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Instituto Valenciano de Investigaciones Económicas

Publicaciones

A ROC analysis-based classification method for landslide susceptibility maps
Cantarino, I., M.Á. Carrión, F.J. Goerlich y V. Martínez
Fuente: Landslides: Journal of the International Consortium on Landslides
Resumen

A landslide susceptibility map is a crucial tool for land-use spatial planning and management in mountainous areas. An essential issue in such maps is the determination of susceptibility thresholds. To this end, the map is zoned into a limited number of classes. Adopting one classification system or another will not only affect the map’s readability and final appearance, but most importantly, it may affect the decision-making tasks required for effective land management. The present study compares and evaluates the reliability of some of the most commonly used classification methods, applied to a susceptibility map produced for the area of La Marina (Alicante, Spain). A new classification method based on ROC analysis is proposed, which extracts all the useful information from the initial dataset (terrain characteristics and landslide inventory) and includes, for the first time, the concept of misclassification costs. This process yields a more objective differentiation of susceptibility levels that relies less on the intrinsic structure of the terrain characteristics. The results reveal a considerable difference between the classification methods used to define the most susceptible zones (in over 20% of the surface) and highlight the need to establish a standard method for producing classified susceptibility maps. The method proposed in the study is particularly notable for its consistency, stability and homogeneity, and may mark the starting point for consensus on a generalisable classification method.

Cómo citar este artículo

Cantarino, Isidro, Miguel Á. Carrión, Francisco J. Goerlich y Víctor Martínez (2019). «A ROC analysis-based classification methodfor landslide susceptibility maps». Landslides: Journal of the International Consortium on Landslides 12, n.º 2 (febrero): 265-282.