Abstract
Abstract. Landslide susceptibility (LS) assessment provides a relative estimate of landslide spatial occurrence based on local terrain conditions. A literature review revealed that LS evaluation has been performed in many study areas worldwide using different methods, model types, different partition of the territory (mapping units) and a large variety of geo-environmental data. Among the different methods, statistical models have been largely used to evaluate LS, but the minority of articles presents a complete and comprehensive LS assessment that includes model performance analysis, prediction skills evaluation, and estimation of the errors and uncertainty. The aim of this paper is to describe LAND-SE (LANDslide Susceptibility Evaluation) software that performs susceptibility modelling and zonation using statistical models, quantifies the model performances, and the associated uncertainty. The software is implemented in R, a free software environment for statistical computing and graphics. This provides users with the possibility to implement and improve the code with additional models, evaluation tools, or output types. The paper describes the software structure, explains input and output, and illustrates specific applications with maps and graphs. The LAND-SE script is delivered with a basic user guide and three example data sets.
Highlights
Landslide susceptibility (LS) is the likelihood of a landslide occurring in an area based on local terrain conditions (Brabb, 1984)
The aim of this paper is to describe LAND-SE (LANDslide Susceptibility Evaluation) software that performs susceptibility modelling and zonation using statistical models, quantifies the model performances, and the associated uncertainty
Adopting a temporal subdivision approach, the training and the validation set are composed by the same mapping units and the analysis is performed using the same explanatory variables but different grouping variable
Summary
Landslide susceptibility (LS) is the likelihood of a landslide occurring in an area based on local terrain conditions (Brabb, 1984). A recent revision of papers on statistical models (Malamud et al, 2014), have shown that more than 95 different model types were proposed in the literature. On account of the large variety of applications of statistical approaches, but the scarcity of model evaluation and quantification of the errors, we have implemented LAND-SE (LANDslide Susceptibility Evaluation), a software developed to prepare landslide susceptibility models and zonation at basin and regional scale, with specific functions focused on results evaluation and uncertainty estimation. Reichenbach: LAND-SE ware environment for statistical computing and graphics (R Core Team, 2015) This provides users with the possibility to implement and improve the code with additional models, evaluation tools, or output types. The paper describes LAND-SE structure, explains input and output, illustrates them with maps and graphs, some applications, and provides a basic user guide. The paper is completed by a Supplement containing the software code, a user guide and example data sets
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