Optimal slope units partitioning in landslide susceptibility mapping

Chiara Martinello, Chiara Cappadonia, Christian Conoscenti, Valerio Agnesi and Edoardo Rotigliano

Journal of Maps, 2021, vol. 17, issue 3, 152-162

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.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/17445647.2020.1805807 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjomxx:v:17:y:2021:i:3:p:152-162

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjom20

DOI: 10.1080/17445647.2020.1805807

Access Statistics for this article

Journal of Maps is currently edited by Dr Mike Smith, Dr Jeremy Porter and Dr Dick Berg

More articles in Journal of Maps from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().