Comparing the Performance of Different Landslide Susceptibility Models in ROC Space



This article addresses performance evaluation routine for comparison of results of several different landslide susceptibility models. The study area is located on the NW slopes of Fruška Gora Mountain (Serbia). Five modelling methods were considered: Stability Index, Analytical Hierarchy Process (AHP), Fuzzy sets, Conditional Probability, and Support Vector Machines (SVM). In this respective order they gave more accurate spatial prediction of landslides. The performance of their “probabilistic” prediction is estimated by Receiver Operating Characteristics (ROC). Evaluation in ROC space is discussed in both quantitative – Area Under Curve (AUC) value, and qualitative manner – ROC curve trends. Finally, the article summarizes the advantages of the proposed ROC-based performance comparison.


ROC curve AUC Landslide susceptibility 



This work was supported by the Czech Science Foundation (Grant No. 205/09/079).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department for GeoinformaticsPalacký UniversityOlomoucCzech Republic

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