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Modeling and classification of alluvial fans with DEMs and machine learning methods : a case study of Slovenian torrential fans
ID Babič, Matej (Avtor), ID Petrovič, Dušan (Avtor), ID Sodnik, Jošt (Avtor), ID Soldo, Božidar (Avtor), ID Komac, Marko (Avtor), ID Chernieva, Olena (Avtor), ID Kovačič, Miha (Avtor), ID Mikoš, Matjaž (Avtor), ID Calì, Michele (Avtor)

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Izvleček
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.

Jezik:Angleški jezik
Ključne besede:digital elevation model, torrential fan surfaces, geomorphometric parameters, graph method, debris flows
Vrsta gradiva:Članek v reviji (dk_c)
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FGG - Fakulteta za gradbeništvo in geodezijo
Leto izida:2021
Status objave pri reviji:Objavljeno
Verzija članka:Založnikova različica članka
Št. strani:18 str.
Številčenje:Vol. 13, iss. 9, art. 1711
UDK:528.7:556(497.4)
ISSN pri članku:2072-4292
DOI:10.3390/rs13091711 Povezava se odpre v novem oknu
COBISS.SI-ID:61449731 Povezava se odpre v novem oknu
Datum objave v RUL:01.06.2021
Število ogledov:314
Število prenosov:88
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
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Gradivo je del revije

Naslov:Remote sensing
Skrajšan naslov:Remote sens.
Založnik:MDPI
ISSN:2072-4292
COBISS.SI-ID:32345133 Povezava se odpre v novem oknu

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:01.05.2021

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:digitalni model reliefa, DMR, daljinsko zaznavanje, hidrologija, struktura hudourniških vršajev, geomorfometrični parametri, metoda grafov, drobirski tokovi

Gradivo je financirano iz projekta

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Številka projekta:J7-8273
Naslov:Prepoznavanje potencialno nevarnih hudourniških vršajev z metodami geomorfometrije in simulacijami nastanka vršajev

Financer:Drugi - Drug financer ali več financerjev
Program financ.:International Programme on Landslides
Številka projekta:IPL-225

Financer:Drugi - Drug financer ali več financerjev
Program financ.:Università degli Studi di Catania
Številka projekta:308811
Akronim:NASCAR

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