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InSAR and deep learning in landslides researchintelligent identification, risk assessment and susceptibility mapping /

Record Type:	Electronic resources : Monograph/item
Title/Author:	InSAR and deep learning in landslides researchby Yi He.
Reminder of title:	intelligent identification, risk assessment and susceptibility mapping /
Author:	He, Yi.
Published:	Singapore :Springer Nature Singapore :2025.
Description:	xv, 214 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Landslide hazard analysisChina.
Online resource:	https://doi.org/10.1007/978-981-96-9132-6
ISBN:	9789819691326$q(electronic bk.)

InSAR and deep learning in landslides researchintelligent identification, risk assessment and susceptibility mapping /
He, Yi.

InSAR and deep learning in landslides researchintelligent identification, risk assessment and susceptibility mapping /[electronic resource] :by Yi He. - Singapore :Springer Nature Singapore :2025. - xv, 214 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9789819691326$q(electronic bk.)

Standard No.: 10.1007/978-981-96-9132-6doiSubjects--Topical Terms:

996493
Landslide hazard analysis
--China.

LC Class. No.: QE599.2

Dewey Class. No.: 551.307

InSAR and deep learning in landslides researchintelligent identification, risk assessment and susceptibility mapping /
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520 $a 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.
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