A Deep Neural Network Framework for Landslide Susceptibility Mapping by Considering Time-Series Rainfall

A Deep Neural Network Framework for Landslide Susceptibility Mapping by Considering Time-Series Rainfall

Landslide susceptibility mapping (LSM) is of great significance in geohazard early warning and prevention. The existing LSM methods mostly used traditional static landslide conditioning factors (LCFs), which only considered the spatial features of single-pixel neighborhoods and could not extract the...

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Bibliographic Details
Main Authors: Binghai Gao, Yi He, Xueye Chen, Hesheng Chen, Wang Yang, Lifeng Zhang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep learning (DL)
dynamic factors
interferometry synthetic aperture radar (InSAR)
landslide susceptibility
Online Access:https://ieeexplore.ieee.org/document/10449365/

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