6533b856fe1ef96bd12b267a
RESEARCH PRODUCT
Optimal slope units partitioning in landslide susceptibility mapping
Chiara MartinelloEdoardo RotiglianoChiara CappadoniaChristian ConoscentiValerio Agnesisubject
G3180-9980010504 meteorology & atmospheric sciencesGeography Planning and DevelopmentLand managementland managementimera settentrionale river basin (sicily)Mars Exploration ProgramLandslide susceptibility010502 geochemistry & geophysics01 natural sciencesmapping unitsImera Settentrionale river basin (Sicily) land management Landslide susceptibility mapping units MARSMapsEarth and Planetary Sciences (miscellaneous)landslide susceptibilitymarsCartographyGeologySelection (genetic algorithm)0105 earth and related environmental sciencesdescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-01-01 |