Modeling and classification of alluvial fans with DEMs and machine learning methods : a case study of Slovenian torrential fans

Babič, Matej (author), Petrovič, Dušan (author), Sodnik, Jošt (author), Soldo, Božidar (author), Komac, Marko (author), Chernieva, Olena (author), Kovačič, Miha (author), Mikoš, Matjaž (author), Calì, Michele (author)

Alluvial (torrential) fans, especially those created from debris-flow activity, often endanger built environments and human life. It is well known that these kinds of territories where human activities are favored are characterized by increasing instability and related hydrological risk; therefore, treating the problem of its assessment and management is becoming strongly relevant. The aim of this study was to analyze and model the geomorphological aspects and the physical processes of alluvial fans in relation to the environmental characteristics of the territory for classification and prediction purposes. The main geomorphometric parameters capable of describing complex properties, such as relative fan position depending on the neighborhood, which can affect their formation or shape, or properties delineating specific parts of fans, were identified and evaluated through digital elevation model (DEM) data. Five machine learning (ML) methods, including a hybrid Euler graph ML method, were compared to analyze the geomorphometric parameters and physical characteristics of alluvial fans. The results obtained in 14 case studies of Slovenian torrential fans, validated with data of the empirical model proposed by Bertrand et al. (2013), confirm the validity of the developed method and the possibility to identify alluvial fans that can be considered as debris-flow prone.

• Language: English
• Keywords: digital elevation model, torrential fan surfaces, geomorphometric parameters, graph method, debris flows
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FGG - Faculty of Civil and Geodetic Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2021
• Number of pages: 18 str.
• Numbering: Vol. 13, iss. 9, art. 1711
• PID: 20.500.12556/RUL-127268
• UDC: 528.7:556(497.4)
• ISSN on article: 2072-4292
• DOI: 10.3390/rs13091711
• COBISS.SI-ID: 61449731
• Publication date in RUL: 01.06.2021

Record is a part of a journal

• Title: Remote sensing
• Shortened title: Remote sens.
• Publisher: MDPI
• ISSN: 2072-4292
• COBISS.SI-ID: 32345133

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
• Licensing start date: 01.05.2021

Secondary language

• Language: Slovenian
• Keywords: digitalni model reliefa, DMR, daljinsko zaznavanje, hidrologija, struktura hudourniških vršajev, geomorfometrični parametri, metoda grafov, drobirski tokovi