Coseismic Landslides: Intelligent Prediction and Recognition
Focusing on Habitable Earth for sustainability, this book develops novel and sophisticated deep learning algorithms and explores their successful application in intelligent prediction and recognition of coseismic landslides. These algorithms have originality and unique advantages in relatively high accuracy, low false alarms, strong generalization, and good interpretability. They were successfully applied in a series of violent earthquakes occurring worldwide from 2008 to 2022. This book provides significant techniques to support the 72-hour “golden window” for survivors in emergency rescue and to instruct postseismic rational reconstruction and development in society and economy. With cutting-edge algorithms and international urgent disaster-mitigating demands, this book caters to geoscientists, environmentalists, engineering geologists, and hazard geologists. It also appeals graduate students in the above fields.

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Coseismic Landslides: Intelligent Prediction and Recognition
Focusing on Habitable Earth for sustainability, this book develops novel and sophisticated deep learning algorithms and explores their successful application in intelligent prediction and recognition of coseismic landslides. These algorithms have originality and unique advantages in relatively high accuracy, low false alarms, strong generalization, and good interpretability. They were successfully applied in a series of violent earthquakes occurring worldwide from 2008 to 2022. This book provides significant techniques to support the 72-hour “golden window” for survivors in emergency rescue and to instruct postseismic rational reconstruction and development in society and economy. With cutting-edge algorithms and international urgent disaster-mitigating demands, this book caters to geoscientists, environmentalists, engineering geologists, and hazard geologists. It also appeals graduate students in the above fields.

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Coseismic Landslides: Intelligent Prediction and Recognition

Coseismic Landslides: Intelligent Prediction and Recognition

Coseismic Landslides: Intelligent Prediction and Recognition

Coseismic Landslides: Intelligent Prediction and Recognition

Overview

Focusing on Habitable Earth for sustainability, this book develops novel and sophisticated deep learning algorithms and explores their successful application in intelligent prediction and recognition of coseismic landslides. These algorithms have originality and unique advantages in relatively high accuracy, low false alarms, strong generalization, and good interpretability. They were successfully applied in a series of violent earthquakes occurring worldwide from 2008 to 2022. This book provides significant techniques to support the 72-hour “golden window” for survivors in emergency rescue and to instruct postseismic rational reconstruction and development in society and economy. With cutting-edge algorithms and international urgent disaster-mitigating demands, this book caters to geoscientists, environmentalists, engineering geologists, and hazard geologists. It also appeals graduate students in the above fields.

Product Details

ISBN-13: 9789819512966
Publisher: Springer Nature Singapore
Publication date: 10/22/2025
Pages: 132
Product dimensions: 6.10(w) x 9.25(h) x (d)

About the Author

Xianmin Wang is a professor at China University of Geosciences (Wuhan). She achieved the honors or awards of “Hubei Province Industry Professor,” “3551 Optics Valley Talent,” “First Prize for Teaching Achievement of Higher Education in Hubei Province,” “Third Prize for Science and Technology Progress in Hubei Province,” “First Prize of Geographic Information Science and Technology Progress Award,” “Wangzhizhuo Innovation Talent Award,” and “Baogang Education Award.” She is mainly engaged in the research areas of geohazard monitoring and evaluating, intelligent interpretation of geological environment, and artificial intelligence and machine learning. Professor Xianmin Wang has published more than 90 academic papers, 2 monographs, and 1 monograph chapter. She serves as a member of the Chinese Association of Artificial Intelligence, an associate editor of Journal of Big data, and an editorial board member of Bulletin of Geological Science and Technology.

Lizhe Wang is a professor at China University of Geosciences (Wuhan). He is a member of Academia Europaea, IEEE fellow, SPIE fellow. His research interests include remote sensing data processing and applications.

Haixiang Guo is a professor at China University of Geosciences (CUG) (Wuhan) and also the vice-president of Science and Technology Development in CUG. He achieved the honors and awards of “Leading Talent for Science and Technology” by the Ministry of Natural Resources, “New Century Excellent Talent in University” by the Ministry of Education, “Second Prize for Science and Technology in Ministry of Land and Resources,” “First Prize for Development Research in Hubei Province,” “Second Prize for Excellent Achievement in Social Sciences in Hubei Province,” and “Third Prize for Science and Technology Progress in Hubei Province.” Professor Haixiang Guo focuses mainly on hazard chain risk assessment, complex system simulation and decision making, and artificial intelligence. He has published more than 110 academic papers and 5 monographs. Six papers were selected as ESI highly cited papers and 1 paper were selected as a ESI hot paper.

Xuewen Wang is a doctoral student at China University of Geosciences (CUG) (Wuhan) and has published 3 papers in the “International Journal of Digital Earth,” “International Journal of Applied Earth Observation and Geoinformation,” and so on. His research interest is landslide disaster and artificial intelligence.

Qiyuan Yang is a doctoral student at China University of Geosciences (CUG) (Wuhan) and has published 3 papers in the “Remote Sensing,” “Geoscience Frontiers,” and so on. His research interest is landslide disaster and emergency rescue.

Aomei Zhang is a master student at China University of Geosciences (CUG) (Wuhan) and has published 2 papers in the “Remote Sensing,” and “Soil Dynamics and Earthquake Engineering” journals. Her research interest is landslide disaster and artificial intelligence.

Table of Contents

Near real-time intelligent prediction and cause characteristics of coseismic landslides.- Intelligent identification of coseismic landslides across an extensive region.- Cross-earthquake-event intelligent recognition of coseismic landslides.

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