Description |
1 online resource (464 p.) |
Contents |
Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Acknowledgments -- About the Author -- List of Acronyms -- Chapter 1: Introduction -- 1.1. Introduction -- 1.2. Natural Hazards and Risk -- 1.2.1. Classification of Hazards -- 1.2.2. Vulnerability and Risk -- 1.2.3. Remote Sensing and Natural Hazards -- 1.3. Remote Sensing Data -- 1.3.1. Imagery Data -- 1.3.1.1. VHR Imagery -- 1.3.1.2. Medium Resolution Optical Imagery -- 1.3.1.3. Radar Imagery -- 1.3.2. LiDAR -- 1.3.3. GPS -- 1.3.3.1. GPS Fundamentals -- 1.3.3.2. GPS Accuracy -- 1.3.4. DEM |
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1.3.5. Data Selection Considerations -- 1.4. Data Analytical Methods -- 1.4.1. Image Analysis Methods -- 1.4.1.1. Per-Pixel Image Classification -- 1.4.1.2. Object-Oriented Image Classification -- 1.4.2. Machine Learning Methods -- 1.4.2.1. Support Vector Machine -- 1.4.2.2. Random Forest -- 1.4.2.3. ANN -- 1.4.2.4. CART -- 1.4.2.5. NBT -- 1.4.2.6. Generalized Additive Model -- 1.4.3. Vegetation Indices -- 1.5. Accuracy Measures of Sensing -- 1.5.1. (Cross) Validation -- 1.5.2. Accuracy Measures -- 1.5.3. Prediction Accuracy Measures -- References -- Chapter 2: Earthquakes -- 2.1. Introduction |
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2.2. Assessment of Earthquake Damage -- 2.2.1. Grades of Building Damage -- 2.2.2. From Optical VHR Imagery -- 2.2.3. From SAR Imagery -- 2.2.3.1. SAR Backscattering and Building Damage -- 2.2.3.2. Medium-Resolution SAR -- 2.2.3.3. VHR SAR Imagery -- 2.2.4. From Integrated Images -- 2.3. Post-Event Displacements -- 2.4. Detection of Liquefaction -- 2.4.1. Indices-based Detection -- 2.4.2. From VHR Imagery -- 2.4.3. From Medium Resolution Imagery -- 2.4.4. From Radar Imagery -- 2.4.5. Lateral Spreading Distance -- References -- Chapter 3: Landslides -- 3.1. Introduction |
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3.2. Sensing of Landslides -- 3.2.1. Identification of Triggering Factors -- 3.2.2. Recognition and Identification -- 3.3. Landslide Mapping -- 3.3.1. Manual Mapping -- 3.3.2. Automatic Mapping -- 3.3.2.1. Per-Pixel Classification and Vegetation Indexing -- 3.3.2.2. Object-Oriented Image Analysis -- 3.3.2.3. Machine Learning-Based Mapping -- 3.3.3. A Comparison -- 3.4. Non-Imagery Sensing -- 3.4.1. Recognition of Landslides -- 3.4.2. Identification of Landslide Components -- 3.4.3. Detection of Landslide Deformation and Movement -- 3.4.4. Estimation of Debris Volume |
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3.4.5. Airborne or Terrestrial LiDAR? -- 3.5. Landslide Vulnerability and Hazard Zoning -- 3.6. Landslide Monitoring -- 3.6.1. Monitoring Methods -- 3.6.2. InSAR-Based Monitoring -- References -- Chapter 4: Land Degradation -- 4.1. Introduction -- 4.2. Mapping and Monitoring -- 4.2.1. Image Classification -- 4.2.2. Indicator Differencing and Thresholding -- 4.2.3. Decision-tree Analysis -- 4.2.4. Degradation Monitoring -- 4.3. Detection and Assessment -- 4.3.1. Post-classification Comparison -- 4.3.2. Complex Statistical Analysis -- 4.3.3. Assessment of Degradation Cause, Severity, and Risk |
Summary |
This book examines the remote sensing technology used to gather information on 12 types of natural hazards in the terrestrial sphere, biosphere, hydrosphere, and atmosphere. It clarifies how to yield spatial and quantitative data on a natural hazard, including its spatial distribution, severity, causes, and the likelihood of occurrence |
Notes |
Description based upon print version of record |
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4.4. Land Salinization |
Subject |
Natural disasters -- Remote sensing
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Hazard mitigation -- Remote sensing
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Natural disasters -- Remote sensing.
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Form |
Electronic book
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ISBN |
9781000856132 |
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1000856135 |
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