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 Fusion Analysis of Optical Satellite Images and Digital Elevation Model for Quantifying Volume in Debris Flow Disaster

2019 ◽  
Vol 11 (9) ◽  
pp. 1096 ◽  
Author(s):  
Hiroyuki Miura
Keyword(s):  
Debris Flow ◽  
Digital Elevation Model ◽  
Large Scale ◽  
Satellite Images ◽  
Erosion Depth ◽  
Digital Elevation ◽  
Elevation Model ◽  
Fusion Analysis ◽  
Optical Satellite Images ◽  
Debris Flow Disaster

Rapid identification of affected areas and volumes in a large-scale debris flow disaster is important for early-stage recovery and debris management planning. This study introduces a methodology for fusion analysis of optical satellite images and digital elevation model (DEM) for simplified quantification of volumes in a debris flow event. The LiDAR data, the pre- and post-event Sentinel-2 images and the pre-event DEM in Hiroshima, Japan affected by the debris flow disaster on July 2018 are analyzed in this study. Erosion depth by the debris flows is empirically modeled from the pre- and post-event LiDAR-derived DEMs. Erosion areas are detected from the change detection of the satellite images and the DEM-based debris flow propagation analysis by providing predefined sources. The volumes and their pattern are estimated from the detected erosion areas by multiplying the empirical erosion depth. The result of the volume estimations show good agreement with the LiDAR-derived volumes.

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 Sidik Cepat Potensi Karst Rocky Desertification (KRD) Menggunakan Citra Landsat 8 OLI: Studi di Kawasan Karst Gunungsewu Bagian Barat

2020 ◽  
Vol 34 (2) ◽  
pp. 150
Author(s):  
Pendi Tri Sutrisno ◽  
Sigit Heru Murti ◽  
Eko Haryono
Keyword(s):  
Digital Elevation Model ◽  
Karst Area ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Karst Rocky Desertification ◽  
Rocky Desertification ◽  
Digital Elevation ◽  
Dem Analysis ◽  
Elevation Model ◽  
Total Study Area

 Abstrak. Proses identifikasi kondisi lingkungan dapat dilakukan melalui adanya sidik cepat pemetaan Karst Rocky Desertification (KRD), termasuk di kawasan karst Gunungsewu bagian barat. Tujuan dari kajian ini adalah untuk mengetahui secara cepat potensi intensitas proses KRD yang terjadi di wilayah kajian, menggunakan metode analisis data citra penginderaan jauh multispektral. Metode yang digunakan adalah pengolahan citra secara digital menjadi citra indeks NDVI dan BI ditunjang dengan menggunakan analisis Digital Elevation Model (DEM) untuk menghasilkan data kemiringan lereng. Kriteria kelas potensi terjadinya KRD yang dihasilkan yaitu non KRD, potensi KRD rendah, potensi KRD sedang dan potensi KRD tinggi dengan luas total wilayah kajian 56.686,17 Ha. Wilayah kajian masih didominasi kelas non KRD dengan luas 32.140,56 Ha, sedangkan potensi KRD rendah seluas 24.447,72 Ha, kelas potensi KRD sedang seluas 96,53 Ha dan potensi KRD tinggi seluas 1,36 Ha. Abstract. Identification of environmental conditions can be done through the rapid mapping of karst rocky desertification (KRD) process. The purpose of this study is to know rapidly the potential of KRD processes, using Landsat 8 OLI multispectral image that covering the western part of Gunungsewu karst area. The method used is digital image processing of NDVI and BI index supported by using Digital Elevation Model (DEM) analysis to produce slope data. Criteria of KRD potential in this study are non KRD, low KRD potential, medium KRD potential and high KRD potential for total study area of 56.686,17 Ha. The study area dominated by non-KRD class with an area of 32.140,56 Ha, while the low KRD potential is 24.447,72 Ha, the medium KRD potential is 96,53 Ha and high KRD potential is 1,36 Ha.

scholarly journals Main features of geomorphology of the Sudetes re-assessed in the light of digital elevation model

Geografie ◽  
2008 ◽  
Vol 113 (4) ◽  
pp. 400-416
Author(s):  
Piotr Migoń
Keyword(s):  
Digital Elevation Model ◽  
Digital Elevation ◽  
Dem Analysis ◽  
Low Altitude ◽  
The Difference ◽  
Differential Uplift ◽  
Intramontane Basins ◽  
Elevation Model ◽  
The One ◽  
Planation Surfaces

The Sudetes as a geomorphological region are distinguished by complicated spatial pattern of high- and low-altitude terrains and variable mean slope gradients across the range. Several conceptual models have been proposed to account for this variability, emphasizing the significance of planation surfaces, intramontane basins, climate-controlled landform generations, or differential uplift and subsidence. An analysis of a digital elevation model and maps derived from the model have allowed for re-assessment of some of those hypotheses and concepts. It confirms that differential tectonics explains best the morphological layout of the Sudetes, but its effects are superimposed on a variety of rock - landform relationships. Neither the model emphasizing the occurrence of tiered levels of relict planation surfaces, nor one assuming the widespread existence of distinctive landforms of tropical morphogenesis find support in the light of region-wide DEM analysis. The general landform pattern of the western part of the Sudetes differs from the one in the eastern part, the difference being the abundance of intramontane basins in the former.

STUDY OF THE LANDSLIDE MORPHOLOGY BASED ON GNSS DATA AND AIRBORNE SOUNDING (ON THE EXAMPLE OF A SECTION OF THE PROTVA RIVER VALLEY)

2018 ◽  
Vol 12 (5-6) ◽  
pp. 50-57 ◽  
Author(s):  
I. S. Voskresensky ◽  
A. A. Suchilin ◽  
L. A. Ushakova ◽  
V. M. Shaforostov ◽  
A. L. Entin ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Geodetic Network ◽  
Aerial Survey ◽  
River Valley ◽  
Ease Of Use ◽  
Digital Elevation ◽  
Loose Deposits ◽  
Positioning Method ◽  
Landslide Body ◽  
Elevation Model

To use unmanned aerial vehicles (UAVs) for obtaining digital elevation models (DEM) and digital terrain models (DTM) is currently actively practiced in scientific and practical purposes. This technology has many advantages: efficiency, ease of use, and the possibility of application on relatively small area. This allows us to perform qualitative and quantitative studies of the progress of dangerous relief-forming processes and to assess their consequences quickly. In this paper, we describe the process of obtaining a digital elevation model (DEM) of the relief of the slope located on the bank of the Protva River (Satino training site of the Faculty of Geography, Lomonosov Moscow State University). To obtain the digital elevation model, we created a temporary geodetic network. The coordinates of the points were measured by the satellite positioning method using a highprecision mobile complex. The aerial survey was carried out using an unmanned aerial vehicle from a low altitude (about 40–45 m). The processing of survey materials was performed via automatic photogrammetry (Structure-from-Motion method), and the digital elevation model of the landslide surface on the Protva River valley section was created. Remote sensing was supplemented by studying archival materials of aerial photography, as well as field survey conducted immediately after the landslide. The total amount of research results made it possible to establish the causes and character of the landslide process on the study site. According to the geomorphological conditions of formation, the landslide refers to a variety of landslideslides, which are formed when water is saturated with loose deposits. The landslide body was formed with the "collapse" of the blocks of turf and deluvial loams and their "destruction" as they shifted and accumulated at the foot of the slope.

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