Land subsidence susceptibility mapping based on InSAR and a hybrid machine learning approach

Land subsidence susceptibility mapping based on InSAR and a hybrid machine learning approach

Land subsidence (LS) due to natural processes or human activity can irreparably damage the environment. This study employed the quasi-permanent scatterer method to detect areas with and without subsidence in the period from 2018 to 2020. In addition, 12 factors affecting subsidence were selected to...

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Bibliographic Details
Main Authors: Ali Asghar Alesheikh, Zahra Chatrsimab, Fatemeh Rezaie, Saro Lee, Ali Jafari, Mahdi Panahi
Format: Article
Language:English
Published: Elsevier 2024-06-01
Series:Egyptian Journal of Remote Sensing and Space Sciences
Subjects:
Quasi-permanent scatterer
Land subsidence
Adaptive-network-based fuzzy inference system
Tehran-Karaj-Shahriyar aquifer
Particle swarm optimization
Remote sensing
Online Access:http://www.sciencedirect.com/science/article/pii/S1110982324000243

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http://www.sciencedirect.com/science/article/pii/S1110982324000243

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