Fuzzy c-mean classification (FCM), multi-layer perceptron neural network (MLP), fuzzy ARTMAP, and linear discriminant analysis (LDA) were used to classify Forest Inventory and Analysis (FIA) plots into six ecological habitats in the U.S. Northeast. Among the four classifiers, both FCM and MLP produced “soft” classifications based on fuzzy membership values. In contrast, fuzzy ARTMAP and LDA generated only “hard” classification...

Two artificial neural networks (ANN) and three traditional statistical classification methods are used to classify Forest Inventory and Analysis (FIA) plots into six ecological habitats in the U.S. Northeast. Four variables (overstory and understory species composition, hardwood basal area percentage, and current FIA forest type) are identified from a list of available stand variables as the most important discriminating varia...