Citation:

CLINTON, P. J. AND D. R. YOUNG. USING IMAGE PROCESSING METHODS WITH RASTER EDITING TOOLS FOR MAPPING EELGRASS DISTRIBUTIONS IN PACIFIC NORHWEST ESTUARIES. Presented at Coastal GeoTools '07, Myrtle Beach, SC, March 05 - 08, 2007.

Description:

False-color near-infrared (CIR) aerial photography of seven Oregon estuaries was acquired at extreme low tides and digitally orthorectified with a ground pixel resolution of 25 cm to provide data for intertidal vegetation mapping. Exposed, semi-exposed and some submerged eelgrass meadows were clearly imaged. Three-band Soil-adjusted Vegetation Index (SAVI) derived image processing algorithms were applied to the orthoimagery. The images were further processed with unsupervised isoclassification into seven statistically distinct isocluster raster layers. Each isocluster layer was converted to a binary raster and edited using on-screen raster editing tools following traditional photo-interpretation methods using the original orthophotography as an overlay. Once edited the isocluster rasters were recombined to form the eelgrass classification. This method proved to be effective in distinguishing intertidal vegetation from non-vegetated areas with overall accuracy assessments by individual estuary ranging between 79 and 100 percent. This method combines vegetation classification in digital image processing, raster editing tools and photo-interpreter guidance to produce maps less spatially generalized than manual methods, and more accurately classified than automated digital processing methods. Remotely sensed data derived with this hybrid classification method have promising uses in areas where relatively high levels of data precision and accuracy are required, such as in estuarine ecological analyses and coastal resource management.

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