Abstract
Soil sealing is the destruction or covering of natural soils by totally or partially impermeable artificial material. ISPRA (Italian Institute for Environmental Protection Research) uses different remote sensing techniques to monitor this process and updates yearly a national-scale soil sealing map of Italy. In this work, for the first time, we tried to combine soil sealing indicators as additional parameters within a landslide susceptibility assessment. Four new parameters were derived from the raw soil sealing map: Soil sealing aggregation (percentage of sealed soil within each mapping unit), soil sealing (categorical variable expressing if a mapping unit is mainly natural or sealed), urbanization (categorical variable subdividing each unit into natural, semi-urbanized, or urbanized), and roads (expressing the road network disturbance). These parameters were integrated with a set of well-established explanatory variables in a random forest landslide susceptibility model and different configurations were tested: Without the proposed soil-sealing-derived variables, with all of them contemporarily, and with each of them separately. Results were compared in terms of AUC ((area under receiver operating characteristics curve, expressing the overall effectiveness of each configuration) and out-of-bag-error (estimating the relative importance of each variable). We found that the parameter “soil sealing aggregation” significantly enhanced the model performances. The results highlight the potential relevance of using soil sealing maps on landslide hazard assessment procedures.
Highlights
Landslide susceptibility mapping (LSM) is the representation of the spatial probability of landslide occurrence, based on the correlation between known landslide locations and the spatial arrangement of a set of predisposing factors [1,2]
The configuration that returned the best validation statistics is the one using the soil sealing aggregation (SSA) parameter, with an AUC of 0.74, showing that land consumption can be used as an important feature in landslide susceptibility mapping
Soil sealing maps at a 10-m spatial resolution covering the whole Italian territory are updated every year by ISPRA
Summary
Landslide susceptibility mapping (LSM) is the representation of the spatial probability of landslide occurrence, based on the correlation between known landslide locations and the spatial arrangement of a set of predisposing factors [1,2]. Several authors pointed out that geographic information systems (GISs) can be useful tools to prepare the input data and to run the LSM [23,24] and the challenge to increase the quality, accuracy, and areal coverage of many input data has led to wide use of remote sensing techniques [25,26,27,28]. In local-scale applications, high-resolution DEMs can be obtained using LiDAR (Light Detection And Ranging) [29]. Another series of remotely sensed products, which are widely used in LSM, are indicators of the vegetation cover (e.g., the NDVI – Normalized Difference Vegetation Index) [30,31] and land-use or land-cover thematic maps [22,32,33]
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