3D coseismic deformation and slip distribution inversion of the 2024 Noto <italic style="font-style: italic">M</italic><sub>w</sub> 7.5 earthquake

ZHAO Jinqi; HOU Chengbin; NIU Yufen; WANG Shuai; ZHOU Zhengpei; FAN Qianyou; WANG Zixuan

doi:10.11834/jrs.20265345

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3D coseismic deformation and slip distribution inversion of the 2024 Noto M_w 7.5 earthquake
Vol. 30, Issue 4, Pages: 1150-1165(2026)
Received：11 September 2025，

Published：07 April 2026
DOI： 10.11834/jrs.20265345
稿件说明：

移动端阅览

赵金奇，侯承斌，牛玉芬，王帅，周正培，樊茜佑，王子旋.2026.2024年能登M_w7.5级地震三维同震形变场获取及其滑动分布反演.遥感学报，30（4）： 1150-1165 DOI: 10.11834/jrs.20265345. DOI：

Zhao J Q，Hou C B，Niu Y F，Wang S，Zhou Z P，Fan Q Y and Wang Z X. 2026. 3D coseismic deformation and slip distribution inversion of the 2024 Noto M_w 7.5 earthquake. National Remote Sensing Bulletin， 30（4）：1150-1165 DOI: 10.11834/jrs.20265345. DOI：

摘要

为深入分析2024年1月1日本能登半岛发生

7.5级地震发震机制和构造活动特征，本文依据ALOS-2 PALSAR-2卫星降轨影像、Sentinel-1/2影像，首先采用合成孔径雷达差分干涉测量D-InSAR（Differential Interferometric Synthetic Aperture Radar）、SAR像素偏移跟踪技术POT（Pixel Offset Tracking）和光学影像互相关技术OIC（Optical Image Correlation）获取本次地震的同震形变场；然后，基于最小二乘法解算三维同震形变场，并利用Okada位错模型确定本次地震的断层几何参数；最后基于分布式滑动模型反演本次地震断层面上的精细滑动分布，并计算同震库伦应力扰动。结果表明：（1）三维形变场表明，轮岛市产生了5 m的地表抬升，并在其西南部产生了大约1 m的南北向形变，沿海区域产生了大约2 m的东西向形变；（2）滑动分布反演结果揭示2024年能登地震是一次大型的浅源逆冲型地震，破裂断层主要为位于猿山和轮岛破裂区间的东北—西南走向的东南倾斜逆断层，地震破裂主要集中在0—10 km深度范围，最大滑动量达15 m，矩震级为

7.35；（3）同震库伦应力变化显示余震活动主要受应力触发，能登半岛沿海破裂段呈显著应力加载状态，具备未来孕震潜势。因此，后续研究可结合GNSS与地震波等多源数据以提升形变结果的可靠性，并融合深度学习方法提高三维形变解算精度以及断层几何参数精确估计，在此基础上发展耦合物理机制的动态模型，从而模拟同震形变触发次生灾害的链式演化过程，为灾后预警与风险防控提供量化依据。

Abstract

On January 1

2024

a magnitude

7.5 earthquake struck Japan’s Noto Peninsula. To investigate the seismogenic mechanism and tectonic characteristics of the event

this study integrated data from ALOS-2 PALSAR-2 and Sentinel-1/2 satellites. Geodetic techniques

including differential interferometric synthetic aperture radar (D-InSAR)

SAR pixel offset tracking (POT)

and optical image correlation (OIC)

were employed to derive coseismic surface displacement. The 3D coseismic deformation field was resolved using the least-squares method. Fault geometry was determined by employing the Okada dislocation model. Then

distributed slip inversion was performed to resolve the detailed slip distribution on the fault plane

and the associated coseismic Coulomb stress changes were calculated. The principal findings of this study are summarized as follows: (1) The resolved 3D deformation field revealed substantial crustal movement

with the city of Wajima experiencing uplift of up to 5 m. Substantial north-south deformation of approximately 1 m was detected sout

hwest of Wajima

and the east-west component of the deformation field reached a maximum coseismic displacement of 2 m. (2) Slip distribution inversion indicated that the 2024 Noto Earthquake was a major shallow reverse faulting event. The rupture occurred primarily on a northeast-southwest-striking

southeast-dipping reverse fault located between the Suzuyama and Wajima rupture segments. Seismic rupture was predominantly concentrated at depths of 0—10 km

with a maximum slip of 15 m. The estimated moment magnitude was

7.35. (3) Analysis of coseismic Coulomb stress changes suggested that the subsequent aftershock activity was predominantly stress-triggered. The coastal rupture segments of the Noto Peninsula exhibited a state of substantial stress loading

indicating considerable potential for future seismogenesis. Future research should integrate multisource data

such as those from global navigation satellite systems and seismic waves

to enhance the reliability of deformation results. Deep learning techniques can be incorporated to improve the accuracy of 3D deformation resolution and fault geometric parameter estimation. Moreover

dynamic models that couple physical mechanisms should be developed to simulate the cascading evolution process of secondary hazards triggered by coseismic deformation. This endeavor will ultimately provide a quantitative basis for post-earthquake early warning and risk mitigation strategies.

关键词

Keywords

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