Analysis of Ground Subsidence Evolution Characteristics and Attribution Along the Beijing–Xiong’an Intercity Railway with Time-Series InSAR and Explainable Machine-Learning Technique

The long-term overextraction of groundwater in the Beijing–Tianjin–Hebei region has led to the formation of the world’s largest groundwater depression cone and the most extensive land subsidence zone, posing a potential threat to the operational safety of high-speed railways in the region. As a crit...

Volledige beschrijving

Bibliografische gegevens

Hoofdauteurs:	Xin Liu, Huili Gong, Chaofan Zhou, Beibei Chen, Yanmin Su, Jiajun Zhu, Wei Lu
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2025-02-01
Reeks:	Land
Onderwerpen:	PS-InSAR explainable machine learning land subsidence evolution characteristics attribution analysis
Online toegang:	https://www.mdpi.com/2073-445X/14/2/364
Tags:	Voeg label toe Geen labels, Wees de eerste die dit record labelt!