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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
)
PDF - Predstavitvena datoteka,
prenos
(5,06 MB)
MD5: 1A1FD588FC62D17C51BCE61B44BF5806
URL - Izvorni URL, za dostop obiščite
https://www.mdpi.com/2072-4292/13/9/1711
Galerija slik
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
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FGG - Fakulteta za gradbeništvo in geodezijo
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Leto izida:
2021
Št. strani:
18 str.
Številčenje:
Vol. 13, iss. 9, art. 1711
PID:
20.500.12556/RUL-127268
UDK:
528.7:556(497.4)
ISSN pri članku:
2072-4292
DOI:
10.3390/rs13091711
COBISS.SI-ID:
61449731
Datum objave v RUL:
01.06.2021
Število ogledov:
1087
Število prenosov:
164
Metapodatki:
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Objavi na:
Gradivo je del revije
Naslov:
Remote sensing
Skrajšan naslov:
Remote sens.
Založnik:
MDPI
ISSN:
2072-4292
COBISS.SI-ID:
32345133
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
Projekti
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
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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