A multi-scale geomorphometric landform system was created through the use of fuzzy semantic import models and fuzzy overlay to measure distribution of landforms within parcels of the Conservation Reserve Program in Northeast Kansas, United States. The uncertainty and stability of landform classes was measured by calculating the area proportions covered by these classes at varying levels of classification entropy across different scales. Within each scale, the landform classes backslopes and flats had the highest proportional representation of all classes at most entropy levels (defined by values greater or equal than 0.95, 0.90, 0.85, and 0.75, respectively). At the highest entropy level (0.99) the class proportions were more variable. This is important as both backslopes and flats showed dominant proportions of total area at different scales (backslopes at finer scales, and flats at coarser scales) within CRP Parcels. The presented model allows an improved implementation of landform models by incorporating an uncertainty assessment and sensitivity analysis for a variation of spatial scales.
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