Identifying spatiotemporal pattern and trend prediction of land subsidence in Zhengzhou combining MT-InSAR, XGBoost and hydrogeological analysis
Abstract Zhengzhou city (China) experienced relatively significant land deformation following the July 20, 2021, extreme rainstorm (7·20 event). This study jointly utilised Multi-temporal synthetic aperture radar interferometry (MT-InSAR), eXtreme Gradient Boosting (XGBoost), and hydrogeological ana...
Saved in:
Main Authors: | Zheng Zhou, Jiyuan Hu, Jiayao Wang, Lijun Wang, Tianrong Qiao, Zhen Li, Shiyuan Cheng |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-025-87789-9 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Land Subsidence in the Yangtze River Delta, China Explored Using InSAR Technique From 2019 to 2021
by: Hongbo Jiang, et al.
Published: (2025-01-01) -
Mapping Susceptibility and Risk of Land Subsidence by Integrating InSAR and Hybrid Machine Learning Models: A Case Study in Xi'an, China
by: Chen Chen, et al.
Published: (2025-01-01) -
From InSAR‐Derived Subsidence to Relative Sea‐Level Rise—A Call for Rigor
by: P. S. J. Minderhoud, et al.
Published: (2025-01-01) -
On the (im)possible validation of hydrogeological models
by: Andréassian, Vazken
Published: (2022-09-01) -
Urban Land Subsidence Characteristics and Their Relationship with Locations Liable to Waterlogging Based on SBAS-InSAR
by: LIU Huanyu, et al.
Published: (2025-01-01)