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Optimal slope units partitioning in landslide susceptibility mapping

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  • Chiara Martinello
  • Chiara Cappadonia
  • Christian Conoscenti
  • Valerio Agnesi
  • Edoardo Rotigliano

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.

Suggested Citation

  • Chiara Martinello & Chiara Cappadonia & Christian Conoscenti & Valerio Agnesi & Edoardo Rotigliano, 2021. "Optimal slope units partitioning in landslide susceptibility mapping," Journal of Maps, Taylor & Francis Journals, vol. 17(3), pages 152-162, June.
    • Handle: RePEc:taf:tjomxx:v:17:y:2021:i:3:p:152-162
    DOI: 10.1080/17445647.2020.1805807
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    Cited by:

    1. Tingyu Zhang & Quan Fu & Chao Li & Fangfang Liu & Huanyuan Wang & Ling Han & Renata Pacheco Quevedo & Tianqing Chen & Na Lei, 2022. "Modeling landslide susceptibility using data mining techniques of kernel logistic regression, fuzzy unordered rule induction algorithm, SysFor and random forest," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 3327-3358, December.

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