The location and distribution of wetlands and riparian zones influence the ecological functions present on a landscape. Accurate and easily reproducible land-cover maps enable monitoring of land-management decisions and ultimately a greater understanding of landscape ecology. Multi-season Landsat ETM+ imagery from 2001 combined with ancillary topographic and soils data were used to map wetland and riparian systems in the Gallatin Valley of Southwest Montana, USA. Classification Tree Analysis (CTA) and Stochastic Gradient Boosting (SGB) decision-tree-based classification algorithms were used to distinguish wetlands and riparian areas from the rest of the landscape. CTA creates a single classification tree using a one-step-look-ahead procedure to reduce variance. SGB uses classification errors to refine tree development and incorporates multiple tree results into a single best classification. The SGB classification (86.0% overall accuracy) was more effective than CTA (73.1% overall accuracy) at detecting a variety of wetlands and riparian zones present on this landscape.
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