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Change detection of wetland ecosystems using Landsat imagery and change vector analysis

Accurate, efficient, and repeatable mapping of changes in wetlands and riparian areas (referred to collectively as wetlands) is critical for monitoring human, climatic, and other effects on these important systems. We used Landsat-based satellite imagery from 1988 and 2001 to map changes in wetland ecosystems in the Gallatin Valley of southwest Montana. Stochastic gradient boosting (SGB) was used to classify the 2001 image, and change vector analysis (CVA) was used to identify locations where wetland areas might have changed between 1988 and 2001. These potentially changed locations again were classified for the 1988 Landsat image using SGB. Areas of change constituted 3.4% of the study area, thus only this small percentage of the image was reclassified for the 1988 image. Overall change detection accuracy was 76%, although changes along the periphery of wetland boundaries and in areas of smaller upland inclusions were not distinguished as well as other changes. Overall accuracies of the SGB wetland classification maps were 81% for 1988 and 86% for 2001. CVA significantly reduced the number of pixels involved in the historical image classification compared to conducting independent classifications, thus reducing the potential for compounding classification errors in unchanged areas.