M. Alvioli, A. C. Mondini, F. Fiorucci, M. Cardinali, I. Marchesini, 2018, Automatic landslide mapping from satellite imagery with a topography-driven thresholding algorithm, Geomorphometry 2018, pp. 1–4, Boulder CO, USA, 13/08/2018, 17/08/2018,
URL: http://www.cnr.it/prodotto/i/391537

We present an improvement of image classification by "thresholding", using topographic information to determine multiple thresholds. We devised a two-steps procedure for automatic classification into landslide or no landslide categories of a change-detection map obtained from satellite imagery. Requirements of the proposed procedure are knowledge of the occurrence of a landslide event, availability of a pre- and postevent pseudo-stereo image pair and a digital elevation model. The novel feature of the approach is represented by the use of slope units as topographic-aware subsets of the scene within which we apply a multiple thresholding method to classify a landslide class membership tuned on the sole landslide spectral response. The method is fully automatic after site-dependent operations, required only once, are performed, and exhibits improved classification performance with limited training requirements. Our automatic procedure is a step forward towards systematic acquisition of landslide events and real-time landslide mapping from satellite imagery.

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