Abstract.A coupled empirical approach to highlight relationships between rainfall, vegetation segmentation, and landslide occurrence is discussed. To reveal such links, two important rainfall events, which occurred over the Esino river basin in central Italy in November 2013 and May 2014, were analysed. The correlation between rainfall and landslides was evaluated by applying an intensity-duration (ID) threshold method, whereas the correlation between vegetation segmentation and landslides was investigated using morphological spatial pattern analysis (MSPA). This coupled approach represents an attempt to find both timing and location of landslide occurrence through an empirical (black box) analysis. Results showed: (i) the ID minimum threshold proposed in a previous study to be verified as an effective equation to assess the rainfall conditions likely to trigger landslides in the study area ("when"), and (ii) the core areas and the fragmented vegetation structures defined by the MSPA to be the most affected by slope failures ("where"). These encouraging findings prompt additional testing and the application of such a coupled empirical approach so that it is possible to achieve an integrated basis for landslide forecasting.
Abstract. A coupled empirical approach for studying possible correlations among rainfall, vegetation segmentation and landslide occurrence is discussed. To reveal such links two important rainfall events, occurred over the Esino river basin in central Italy, in November 2013 and May 2014, were analysed. The correlation between rainfall and landslides was carried out applying an intensity–duration (ID) threshold method, whereas the correlation between vegetation segmentation and landslides was investigated using the Morphological Spatial Pattern Analysis (MSPA). This coupled approach represents an attempt to find both timing and location of landslide occurrence through an empirical (black box) analysis. Results showed that: (i) the ID minimum threshold proposed in a previous study (Gioia et al., 2015) was verified as an effective equation to assess the rainfall conditions likely to trigger landslides in the study area ("when"), and (ii) the Core areas and the fragmented vegetation structures defined by the MSPA were the most affected by slope failures ("where"). These encouraging findings prompt for additional testing and application of such coupled empirical approach to possibly achieve an integrated basis for landslide forecasting.
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