洪灾是世界上分布区域最广、破坏性最大的自然灾害之一，基于遥感技术监测洪灾面积、评估灾害损失的研究始于20世纪80年代后期。随着近30年的技术发展，洪灾遥感监测及灾后传染病预测领域的研究取得了一定的进展。本书系统介绍了洪水淹没区识别及洪灾引起的水源性传染病爆发风险监测方法。全书以2011年泰国大城地区洪灾为例，介绍了基于遥感技术的洪水淹没区识别方法和基于地理信息系统等空间信息技术的洪灾区水源性疾病监测预警系统，包括研究区和数据；基于植被指数、支持向量机和改进后的支持向量机的洪水淹没区识别方法；洪水遥感参数和水源性疾病的相关关系；水源性疾病爆发风险评估方法、基于后向传播神经网络的水源性疾病爆发风险监测及其专家系统的应用案例等。本书具有较强的实用性，可为该领域科研工作者提供参考，也可为灾害治理部门的科学决策提供支撑。 本书可供地学、遥感科学、传染病学和空间分析领域的科研人员和管理人员参考。

前辅文
Part I Flooding Identification Method
  1 Geographical Characteristics of the Study Area
   1.1 Characteristics of the Ayutthaya Province
   1.2 Thailand Major Flood Event of 2011
   1.3 Environmental Remote Sensing of Flooding Area
   1.4 Summary
   References
  2 Datasets and Data Preparation
   2.1 Remote Sensing Datasets and Preprocessing
   2.2 Flood Water Quality Data
   2.3 Morbidity Data
   2.4 Summary
   References
  3 Flooding Identification by Vegetation Index
   3.1 Flooding Identification from Multispectral Images
   3.2 Flooding Identification from SAR Images
   3.3 Multi-temporal Remote Sensing Data for Flooding Identification
   3.4 Summary
   References
  4 Flooding Identification by Support Vector Machine
   4.1 Support Vector Machine
   4.2 Affecting Parameters of the SVM Classifier
   4.3 Summary
   References
  5 Improved Support Vector Machine Classifier Through a Particle Filter Algorithm
   5.1 Linear Dynamics Systems
   5.2 Random Process and Stochastic Systems to Model State Estimation
   5.3 Particle Filter Algorithm
   5.4 A Support Vector Machine-Based Particle Filter (SVM-PF)
   5.5 A SVM-PF Applied in the Study Area
   5.6 Measured Results of the SVM-PF in Water Identification of Flooding Area
   5.7 An In-House Classifier for All Land Cover—CANFET
   5.8 Summary
   References
Part II Waterborne Diseases Caused by Flooding Disasters
  6 Flood-Related Parameters Affecting Waterborne Diseases
   6.1 Flood Parameters Derived from Multi-temporal Remote Sensing Data
   6.2 Population Variables
   6.3 Flood Water Quality
   6.4 Summary
   References
  7 Measure of Disease Risk
   7.1 Waterborne Diseases Caused by Flooding
   7.2 Disease Risk Assessment
   7.3 Outbreak Detection Methods
   7.4 Estimation of Outbreak Risk Using Risk Ratio Function
   7.5 Summary
   References
  8 Modeling Outbreak Risk Based on the Back Propagation Neural Network (BPNN) Algorithm
   8.1 Back Propagation Neural Network (BPNN)
   8.2 A Multilayer Feed-Forward Neural Network
   8.3 Back Propagation
   8.4 Modeling Outbreak Risk Based on BPNN
   8.5 Summary
   References
  9 Application of Surveillance of Communicable Disease Risk Using Expert Systems
   9.1 Introduction to the Expert System
   9.2 Integrated Expert System for Surveillance of Communicable Disease Risk
   9.3 Summary
   References
  10 Conclusions and Discussions
   10.1 Summary of Major Results
   10.2 Further Work
   References