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Natural Disasters, When Will They Reach Me?

  • Isuri Wijesundera
  • Malka N. Halgamuge
  • Thrishantha Nanayakkara
  • Thas Nirmalathas

Part of the Springer Natural Hazards book series (SPRINGERNAT)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Isuri Wijesundera, Malka N. Halgamuge, Thrishantha Nanayakkara, Thas Nirmalathas
    Pages 1-10
  3. Isuri Wijesundera, Malka N. Halgamuge, Thrishantha Nanayakkara, Thas Nirmalathas
    Pages 11-28
  4. Isuri Wijesundera, Malka N. Halgamuge, Thrishantha Nanayakkara, Thas Nirmalathas
    Pages 29-66
  5. Isuri Wijesundera, Malka N. Halgamuge, Thrishantha Nanayakkara, Thas Nirmalathas
    Pages 67-87
  6. Isuri Wijesundera, Malka N. Halgamuge, Thrishantha Nanayakkara, Thas Nirmalathas
    Pages 89-118
  7. Isuri Wijesundera, Malka N. Halgamuge, Thrishantha Nanayakkara, Thas Nirmalathas
    Pages 119-124
  8. Back Matter
    Pages 125-128

About this book

Introduction

The expected time of impact, also known as the mean first passage time (MFPT) to reach failure, is a critical metric in the management of natural disasters. The complexity of the dynamics governing natural disasters lead to stochastic behaviour. This book shows that state transitions of many such systems translate into random walks on their respective state spaces, biased and shaped by environmental inhomogeneity. Thus the probabilistic treatment of those random walks gives valuable insights of expected behaviour. A comprehensive case study of predicting cyclone induced flood is followed by a discussion of generic methods that predict MFPT addressing directional bias. This is followed by discussing MFPT prediction methods in systems showing network inhomogeneity. All presented methods are illustrated using real datasets of natural disasters. The book ends with a short discussion of possible future research areas introducing the problem of predicting MFPT for bush-fire propagation.

Keywords

Automated Dynamic Sensors Bush Fires/ Wild-land Fires Cyclone Induced Flood Propagation Environmental Factors Floods Forecast Impact Area Geographic Primitives (GP) Natural Disasters Prediction Efficiency Real Time Data Sensor Networks Geographic Primitives (GP) Network Primitives (NP)

Authors and affiliations

  • Isuri Wijesundera
    • 1
  • Malka N. Halgamuge
    • 2
  • Thrishantha Nanayakkara
    • 3
  • Thas Nirmalathas
    • 4
  1. 1.Melbourne School of EngineeringThe University of MelbourneMelbourneAustralia
  2. 2.Electrical and Electronic EngineeringThe University of MelbourneMelbourneAustralia
  3. 3.Department of InformaticsKing’s College LondonLondonUnited Kingdom
  4. 4.Electrical and Electronic EngineeringThe University of MelbourneMelbourneAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-10-1113-9
  • Copyright Information Springer Science+Business Media Singapore 2016
  • Publisher Name Springer, Singapore
  • eBook Packages Earth and Environmental Science
  • Print ISBN 978-981-10-1111-5
  • Online ISBN 978-981-10-1113-9
  • Series Print ISSN 2365-0656
  • Series Online ISSN 2365-0664
  • Buy this book on publisher's site