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InSAR and Deep Learning in Landslides Research: Intelligent Identification, Risk Assessment and Susceptibility Mapping / by Yi He.
- Format:
- Book
- Author/Creator:
- He, Yi.
- Language:
- English
- Subjects (All):
- Natural disasters.
- Artificial intelligence.
- Geographic information systems.
- Geotechnical engineering.
- Natural Hazards.
- Artificial Intelligence.
- Geographical Information System.
- Geotechnical Engineering and Applied Earth Sciences.
- Local Subjects:
- Natural Hazards.
- Artificial Intelligence.
- Geographical Information System.
- Geotechnical Engineering and Applied Earth Sciences.
- Physical Description:
- 1 online resource (230 pages)
- Edition:
- 1st ed. 2025.
- Place of Publication:
- Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
- Summary:
- This book combines remote sensing and deep learning technology to develop a variety of models in the study of different type landslides in a wide range of areas including northwest, southwest and southern China. It explores the application of various deep learning methods in landslide identification and sensitivity mapping. It also explores intelligent landslide monitoring and susceptibility mapping using a variety of data and methods, providing ideas and methods for landslide prevention and mitigation. This book is suitable for professionals in the field of landslide monitoring and graduate students in the fields of remote sensing and geological hazards research to mitigate this most widespread and harmful geological hazards in the world.
- Contents:
- Introduction
- InSAR and deep learning theory
- Deep learning landslide intelligent identification methods
- Landslide susceptibility assessment based on geography consistency constraints
- Landslide susceptibility assessment by integrated multi-model based on static-dynamic data
- Landslide susceptibility assessment based on integrated static-dynamic characteristics of InSAR deformation information.
- ISBN:
- 981-9691-32-X
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