance of the classification and remove isolated pixels. The random forest classifier performed well, with a combined overall accuracy of 0.90 for an eight-class habitat map. The overall accuracy of individual county random forest classifications ranged from 0.85 (Camden) to 0.95 (Bryan).
Copyright Text: Dr. Christine Hladik, Georgia Southern University, chladik@georgiasouthern.edu
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Description: The NWI Plus was reclassed in ArcGIS 10 to include the following classes: regularly flooded marsh (salt marsh), irregularly flooded marsh (brackish marsh), paulstrine emergent (tidal fresh marsh), tidal flat (mud), and estuarine beach (unvegetated) based on Cowardin wetland code (Cowardin et al. 1979)