scholarly journals r.randomwalk v1.0, a multi-functional conceptual tool for mass movement routing

2015 ◽  
Vol 8 (9) ◽  
pp. 8193-8237 ◽  
Author(s):  
M. Mergili ◽  
J. Krenn ◽  
H.-J. Chu
Keyword(s):  
Programming Languages ◽  
Mass Movement ◽  
Rock Avalanche ◽  
R Software ◽  
Impact Indicator ◽  
Conceptual Tool ◽  
Outburst Floods ◽  
Digital Elevation ◽  
Elevation Model ◽  
Indicator Score

Abstract. We introduce r.randomwalk, a flexible and multi-functional open source tool for backward- and forward-analyses of mass movement propagation. r.randomwalk builds on GRASS GIS, the R software for statistical computing and the programming languages Python and C. Using constrained random walks, mass points are routed from defined release pixels of one to many mass movements through a digital elevation model until a defined break criterion is reached. Compared to existing tools, the major innovative features of r.randomwalk are: (i) multiple break criteria can be combined to compute an impact indicator score, (ii) the uncertainties of break criteria can be included by performing multiple parallel computations with randomized parameter settings, resulting in an impact indicator index in the range 0–1, (iii) built-in functions for validation and visualization of the results are provided, (iv) observed landslides can be back-analyzed to derive the density distribution of the observed angles of reach. This distribution can be employed to compute impact probabilities for each pixel. Further, impact indicator scores and probabilities can be combined with release indicator scores or probabilities, and with exposure indicator scores. We demonstrate the key functionalities of r.randomwalk (i) for a single event, the Acheron Rock Avalanche in New Zealand, (ii) for landslides in a 61.5 km2 study area in the Kao Ping Watershed, Taiwan; and (iii) for lake outburst floods in a 2106 km2 area in the Gunt Valley, Tajikistan.

scholarly journals r.randomwalk v1, a multi-functional conceptual tool for mass movement routing

2015 ◽  
Vol 8 (12) ◽  
pp. 4027-4043 ◽  
Author(s):  
M. Mergili ◽  
J. Krenn ◽  
H.-J. Chu
Keyword(s):  
Programming Languages ◽  
Mass Movement ◽  
Rock Avalanche ◽  
R Software ◽  
Impact Indicator ◽  
Conceptual Tool ◽  
Outburst Floods ◽  
Digital Elevation ◽  
Elevation Model ◽  
Indicator Score

Abstract. We introduce r.randomwalk, a flexible and multi-functional open-source tool for backward and forward analyses of mass movement propagation. r.randomwalk builds on GRASS GIS (Geographic Resources Analysis Support System – Geographic Information System), the R software for statistical computing and the programming languages Python and C. Using constrained random walks, mass points are routed from defined release pixels of one to many mass movements through a digital elevation model until a defined break criterion is reached. Compared to existing tools, the major innovative features of r.randomwalk are (i) multiple break criteria can be combined to compute an impact indicator score; (ii) the uncertainties of break criteria can be included by performing multiple parallel computations with randomized parameter sets, resulting in an impact indicator index in the range 0–1; (iii) built-in functions for validation and visualization of the results are provided; (iv) observed landslides can be back analysed to derive the density distribution of the observed angles of reach. This distribution can be employed to compute impact probabilities for each pixel. Further, impact indicator scores and probabilities can be combined with release indicator scores or probabilities, and with exposure indicator scores. We demonstrate the key functionalities of r.randomwalk for (i) a single event, the Acheron rock avalanche in New Zealand; (ii) landslides in a 61.5 km2 study area in the Kao Ping Watershed, Taiwan; and (iii) lake outburst floods in a 2106 km2 area in the Gunt Valley, Tajikistan.

scholarly journals Status of Major Glaciers of Hunza River Basin, Under Changing Climatic Conditions of Pakistan Over the Period of (1990-2018)

2021 ◽  
Author(s):  
Sajid Ali ◽  
Garee Khan ◽  
Wajid Hassan ◽  
Javed Akhter Qureshi ◽  
Iram Bano
Keyword(s):  
River Basin ◽  
Primary Source ◽  
Climatic Conditions ◽  
Climate Data ◽  
Outburst Floods ◽  
Glacial Lake Outburst Floods ◽  
Digital Elevation ◽  
Remote Sensing Techniques ◽  
Elevation Model ◽  
Hunza River

Abstract Ice masses and snow of Hunza River Basin (HRB) are an important primary source of fresh water and lifeline for downstream inhabitants. Changing climatic conditions seriously put an impact on these available ice and snow masses. These glaciers may affect downstream population by glacial lake outburst floods (GLOF) and surge events due to climatic variation. So, monitoring of these glaciers and available ice masses are important. This research delivers an approach for selected glaciers of the Hunza river basin. An attempt is made in this study using Landsat (OLI, ETM, ETM+, TM), digital elevation model (DEM), Geographic Information System and Remote Sensing techniques (RS&GIS) techniques. We delineated 27 glaciers within HRB from the period of 1990-2018. These glaciers' total area is about 2589.75 ±86km 2 in 1990 and about 2565.12 ±68km 2 in 2018. Our results revealed that from 2009 to 2015, glacier coverage of HRB advanced with a mean annual advance rate of 2.22±0.1 km 2 a -1 . Conversely, from 1994 to 1999, the strongest reduction in glacier area with a mean rate of - 3.126±0.3km 2 a -1 is recorded. The glaciers of HRB are relatively stable compared to Hindukush, Himalayan and Tibetan Plateau (TP) region of the world. The steep slope glacier's retreat rate is more than that of gentle slope glaciers, and the glaciers below elevation of 5000 m above sea level change significantly. Based on climate data from 1995-2018, HRB shows a decreasing trend in temperature and increasing precipitation. The glacier area's overall retreat is due to an increase in summer temperature while the glacier advancement is induced possibly by winter and autumn precipitation.

25 years of movement monitoring on South Peak, Turtle Mountain: understanding the hazard

2009 ◽  
Vol 46 (3) ◽  
pp. 256-269 ◽  
Author(s):  
Corey R. Froese ◽  
Francisco Moreno ◽  
Michel Jaboyedoff ◽  
David M. Cruden
Keyword(s):  
Monitoring Program ◽  
Rock Avalanche ◽  
Light Detection And Ranging ◽  
Short Term ◽  
The Past ◽  
Digital Elevation ◽  
Government Project ◽  
Elevation Model ◽  
Movement Monitoring ◽  
Deep Fractures

In 1981, an Alberta Government project upgraded the monitoring of South Peak, Turtle Mountain, on the south margin of the 1903 Frank Slide. The monitoring program aimed at understanding the rates of deformation over large, deep fractures encompassing South Peak and predicting a second large rock avalanche on the mountain. The monitoring program consisted of a complement of static ground points and remotely monitored targets measured periodically, and climatic, microseismic, and deformation data collected automatically on daily intervals and archived. In the late 1980s, developmental funding for the monitoring program ceased and some of the installations fell into disrepair. Between May 2004 and September 2006, readings from the remaining functional monitoring points were compiled and interpreted. In addition, readings compiled previously were re-interpreted based on a more recent understanding of short-term movement patterns and climatic influences. These observations were compared with recent observations from an airborne light detection and ranging (LiDAR) digital elevation model and field photographs to give more precise estimates of the overall rates, extent, and patterns of motion for the past 25 years.

scholarly journals A Semiautomatic Pixel-Object Method for Detecting Landslides Using Multitemporal ALOS-2 Intensity Images

2020 ◽  
Vol 12 (3) ◽  
pp. 561 ◽  
Author(s):  
Bruno Adriano ◽  
Naoto Yokoya ◽  
Hiroyuki Miura ◽  
Masashi Matsuoka ◽  
Shunichi Koshimura
Keyword(s):  
Disaster Response ◽  
Large Scale ◽  
Reference Data ◽  
Mass Movement ◽  
Recovery Planning ◽  
Additional Information ◽  
Digital Elevation ◽  
Before And After ◽  
Intensity Images ◽  
Elevation Model

The rapid and accurate mapping of large-scale landslides and other mass movement disasters is crucial for prompt disaster response efforts and immediate recovery planning. As such, remote sensing information, especially from synthetic aperture radar (SAR) sensors, has significant advantages over cloud-covered optical imagery and conventional field survey campaigns. In this work, we introduced an integrated pixel-object image analysis framework for landslide recognition using SAR data. The robustness of our proposed methodology was demonstrated by mapping two different source-induced landslide events, namely, the debris flows following the torrential rainfall that fell over Hiroshima, Japan, in early July 2018 and the coseismic landslide that followed the 2018 Mw6.7 Hokkaido earthquake. For both events, only a pair of SAR images acquired before and after each disaster by the Advanced Land Observing Satellite-2 (ALOS-2) was used. Additional information, such as digital elevation model (DEM) and land cover information, was employed only to constrain the damage detected in the affected areas. We verified the accuracy of our method by comparing it with the available reference data. The detection results showed an acceptable correlation with the reference data in terms of the locations of damage. Numerical evaluations indicated that our methodology could detect landslides with an accuracy exceeding 80%. In addition, the kappa coefficients for the Hiroshima and Hokkaido events were 0.30 and 0.47, respectively.

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 The 1513 Monte Crenone rock avalanche: numerical model and geomorphological analysis

2022 ◽  
Vol 77 (1) ◽  
pp. 21-37
Author(s):  
Alessandro De Pedrini ◽  
Christian Ambrosi ◽  
Cristian Scapozza
Keyword(s):  
Numerical Modelling ◽  
Rock Avalanche ◽  
Historical Reconstruction ◽  
Field Mapping ◽  
Digital Elevation ◽  
Lake Formation ◽  
Detachment Zone ◽  
Elevation Model ◽  
Geomorphological Analysis

Abstract. As a contribution to the knowledge of historical rockslides, this research focuses on the historical reconstruction, field mapping, and simulation of the expansion, through numerical modelling, of the 30 September 1513 Monte Crenone rock avalanche. Earth observation in 2-D and 3-D, as well as direct in situ field mapping, allowed the detachment zone and the perimeter and volume of the accumulation to be determined. Thanks to the reconstruction of the post-event digital elevation model based on historical topographic maps and the numerical modelling with the RAMMS::DEBRISFLOW software, the dynamics and runout of the rock avalanche were calibrated and reconstructed. The reconstruction of the runout model allowed confirmation of the historical data concerning this event, particularly the damming of the valley floor and the lake formation up to an elevation of 390 m a.s.l., which generated an enormous flood by dam breaching on 20 May 1515, known as the “Buzza di Biasca”.

scholarly journals UAV-Derived Himalayan Topography: Hazard Assessments and Comparison with Global DEM Products

Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 18 ◽  
Author(s):  
C. Watson ◽  
Jeffrey Kargel ◽  
Babulal Tiruwa
Keyword(s):  
Mass Movement ◽  
High Mountain ◽  
Lake Area ◽  
Digital Elevation ◽  
2015 Gorkha Earthquake ◽  
Order Of Magnitude ◽  
Hazard Assessments ◽  
Elevation Model ◽  
Terrain Elevation ◽  
Fine Resolution

Topography derived using human-portable unmanned aerial vehicles (UAVs) and structure from motion photogrammetry offers an order of magnitude improvement in spatial resolution and uncertainty over small survey extents, compared to global digital elevation model (DEM) products, which are often the only available choice of DEMs in the high-mountain Himalaya. Access to fine-resolution topography in the high mountain Himalaya is essential to assess where flood and landslide events present a risk to populations and infrastructure. In this study, we compare the topography of UAV-derived DEMs, three open-access global DEM products, and the 8 m High Mountain Asia (HMA) DEMs (released in December 2017) and assess their suitability for landslide- and flood-related hazard assessments. We observed close similarity between UAV and HMA DEMs when comparing terrain elevation, river channel delineation, landside volume, and landslide-dammed lake area and volume. We demonstrate the use of fine-resolution topography in a flood-modelling scenario relating to landslide-dammed lakes that formed on the Marsyangdi River following the 2015 Gorkha earthquake. We outline a workflow for using UAVs in hazard assessments and disaster situations to generate fine-resolution topography and facilitate real-time decision-making capabilities, such as assessing landslide-dammed lakes, mass movement volumes, and flood risk.

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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