BUS606: Operations and Supply Chain Management

The Area Under Curve (AUC) is an intuitive and comprehensive tool to evaluate the reliability and precision of the model outcomes. The AUC method has been broadly applied in several studies to evaluate the efficiency of susceptibility mapping. It starts with dividing the forest fire probability map into equal area categories and then ranking them from a minimum to a maximum value. Curve creation is implemented by plotting the cumulative percentage of forest fire susceptible areas on the 'x' axis and the cumulative percentage of forest fire events on the 'y' axis. Prediction and success rate are two outputs of the AUC method. The success and prediction curves determine the percentage of fire occurrence points in each probability category. The validation process was undertaken by comparing the existing forest fire inventory data with the model derived forest fire-prone areas maps. The AUC values range from 0.5 to 1.0 such that values closer to or equal to 0.5 indicate very poor fit or classification by chance, whereas those closer to or equal to 1 indicate perfect fit or perfect classification. The success rate outcome was attained using the forest fire training dataset (70% of the inventory forest fire points). The real proficiency of the model output can be tested using the prediction rate, which was implemented using the test dataset (30% of the inventory forest fire points). This is because the prediction capability of the model cannot be achieved using the training data. The prediction rate shows how well the model can predict the forest fire proneness or susceptibility of an area.