This book is related to various applications of laser scanning in landslide assessment. Landslide detection approaches, susceptibility, hazard, vulnerability assessment and various modeling techniques are presented. Optimization of landslide conditioning parameters and use of heuristic, statistical, data mining approaches, their advantages and their relationship with landslide risk assessment are discussed in detail. The book contains scanning data in tropical forests; its indicators, assessment, modeling and implementation. Additionally, debris flow modeling and analysis including source of debris flow identification and rockfall hazard assessment are also presented.
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1 Laser Scanning Systems in Landslide Studies |
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3 | (20) |
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Part II Landslide Detection Techniques |
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2 A Supervised Object-Based Detection of Landslides and Man-Made Slopes Using Airborne Laser Scanning Data |
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23 | (28) |
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3 Optimized Rule Sets for Automatic Landslide Characteristic Detection in a Highly Vegetated Forests |
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51 | (18) |
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4 Integration of LiDAR and QuickBird Data for Automatic Landslide Detection Using Object-Based Analysis and Random Forests |
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69 | (16) |
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Part III Debris Flow Source Identification |
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5 Debris Flow Source Identification in Tropical Dense Forest Using Airborne Laser Scanning Data and Flow-R Model |
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85 | (30) |
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Part IV Landslide Susceptibility Modelling |
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6 Landslide Susceptibility Modeling: Optimization and Factor Effect Analysis |
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115 | (18) |
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7 Effects of the Spatial Resolution of Digital Elevation Models and Their Products on Landslide Susceptibility Mapping |
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133 | (18) |
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8 Spatial Prediction of Landslide-Prone Areas Through k-Nearest Neighbor Algorithm and Logistic Regression Model Using High Resolution Airborne Laser Scanning Data |
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151 | (16) |
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9 Spatial Prediction of Landslides Along Jalan Kota in Bandar Seri Begawan (Brunei) Using Airborne LiDAR Data and Support Vector Machine |
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167 | (12) |
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10 Ensemble Disagreement Active Learning for Spatial Prediction of Shallow Landslide |
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179 | (14) |
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11 Performance Evaluation and Sensitivity Analysis of Expert-Based, Statistical, Machine Learning, and Hybrid Models for Producing Landslide Susceptibility Maps |
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193 | (42) |
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Part V Landslide Vulnerability and Risk Modelling |
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12 Slope Vulnerability and Risk Assessment Using High-Resolution Airborne Laser Scanning Data |
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235 | (18) |
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13 Landslide Risk Assessment Using Multi-hazard Scenario Produced by Logistic Regression and LiDAR-Based DEM |
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253 | (26) |
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Part VI Debris Flow Modelling |
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14 Debris Flow Susceptibility Assessment Using Airborne Laser Scanning Data |
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279 | (20) |
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Part VII Rockfall Hazard Assessment |
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15 Rockfall Hazard Assessment: An Overview |
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299 | (24) |
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16 Application of LiDAR in Rockfall Hazard Assessment in Tropical Region |
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323 | |
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Prof. Dr. Biswajeet Pradhan (University Putra Malaysia, Malaysia) Dr. Pradhan received the B.Sc. degree with honors from Berhampur University (India), the M.Sc. degree from the Indian Institute of Technology (IIT) in Bombay (India), and the M.Tech. degree in Civil Engineering from the IIT in Kanpur (India) and Dresden University of Technology (Germany). He received the Ph.D. degree in GIS and Geomatics Engineering from the University Putra Malaysia. From 2008 to 2010 he was a recipient of the Alexander von Humboldt Research Fellowship from Germany. In 2011, he received his Habilitation in Remote Sensing from Dresden University of Technology (Germany). Since March 2015, he is serving as the Humboldt Ambassador Scientist for the Alexander Von Humboldt Foundation (Germany). Dr. Pradhan is also the recipient of the prestigious German Academic Exchange Research (DAAD) Fellowship Award, Saxony State Fellowship from 1999 to 2002, Keith Atherton Research Award, and Georg Forster Research Award from German Government. He is currently Faculty Member of Dept. of Civil Engineering, University Putra Malaysia. He has more than sixteen years of teaching, research, consultancy and industrial experience. Out of his more than 350 articles, more than 245 have been published in science citation index (SCI/SCIE) technical journals. He has written two books in GIS data compression and disaster management and edited three volumes, and written 12 book chapters. He specializes in Remote Sensing, GIS application, and soft computing techniques in natural hazard and environmental problems. His published work has been widely cited by his peers with more than 4800 citations in SCOPUS database. His H-index is 41. He has completed 20 research projects. Dr. Pradhan is a member of many professional bodies such as Committee of Space Research (COSPAR), Senior Member of IEEE, United Nations Outer Space Research Programme (UNOOSA) and many more. He sits as board member of many national programs in Malaysia and South-East Asia. He is a regular reviewer for many international bodies alike Dutch Research Council, European Science Foundation, Austrian Science Foundation, Research Council UK (RCUK) and many more. He has been also active with teaching and supervising of many Ph.D., MSc. and undergraduate students. Dr. Pradhan has widely travelled abroad visiting more than 55 countries to present his research findings. Countries involved are Germany, USA, Netherlands, UK, Switzerland, Turkey, South Korea, Japan, Indonesia, Thailand and many more. In 2013 Dr. Pradhan joined the AJGS as an Associate Editor responsible for evaluating submissions in the fields of Environmental, Geo-Informatics and Geotechnical Sciences.
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