scholarly journals Modeling and Classification of Alluvial Fans with DEMs and Machine Learning Methods: A Case Study of Slovenian Torrential Fans

2021 ◽  
Vol 13 (9) ◽  
pp. 1711
Author(s):  
Matej Babič ◽  
Dušan Petrovič ◽  
Jošt Sodnik ◽  
Božo Soldo ◽  
Marko Komac ◽  
...  
Keyword(s):  
Machine Learning ◽  
Debris Flow ◽  
Human Life ◽  
Alluvial Fans ◽  
Digital Elevation ◽  
Elevation Model ◽  
Flow Activity ◽  
Geomorphometric Parameters

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.

scholarly journals Numerical Modelling Based on Digital Elevation Model (DEM) Analysis of Debris Flow at Rinjani Volcano, West Nusa Tenggara, Indonesia

2021 ◽  
Vol 7 (3) ◽  
pp. 279
Author(s):  
Muhammad Fatih Qodri ◽  
Noviardi Noviardi ◽  
Al Hussein Flowers Rizqi ◽  
Lindung Zalbuin Mase
Keyword(s):  
Debris Flow ◽  
Digital Elevation Model ◽  
High Speed ◽  
Human Life ◽  
Mass Movement ◽  
High Viscosity ◽  
Particle Flows ◽  
Digital Elevation ◽  
Dem Analysis ◽  
Elevation Model

Debris flow is a disaster occurring in cases where a sediment particle flows at high speed, down to the slope, and usually with high viscosity and speed. This disaster is very destructive and human life-threatening, especially in mountainous areas. As one of the world’s active volcanoes in the world, Rinjani had the capacity to produce over 3 million m3 volume material in the 2015 eruption alone. Therefore, this study proposes a numerical model analysis to predict the debris flow release area (erosion) and deposition, as well as the discharge, flow height, and velocity. The Digital Elevation Model (DEM) was analyzed in ArcGIS, to acquire the Cartesian coordinates and “hillshade” form. This was also used as a method to produce vulnerable areas in the Jangkok watershed. Meanwhile, the Rapid Mass Movement Simulation (RAMSS) numerical modeling was simulated using certain parameters including volume, friction, and density, derived from the DEM analysis results and assumptions from similar historical events considered as the best-fit rheology. In this study, the release volume was varied at 1,000,000 m3, 2,000,000 m3, and 3,000,000 m3, while the simulation results show movement, erosion, and debris flow deposition in Jangkok watershed. This study is bound to be very useful in mitigating debris flow as disaster anticipation and is also expected to increase community awareness, as well as provide a reference for structural requirements, as a debris flow prevention.

scholarly journals Conformity of the NASADEM_HGT and ALOS AW3D30 DEM with the Altitude from the Brazilian Geodetic Reference Stations: A Case Study from Brazilian Cerrado

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2935
Author(s):  
Giovana Maranhão Bettiol ◽  
Manuel Eduardo Ferreira ◽  
Luiz Pacheco Motta ◽  
Édipo Henrique Cremon ◽  
Edson Eyji Sano
Keyword(s):  
Decision Makers ◽  
Surface Model ◽  
Brazilian Cerrado ◽  
Digital Elevation ◽  
Class B ◽  
Crucial Information ◽  
Error Standard Deviation ◽  
Elevation Model ◽  
Main Region

The Brazilian Cerrado (tropical savanna) is the second largest biome in South America and the main region in the country for agricultural production. Altitude is crucial information for decision-makers and planners since it is directly related to temperature that conditions, for example, the climatic risk of rainfed crop plantations. This study analyzes the conformity of two freely available digital elevation models (DEMs), the NASADEM Merged Digital Elevation Model Global 1 arc second (NASADEM_HGT) version 1 and the Advanced Land Observing Satellite Global Digital Surface Model (ALOS AW3D30), version 3.1, with the altitudes provided by 1695 reference stations of the Brazilian Geodetic System. Both models were evaluated based on the parameters recommended in the Brazilian Cartographic Accuracy Standard for Digital Cartographic Products (PEC-PCD), which defines error tolerances according to eight different scales (from 1:1000 to 1:250,000) and classes A (most strict tolerance, for example, 0.17 m for 1:1000 scale), B, C, and D (least strict tolerance, for example, 50 m for 1:250,000 scale). Considering the class A, the NASADEM_HGT meets 1:250,000 and lower scales, while AW3D30 meets 1:100,000 and lower scales; for class B, NASADEM_HGT meets 1:100,000 scale and AW3D30 meets 1:50,000. AW3D30 presented lower values of root mean square error, standard deviation, and bias, indicating that it presents higher accuracy in relation to the NASADEM_HGT. Within eight of Cerrado’s municipalities with the highest grain production, the differences between average altitudes, measured by the Cohen’s effect size, were statistically insignificant. The results obtained by the PEC-PCD for the Cerrado biome indicate that both models can be employed in different DEM-dependent applications over this biome.

scholarly journals Risk management on an alluvial fan: a case study of the 2008 debris-flow event at Villar Pellice (Piedmont, N-W Italy)

2010 ◽  
Vol 10 (5) ◽  
pp. 999-1008 ◽  
Author(s):  
M. Arattano ◽  
R. Conte ◽  
L. Franzi ◽  
D. Giordan ◽  
A. Lazzari ◽  
...  
Keyword(s):  
Debris Flow ◽  
Human Life ◽  
Alluvial Fan ◽  
Civil Protection ◽  
Emergency Situations ◽  
New Guidelines ◽  
Personal Accounts ◽  
Regional Authorities ◽  
North Western

Abstract. In the Piedmont Region (North-Western Italy), the regional authorities manage debris flow risk by following the ideal sequence of steps that are generally pursued in land planning and civil protection activities. Complex procedures and methods are elaborated and widely discussed with politicians, economists and the general public. On the contrary, in emergency situations, civil protection agencies generally prefer the adoption of simple and flexible criteria. In this paper, a catastrophic debris flow event, that occurred in 2008 in Villar Pellice, is described in this perspective, after an analysis of the triggering rainfalls and of the effects on human life and properties. The availability of a series of personal accounts coming from people who witnessed the occurrences before, during and after the event has allowed us to analyse, in detail, the dynamics of the event. Thanks to these accounts, it has been possible to propose new guidelines for the planning of the emergency activities in areas that are potentially prone to similar impulsive phenomena.

scholarly journals Environmental classification of administrative units of the Ukrainian Carpathians

2014 ◽  
pp. 245-253
Author(s):  
Ivan Kruhlov
Keyword(s):  
Cluster Analysis ◽  
Standard Deviation ◽  
Satellite Images ◽  
Environmental Classification ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data ◽  
Administrative Units ◽  
Elevation Model

Boundaries of 43 administrative units (raions and oblast towns) were digitized and manually rectified using official schemes and satellite images. SRTM digital elevation data were used to calculate mean relative elevation and its standard deviation for each unit, as well as to delineate altitudinal bioclimatic belts and their portions within the units. These parameters were used to classify the units via agglomerative cluster analysis into nine environmental classes. Key words: cluster analysis, digital elevation model, geoecosystem, geo-spatial analysis.

scholarly journals Environmental monitoring of soil pollution in urban areas (a case study from Heraklion city, Central Crete, Greece)

2017 ◽  
Vol 47 (2) ◽  
pp. 963
Author(s):  
E. Kokinou ◽  
C. Belonaki ◽  
D. Sakadakis ◽  
K. Sakadaki
Keyword(s):  
Magnetic Susceptibility ◽  
Urban Areas ◽  
Magnetic Measurements ◽  
Topographic Map ◽  
Near Surface ◽  
Thermomagnetic Analysis ◽  
Geological Features ◽  
Digital Elevation ◽  
Elevation Model

Main scope of the present study is to combine topographic and geological data, magnetic susceptibility and thermomagnetic analysis in order to investigate the magnetic properties of the near surface soils in possible polluted urban areas. For this purpose, a power plant with a dense traffic net around it, located in the NW section of Heraklion city in Crete was selected to be the study area. Surface soil samples have been collected from the area under investigation and they were analyzed in order to estimate the spatial distribution of the magnetic susceptibility. Loci of high values of the magnetic susceptibility within the study area gave rise to further proceed to thermomagnetic analysis of the selected samples. GIS techniques were used for mapping the magnetic measurements on the various topographic and geological features of the area. The digital elevation model was created by the digitization of the topographic map contours (1:5000 scale maps). The combination of the above techniques indicate high values of the magnetic susceptibility especially in the northeastern part of the investigated area, possibly related to pollution due to the presence of heavy metals.

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