Keywords:
Geographic information systems.
;
Electronic books.
Description / Table of Contents:
Mass movements of terrain, including cliff collapses and landslides, can be disastrous. This volume shows how the latest developments in geoinformation technology, including data modeling and remote sensing, can help to predict movement in advance.
Type of Medium:
Online Resource
Pages:
1 online resource (403 pages)
Edition:
1st ed.
ISBN:
9783642254956
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=972306
DDC:
551.307
Language:
English
Note:
Intro -- Terrigenous MassMovements -- Preface -- Contents -- 1 An Automated Approach for Detection of Shallow Landslides from LiDAR Derived DEM Using Geomorphological Indicators in a Tropical Forest -- Abstract -- 1.1…Introduction -- 1.2…Study Area -- 1.3…Geomorphological Features and Landslides -- 1.4…The Parameter: Slope Curvature -- 1.5…Data Used -- 1.6…LiDAR Processing Steps -- 1.6.1 Potential Landslide Zone Classification -- 1.6.2 Surface Roughness Index -- 1.6.3 Vegetation Index -- 1.6.4 Breaklines -- 1.6.5 Landslide Probability Index -- 1.6.6 Implementation -- 1.7…Results and Discussion -- 1.8…Conclusions and Perspective -- Acknowledgments -- References -- 2 Landslide Susceptibility Mapping Using a Spatial Multi Criteria Evaluation Model at Haraz Watershed, Iran -- Abstract -- 2.1…Introduction -- 2.2…Study Area -- 2.3…Methodology -- 2.4…Construction of Spatial Database -- 2.4.1 Landslide Inventory Map -- 2.4.2 Slope -- 2.4.3 Aspect -- 2.4.4 Altitude -- 2.4.5 Plan Curvature -- 2.4.6 Lithology -- 2.4.7 Land Use -- 2.4.8 Distance from Rivers -- 2.4.9 Distance from Roads -- 2.4.10 Distance from Faults -- 2.4.11 Topographic Wetness Index (TWI) -- 2.4.12 Stream Power Index (SPI) -- 2.4.13 Stream Transport Index (STI) -- 2.5…Landslide Susceptibility Mapping -- 2.6…Validation of the Landslide Susceptibility Map -- 2.7…Concluding Remarks -- References -- 3 Soft Computing Modeling in Landslide Susceptibility Assessment -- Abstract -- 3.1…Introduction -- 3.2…General Concepts -- 3.2.1 Landslide Susceptibility -- 3.2.2 Landslide Hazard -- 3.2.3 Landslide Risk -- 3.3…Fuzzy Modeling and Relations -- 3.3.1 Basic Fuzzy Concepts -- 3.3.2 Fuzzy Relations -- 3.3.3 Fuzzy Inference Systems -- 3.3.3.1 Mamdani Fuzzy Model -- 3.3.3.2 Sugeno Fuzzy Model -- 3.3.3.3 Tsukamoto Fuzzy Model -- 3.3.4 Landslide Susceptibility Applications of Fuzzy Approach.
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3.4…Artificial Neural Networks (ANN) -- 3.4.1 Understanding Biological Neural Networks and ANN Relation -- 3.4.2 Understanding ANN principles -- 3.4.3 Perceptron -- 3.4.4 ANN Types and Terminology -- 3.4.5 Back Propagation Neural Network (BPNN) -- 3.4.5.1 Feed Forward Processes of the BPNN -- 3.4.5.2 Calculation of error -- 3.4.5.3 Back Propagation Processes of the BPNN -- 3.4.6 Constructing an ANN -- 3.4.7 Use of Artificial Neural Networks in Susceptibility Assessments -- 3.5…Further Recommendations -- References -- 4 Application and Verification of Fractal Approach to Landslide Susceptibility Mapping -- Abstract -- 4.1…Introduction -- 4.2…Study Area -- 4.3…Description of Methodology -- 4.4…Application and Validation of Fractal Statistics to Landslide Susceptibility Mapping -- 4.4.1 Landslide Susceptibility Mapping -- 4.4.2 Verification of the Landslide Susceptibility Maps -- 4.5…Discussion -- 4.6…Conclusions -- Acknowledgments -- References -- 5 Preliminary Slope Mass Movement Susceptibility Mapping Using DEM and LiDAR DEM -- Abstract -- 5.1…Introduction -- 5.2…Problem Identification/Conceptual Background -- 5.3…Review of Literature -- 5.4…Study Area/Experimental Site -- 5.4.1 Vaud County -- 5.4.2 Bagnes Valley -- 5.5…Data and Tools -- 5.5.1 Data -- 5.5.2 Tools -- 5.5.2.1 HISTOFIT -- 5.5.2.2 CONEFALL -- 5.5.2.3 RAS -- 5.5.2.4 FLOW-R -- Source Area Identification -- Spreading Area Assessment -- Results -- 5.6…Methodology -- 5.6.1 Landslide Inventory and Susceptibility -- 5.6.1.1 Method -- 5.6.2 Shallow Landslides -- 5.6.2.1 Methodology -- 5.6.2.2 Application of the SINMAP Model -- 5.6.3 Debris Flows -- 5.6.3.1 Introduction -- 5.6.3.2 Source Areas Identification -- 5.6.3.3 Spreading Area Assessment -- 5.6.4 Rockfall -- 5.6.4.1 Identification of Potential Rockfall Source Areas -- 5.6.4.2 GDMU Interpretation.
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5.6.4.3 Assessment of the Maximum Runout Length -- 5.6.5 Snow Avalanches -- 5.6.5.1 Source Areas Identification -- 5.6.5.2 Propagation Zones Assessment -- RAS (Alpha--Beta Methodology) -- FLOW-R -- 5.6.5.3 Avalanche Susceptibility Mapping -- 5.6.6 Flooding and Erosion -- 5.6.6.1 GIS Analysis -- 5.6.6.2 Field Work -- 5.6.6.3 FLOW-R Modelling -- 5.6.6.4 Calculation of Maximum Discharge -- 5.6.6.5 Record of Alluvial Traces -- 5.6.6.6 Classes and Scenarios -- 5.7…Results -- 5.7.1 Landslide Inventory Map -- 5.7.1.1 County of Vaud -- 5.7.1.2 Valley of Bagnes -- 5.7.2 Susceptibility Map of Shallow Landslides -- 5.7.2.1 Vaud County -- 5.7.2.2 Bagnes Valley -- 5.7.3 Debris Flows -- 5.7.3.1 Vaud County -- Source Areas Identification -- Spreading Area Assessment -- 5.7.3.2 Bagnes Valley -- Source Areas Detection -- Propagation Area Assessment -- Detection and Propagation: Example of the Merdenson -- 5.7.4 Rockfall Susceptibility Map -- 5.7.4.1 Vaud Territory -- 5.7.4.2 Bagnes Territory -- 5.7.5 Snow Avalanches -- 5.7.5.1 Bagnes Valley -- Source Ares Identification -- Spreading Area Assessment -- Detection and Spreading, Example of the Folorsi -- 5.7.6 Flooding -- 5.7.6.1 Bagnes Territory -- 5.8…Discussion -- 5.8.1 Landslide Inventory Maps and Shallow Landslides -- 5.8.2 Debris Flows -- 5.8.3 Rockfall -- 5.8.4 Snow Avalanches -- 5.8.5 Floods in Bagnes Territory -- 5.9…Conclusion -- 5.10…Summary/Futuristic Vision -- Acknowledgments -- References -- 6 Application of GIS and RS for Mapping Landslides at the Watershed Level -- Abstract -- 6.1…Introduction -- 6.2…Problem Identification/Conceptual Background -- 6.3…Review of Literature -- 6.4…Tools/Materials -- 6.5…Methodology -- 6.5.1 Pre-Processing -- 6.5.1.1 Object Height Model -- 6.5.1.2 Roughness -- 6.5.1.3 Slope -- 6.5.1.4 Greenness -- 6.5.2 Global Landslide Detection -- 6.5.3 Local Landslide Detection.
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6.5.3.1 Landslide Polygon Editing -- 6.5.3.2 Magic Wand -- 6.5.3.3 3D Painter or Eraser -- 6.6…Results -- 6.6.1 Landslide Detection and Editing -- 6.6.1.1 Global Landslides Detection -- 6.6.1.2 Local Landslides Detection -- 6.6.2 Error Analysis -- 6.7…Discussion -- 6.8…Conclusions -- Acknowledgments -- References -- 7 Ensemble-Based Landslide Susceptibility Maps in Jinbu Area, Korea -- Abstract -- 7.1…Introduction -- 7.2…Study Area -- 7.3…Ensemble Method for Integration -- 7.4…Spatial Database -- 7.5…Landslide Susceptibility Mapping Using Various Models -- 7.6…Ensemble-Based Landslide Susceptibility Mapping -- 7.7…Validation -- 7.8…Discussion and Conclusions -- Acknowledgments -- References -- 8 Geoinformatics and Mass Movements: A Study on Li-shan Landslide, Taiwan -- Abstract -- 8.1…Introduction -- 8.1.1 Li-Shan Landslide -- 8.2…Methodology -- 8.2.1 Basis and Improvements -- 8.2.2 Three-Dimensional Elevation Model -- 8.2.3 Stability Analysis -- 8.2.4 Probabilistic Risk Evaluation -- 8.3…Results and Discussion -- 8.4…Conclusions -- Acknowledgments -- References -- 9 Landslide Inventory, Hazard and Risk Assessment in India -- Abstract -- 9.1…Introduction -- 9.2…Study Areas -- 9.3…Landslide Inventory Mapping -- 9.3.1 Collecting Historical Landslide Information -- 9.3.2 Mapping Landslides from Multi-Temporal Images -- 9.3.3 Automatic Landslide Mapping from Satellite Images -- 9.4…Landslide Hazard Assessment Approaches -- 9.4.1 Direct Hazard Estimation Along Transportation Routes -- 9.4.2 Rock Failure Modeling Using Gis -- 9.4.3 Multivariate Statistical Analysis -- 9.4.4 Physical modeling of landslide initiation and runout -- 9.4.5 The Models -- 9.4.6 The Data -- 9.4.7 The Results -- 9.5…Risk Assessment -- 9.6…Conclusions -- References -- 10 Vision-Based Terrestrial Surface Monitoring -- Abstract -- 10.1…Introduction and Scope -- 10.2…Sensing Techniques.
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10.2.1 Sensors -- 10.2.1.1 Terrestrial Laser Scanner -- 10.2.1.2 Image-Based Tacheometers -- 10.2.2 Data Acquisition Strategies -- 10.2.2.1 Sensor Control -- 10.2.2.2 Sensor Orientation -- 10.2.2.3 Data Handling -- 10.2.3 Data Evaluation -- 10.2.3.1 Surface Reconstruction -- 10.2.3.2 Manual Data Exploitation by Visualization -- 10.2.3.3 Temporal Surface Comparison -- 10.2.3.4 Point Tracking -- 10.2.3.5 Deformation Monitoring -- 10.3…Monitoring Frameworks -- 10.3.1 Geoscanner -- 10.3.2 Site Monitor -- 10.3.3 i-MeaS -- 10.3.3.1 System Layout -- 10.3.3.2 System Verification -- 10.3.3.3 i-MeaS Prospects -- 10.4…Applications -- 10.4.1 Introduction -- 10.4.2 Permafrost -- 10.4.2.1 Hinteres Langtalkar Rock Glacier -- 10.4.3 Glaciers -- 10.4.3.1 Pasterze Glacier -- 10.4.3.2 Göszlignitzkees Glacier -- 10.4.4 Snow -- 10.4.4.1 Monitoring for Snow Avalanche Prediction -- 10.4.4.2 The St. Anton Campaign: Touristic Visualization of Arlberg Snow Cover -- 10.4.5 Disaster Monitoring Application Case Studies -- 10.4.5.1 Schwaz -- 10.4.5.2 Gries -- 10.4.6 Geo-Risk Monitoring Case Studies and Systems -- 10.5…Conclusions and Prospects -- Acknowledgments -- References -- 11 LaSIRF: Landslide Safe Intelligent Route Finder for Mountainous Terrain in GIS Environment -- Abstract -- 11.1…Introduction -- 11.2…Methodology -- 11.2.1 Generation of Thematic Cost Map -- 11.2.2 Selection of Connected Neighbours -- 11.2.3 Computation of Neighbourhood Movement Cost (NM-cost) -- 11.2.4 Selection of Least-Cost Route -- 11.3…Description of the Software -- 11.4…Working Examples to Demonstrate Implementation of the Software -- 11.4.1 Efficiency of the Software -- 11.4.2 Working Examples -- 11.4.2.1 Working Example 1 -- 11.4.2.2 Working Example 2 -- 11.5…Summary and Conclusions -- References -- 12 Identification of Potentially Dangerous Glacial Lakes in the Northern Tian Shan -- Abstract.
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12.1…Introduction.
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