Land Subsidence Susceptibility Mapping Using Interferometric Synthetic Aperture Radar (InSAR) and Machine Learning Models in a Semiarid Region of Iran

Land Subsidence Susceptibility Mapping Using Interferometric Synthetic Aperture Radar (InSAR) and Machine Learning Models in a Semiarid Region of Iran

Most published studies identify groundwater extraction as the leading cause of land subsidence (LS). However, the causes of LS are not only attributable to groundwater extraction. Other land-use practices can also affect the occurrence of LS. In this study, radar interferometric techniques and machi...

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Bibliographic Details
Main Authors: Hamidreza Gharechaee, Aliakbar Nazari Samani, Shahram Khalighi Sigaroodi, Abolfazl Baloochiyan, Maryam Sadat Moosavi, Jason A. Hubbart, Seyed Mohammad Moein Sadeghi
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Land
Subjects:
drylands
InSAR
machine learning
random forest
subsidence
susceptibility prediction
Online Access:https://www.mdpi.com/2073-445X/12/4/843

Internet

https://www.mdpi.com/2073-445X/12/4/843

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