Access the full text.
Sign up today, get DeepDyve free for 14 days.
N. Quadros, P. Collier, C. Fraser (2008)
INTEGRATION OF BATHYMETRIC AND TOPOGRAPHIC LIDAR : A PRELIMINARY INVESTIGATION
D. Hooper, M. Bursik, F. Webb (2003)
Application of high-resolution, interferometric DEMs to geomorphic studies of fault scarps, Fish Lake Valley, Nevada–California, USARemote Sensing of Environment, 84
Hye-In Kim, Gi-Sug Yu, Kwan-Dong Park, J. Ha (2008)
Accuracy Evaluation of VRS RTK Surveys Inside the GPS CORS Network Operated by National Geographic Information InstituteJournal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 26
A Yalcin, S Reis, AC Aydinoglu (2011)
A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistic regression methods for landslide susceptibility mapping in Trabzon, NE TurkeyCatena, 85
Joseph Gartner, S. Cannon, P. Santi, V. deWolfe (2008)
Empirical models to predict the volumes of debris flows generated by recently burned basins in the western U.S.Geomorphology, 96
Guoyun Zhou, T. Esaki, Y. Mitani, M. Xie, J. Mori (2003)
Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approachEngineering Geology, 68
C. Yune, Yun-Ki Chae, J. Paik, Gi-Hong Kim, Seungwhan Lee, H. Seo (2013)
Debris flow in metropolitan area — 2011 Seoul debris flowJournal of Mountain Science, 10
F. Ackermann (1999)
Airborne laser scanning : present status and future expectationsIsprs Journal of Photogrammetry and Remote Sensing, 54
J. Bull, H. Miller, D. Gravley, D. Costello, D. Hikuroa, J. Dix (2010)
Assessing debris flows using LIDAR differencing: 18 May 2005 Matata event, New ZealandGeomorphology, 124
G. Crosta, S. Cucchiaro, P. Frattini (2003)
Validation of semi-empirical relationships for the definition of debris-flow behavior in granular materials
M. Cavalli, P. Tarolli, L. Marchi, G. Fontana (2008)
The effectiveness of airborne LiDAR data in the recognition of channel-bed morphologyCatena, 73
A. Carrara, F. Guzzetti, M. Cardinali, P. Reichenbach (1999)
Use of GIS Technology in the Prediction and Monitoring of Landslide HazardNatural Hazards, 20
G. Ohlmacher, John Davis (2003)
Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USAEngineering Geology, 69
Juana Montané, R. Torres (2006)
Accuracy Assessment of Lidar Saltmarsh Topographic Data Using RTK GPSPhotogrammetric Engineering and Remote Sensing, 72
GB Crosta, S Cucchiaro, P Frattini (2003)
Proceedings of 3rd International Conference on Debris Flows Hazards Mitigation: Mechanics, Prediction and Assessment, Millpress, Rotterdam
S. Lee, G. Kim, C. Yune, H. Ryu (2013)
Development of landslide-risk assessment model for mountainous regions in eastern KoreaDisaster Advances, 6
J. McKean, J. Roering (2004)
Objective landslide detection and surface morphology mapping using high-resolution airborne laser altimetryGeomorphology, 57
R. Iverson, S. Schilling, J. Vallance (1998)
OBJECTIVE DELINEATION OF LAHAR-INUNDATION HAZARD ZONESGeological Society of America Bulletin, 110
ND Quadros, PA Collier, CS Fraser (2008)
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 36, Beijing, China
D. Rickenmanna, D. Laiglec, B. McArdella, J. Hüblb (2006)
Comparison of 2 D debris-flow simulation models with field events
Jia-Chong Du, Hung-Chao Teng (2007)
3D laser scanning and GPS technology for landslide earthwork volume estimationAutomation in Construction, 16
J. Brasington, Joseph Langham, B. Rumsby (2003)
Methodological sensitivity of morphometric estimates of coarse fluvial sediment transportGeomorphology, 53
S. Miles, C. Ho (1999)
Rigorous landslide hazard zonation using Newmark's method and stochastic ground motion simulationSoil Dynamics and Earthquake Engineering, 18
(2010)
2010 abnormal climate special report
C. Scheidl, D. Rickenmann, M. Chiari (2008)
The use of airborne LiDAR data for the analysis of debris flow events in SwitzerlandNatural Hazards and Earth System Sciences, 8
(1998)
Objective delineation
(1999)
System SciencesProceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers, Track8
Xin Huang, Marcelo García (1998)
A Herschel–Bulkley model for mud flow down a slopeJournal of Fluid Mechanics, 374
Joong-hee Han, J. Kwon, Changki Hong (2010)
Analysis of Network-RTK(VRS) Positioning Accuracy for Surveying Public Control Point, 18
D. Rickenmann (1999)
Empirical Relationships for Debris FlowsNatural Hazards, 19
D. Rickenmann, D. Laigle, B. McArdell, J. Hübl (2006)
Comparison of 2D debris-flow simulation models with field eventsComputational Geosciences, 10
M. Berti, A. Simoni (2007)
Prediction of debris flow inundation areas using empirical mobility relationshipsGeomorphology, 90
B. Hunt (1994)
Newtonian Fluid Mechanics Treatment of Debris Flows and AvalanchesJournal of Hydraulic Engineering, 120
A. Nandi, A. Shakoor (2010)
A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analysesEngineering Geology, 110
D Naef, D Rickenmann, P Rutschmann (2006)
Comparison of flow resistance relations for debris flows using a one-dimensional finite element simulation modelNatural Hazards and Earth System Sciences, 6
K. Tsutsui, S. Rokugawa, H. Nakagawa, S. Miyazaki, Chin-Tung Cheng, T. Shiraishi, Shiun-Der Yang (2007)
Detection and Volume Estimation of Large-Scale Landslides Based on Elevation-Change Analysis Using DEMs Extracted From High-Resolution Satellite Stereo ImageryIEEE Transactions on Geoscience and Remote Sensing, 45
(2011)
Umyeon mountain landslide investigation and restoration countermeasure establishment report
J. Chandler (1999)
Effective application of automated digital photogrammetry for geomorphological research: Earth Surf
(2002)
5700/5800 GPS Receiver User Guide, Version1.0, Revision A
J. O'brien, P. Julien, W. Fullerton (1993)
Two‐Dimensional Water Flood and Mudflow SimulationJournal of Hydraulic Engineering, 119
A. Yalçın, Sally Reis, A. Aydinoglu, T. Yomralioglu (2011)
A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statisticsFuel and Energy Abstracts
L. Marchi, V. D’Agostino (2004)
Estimation of debris‐flow magnitude in the Eastern Italian AlpsEarth Surface Processes and Landforms, 29
J. Wheaton, J. Brasington, S. Darby, D. Sear (2009)
Accounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgetsEarth Surface Processes and Landforms, 35
Fuchu Dai, C. Lee, Jiyan Li, Zhen Xu (2001)
Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong KongEnvironmental Geology, 40
M. Jaboyedoff, T. Oppikofer, A. Abellán, M. Derron, A. Loye, R. Metzger, A. Pedrazzini (2012)
Use of LIDAR in landslide investigations: a reviewNatural Hazards, 61
M. Clark, D. Clark, D. Roberts (2004)
Small-footprint lidar estimation of sub-canopy elevation and tree height in a tropical rain forest landscapeRemote Sensing of Environment, 91
A. Refice, D. Capolongo (2002)
Probabilistic modeling of uncertainties in earthquake-induced landslide hazard assessmentComputers & Geosciences, 28
Michel JaboyedoffThierry (2012)
Use of LIDAR in landslide investigations: a review
Saro Lee (2007)
Comparison of landslide susceptibility maps generated through multiple logistic regression for three test areas in KoreaEarth Surface Processes and Landforms, 32
JP Griswold (2004)
Mobility statistics and hazard mapping for non-volcanic debris flows and rock avalanches
M. Bremer, O. Sass (2012)
Combining airborne and terrestrial laser scanning for quantifying erosion and deposition by a debris flow eventGeomorphology, 138
S. DeLong, C. Prentice, G. Hilley, Y. Ebert (2012)
Multitemporal ALSM change detection, sediment delivery, and process mapping at an active earthflowEarth Surface Processes and Landforms, 37
C. Conoscenti, C. Maggio, E. Rotigliano (2008)
GIS analysis to assess landslide susceptibility in a fluvial basin of NW Sicily (Italy)Geomorphology, 94
C. Wang, S. Li, T. Esaki (2008)
GIS-based two-dimensional numerical simulation of rainfall-induced debris flowNatural Hazards and Earth System Sciences, 8
Tamotsu Takahashi (2007)
What is debris flow
(1999)
Efective application of automated digital photogrammetry for geomorphological research
This paper describes a geographic information system (GIS)-based method for observing changes in topography caused by the initiation, transport, and deposition of debris flows using high-resolution light detection and ranging (LiDAR) digital elevation models (DEMs) obtained before and after the debris flow events. The paper also describes a method for estimating the volume of debris flows using the differences between the LiDAR DEMs. The relative and absolute positioning accuracies of the LiDAR DEMs were evaluated using a real-time precise global navigation satellite system (GNSS) positioning method. In addition, longitudinal and cross-sectional profiles of the study area were constructed to determine the topographic changes caused by the debris flows. The volume of the debris flows was estimated based on the difference between the LiDAR DEMs. The accuracies of the relative and absolute positioning of the two LiDAR DEMs were determined to be ±10 cm and ±11 cm RMSE, respectively, which demonstrates the efficiency of the method for determining topographic changes at an scale equivalent to that of field investigations. Based on the topographic changes, the volume of the debris flows in the study area was estimated to be 3747 m3, which is comparable with the volume estimated based on the data from field investigations.
Journal of Mountain Science – Springer Journals
Published: May 15, 2014
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.