Abstract
ABSTRACT In landslide susceptibility modeling, the selection of the mapping units is a very relevant topic both in terms of geomorphological adequacy and suitability of the models and final maps. In this paper, a test to integrate pixels and slope units is presented. MARS (Multivariate Adaptive Regression Splines) modeling was applied to assess landslide susceptibility based on a 12 predictors and a 1608 cases database. A pixel-based model was prepared and the scores zoned into 10 different types of slope units, obtained by differently combining two half-basin (HB) and four landform classification (LCL) coverages. The predictive performance of the 10 models were then compared to select the best performing one, whose prediction image was finally modified to consider also the propagation stage. The results attest integrating HB with LCL as more performing than using simple HB classification, with a very limited loss in predictive performance with respect to the pixel-based model.
Highlights
A pixel-based model was prepared and the scores zoned into 10 different types of slope units, obtained by differently combining two half-basin (HB) and four landform classification (LCL) coverages
Mapping units (MUs), which are defined as the portion of terrain where the geo-environmental conditions differ from the adjacent units across distinct boundaries (Carrara et al, 1995; Guzzetti et al, 2006, 1999; Hansen, 1984; van Westen et al, 1997), are essential both in predicting performance and output results, playing a very important role to determine the design of landslide susceptibility maps
The outcropping rocks mainly consists of carbonate, siliceous-carbonate and siliciclastic successions, which form tectonic units having imbricate geometric structures, as a consequence of the compressive phase that built up the Sicilian chain since the Oligocene (Morticelli et al, 2015)
Summary
Mapping units (MUs), which are defined as the portion of terrain where the geo-environmental conditions differ from the adjacent units across distinct boundaries (Carrara et al, 1995; Guzzetti et al, 2006, 1999; Hansen, 1984; van Westen et al, 1997), are essential both in predicting performance and output results, playing a very important role to determine the design of landslide susceptibility maps. Pixelbased final maps frequently result hard to read and not friendly for land use planners. These maps are often mosaics of cells (generally, with metric resolution), each having a specific susceptibility, without any constraint on the spatial coherence or connectivity between the adjacent pixels in a single slope. Thereby, the territorial planning becomes very complex and complicated causing even an unwillingness from administrators to exploit landslide susceptibility maps as an effective tool for risk analysis and management
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
