Evaluation of rainfall-induced large-scale landslide potential using Scoops3D

2020 ◽  
Author(s):  
Jie-Lun Chiang ◽  
Chia-Ming Kuo
Keyword(s):  
Digital Elevation Model ◽  
Groundwater Level ◽  
Large Scale ◽  
The United States ◽  
Equilibrium Analysis ◽  
Slope Aspect ◽  
Seismic Zone ◽  
Landslide Area ◽  
Digital Elevation ◽  
Elevation Model

<p>Taiwan is located in the Pacific volcanic seismic zone and frequently suffers from landslides and debris flow caused by typhoons. On average, there are four typhoons which may cause tremendous disasters such as massive landslides in Taiwan mainly from July to September every year. The aim of this study is to evaluate the development of large-scale landslide area under various cumulative rainfalls. The study area of this study is Liouquei, Kaohsiung in southern Taiwan. Firstly, the relationship of rainfall and groundwater level were built. The equation of change of groundwater level and rainfall is h=38.2R, R<sup>2</sup>=0.83. Then, 10m digital elevation model (10m-dem) was used to evaluate elevation, slope, aspect and etc. Finally, geology and 10m-dem were used to build Scoops3D model of Liouquei area.</p><p>Scoops3D, which is released by the United States geological survey (USGS), evaluates slope stability throughout a digital landscape represented by a digital elevation model (DEM). The program uses a three-dimensional (3D) method of columns limit-equilibrium analysis to assess the stability of many potential landslides (typically millions) within a user-defined size range. We simulated the potential landslide area under a cumulative rainfall in 24 hours from 800mm~1600mm. The results show that landslide area contributed 65%~76% of the entire potential large-scale landslide area.</p>

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.

A new method for supporting interpretation of paleochannels in a large scale — Detrended Digital Elevation Model Interpretation

Geomorphology ◽  
2020 ◽  
Vol 369 ◽  
pp. 107374
Author(s):  
Shuyan Zhang ◽  
Yong Ma ◽  
Fu Chen ◽  
Jianbo Liu ◽  
Fulong Chen ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Large Scale ◽  
New Method ◽  
Model Interpretation ◽  
Digital Elevation ◽  
Elevation Model

A new deterministic method for groundwater mapping using a digital elevation model

2013 ◽  
Vol 13 (4) ◽  
pp. 1146-1153 ◽  
Author(s):  
Tamás Ács ◽  
Zoltán Simonffy
Keyword(s):  
Digital Elevation Model ◽  
Groundwater Level ◽  
Ground Surface ◽  
Terrestrial Ecosystems ◽  
Groundwater Depth ◽  
Deterministic Method ◽  
Groundwater Levels ◽  
Geostatistical Methods ◽  
Digital Elevation ◽  
Elevation Model

Accurate knowledge of groundwater levels and flow conditions in the vicinity of groundwater-dependent terrestrial ecosystems (GWDTE-s) is required for identifying groundwater dependency and comparing the present situation with the optimal one, as part of the status assessment of groundwaters according to the EU Water Framework Directive. Geostatistical methods (like kriging or cokriging) may result in an unrealistic groundwater level map if only a few measured data are available. In this paper a new, grid-based, deterministic method (GSGW-model) is introduced. The aim of the model is to calculate groundwater depth within the required accuracy from sparse data of monitoring wells. The basic principle of the GSGW-model is that the groundwater table is a smoothed replica of the ground surface. Hence, changes in the groundwater level between two grid points are calculated as a function of the digital elevation model (DEM) and soil properties. The GSGW-model was tested in the Nyírség region (Hungary). Results were compared with those gained by ordinary kriging and cokriging. It has been concluded that kriging overestimates the groundwater level in the low part of the test area, where wetlands are located, while the maps produced by the GSGW-model are a better fit of the real variability, providing more reliable estimates of groundwater depth in GWDTE-s as well.

Food Submergence Calculation and Analysis Using Digital Elevation Model and Geographical Information System

2014 ◽  
Vol 571-572 ◽  
pp. 792-795
Author(s):  
Xiao Qing Zhang ◽  
Kun Hua Wu
Keyword(s):  
Information System ◽  
Digital Elevation Model ◽  
Flood Control ◽  
Large Scale ◽  
Geographical Information ◽  
Economic Losses ◽  
Model Data ◽  
Digital Elevation ◽  
Elevation Model ◽  
Digital Elevation Model Data

Floods usually cause large-scale loss of human life and wide spread damage to properties. Determining flood zone is the core of flood damage assessment and flood control decision. The aim of this paper is to delineate the flood inundation area and estimate economic losses arising from flood using the digital elevation model data and geographic information system techniques. Flood extent estimation showed that digital elevation model data is very precious to model inundation, however, in order to be spatially explicit flood model, high resolution DEM is necessary. Finally, Analyses for the submergence area calculation accuracy.

Evaluation of NDWI and MNDWI for assessment of waterlogging by integrating digital elevation model and groundwater level

2014 ◽  
Vol 30 (6) ◽  
pp. 650-661 ◽  
Author(s):  
Kanwar Vivek Singh ◽  
Raj Setia ◽  
Shashikanta Sahoo ◽  
Avinash Prasad ◽  
Brijendra Pateriya
Keyword(s):  
Digital Elevation Model ◽  
Groundwater Level ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals Fire on the Water Towers: Mapping Burn Scars on Mount Kenya Using Satellite Data to Reconstruct Recent Fire History

2019 ◽  
Vol 11 (2) ◽  
pp. 104
Author(s):  
Mary C. Henry ◽  
John K. Maingi ◽  
Jessica McCarty
Keyword(s):  
Digital Elevation Model ◽  
Fire History ◽  
Slope Aspect ◽  
Burned Area ◽  
Semiarid Region ◽  
Landsat 8 ◽  
Hydroelectric Power ◽  
Active Fire ◽  
Digital Elevation ◽  
Elevation Model

Mount Kenya is one of Kenya’s ‘water towers’, the headwaters for the country’s major rivers including the Tana River and Ewaso Nyiro River, which provide water and hydroelectric power to the semiarid region. Fires affect water downstream, but are difficult to monitor given limited resources of local land management agencies. Satellite-based remote sensing has the potential to provide long term coverage of large remote areas on Mount Kenya, especially using the free Landsat data archive and moderate resolution imaging spectroradiometer (MODIS) fire products. In this study, we mapped burn scars on Mount Kenya using 30 m Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) derived dNBR (change in normalized burn ratio) and MODIS active fire detection and burned area data for fires occurring from 2004 to 2015. We also analyzed topographic position (elevation, slope, aspect) of these fires using an ASTER global digital elevation model (GDEM v2) satellite-derived 30 m digital elevation model (DEM). Results indicate that dNBR images calculated from data acquired about one year apart were able to identify large fires on Mount Kenya that match locations (and timing) of MODIS active fire points and burned areas from the same time period, but we were unable to detect smaller and/or older fires.

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