Abstract:

Accurately and rapidly assessing seismic intensity following an earthquake is essential for effective emergency response, targeted disaster relief, and scientifically informed post-disaster reconstruction. This need is particularly acute in seismically active and often remote regions such as Xinjiang, China. Situated in the interior of Eurasia, Xinjiang is characterized by complex geological structures, where compressional forces from the north and south dominate tectonic activity across the Tianshan, Pamir, and other mountain ranges. Such tectonic environment produces frequent strong earthquakes, most of which are thrust events. Compared with strike-slip and normal faulting, thrust earthquakes are associated with shallow fault dips and may be linked to near-horizontal detachments. Fault displacement is typically absorbed by distributed fold deformation along the fault and attenuates rapidly, often producing little or no surface rupture. These characteristics complicate the interpretation of coseismic rupture processes and the spatial distribution of earthquake damage. Combined with the region's rugged terrain and sparse infrastructure, thrust earthquakes pose a serious threat to lives and property in Xinjiang.

High-quality, rapid post-earthquake intensity assessments are therefore critical to reducing earthquake impacts. Intensity maps are a primary basis for emergency rescue, recovery, and reconstruction. Traditional field investigations of intensity, however, require considerable human and material resources, pose safety risks to investigators, and are influenced by subjective judgment in assessing building damage. Additionally, since the widespread implementation of seismic-resistant housing projects in Xinjiang after 2003, the uniformity of residential building types has further limited the effectiveness of on-site evaluations.

With the advancement of remote sensing technology, Interferometric Synthetic Aperture Radar(InSAR)has emerged as a powerful tool for surface deformation monitoring and disaster assessment. Its all-weather, all-day imaging capabilities, unaffected by conditions such as rain or snow, make Differential InSAR(D-InSAR) an important technique for monitoring earthquake-induced surface deformation. To explore the relationship between seismic intensity and coseismic deformation and to address the challenge of rapid thrust-earthquake intensity assessment in Xinjiang, this study investigates three thrust earthquakes: the 2015 Pishan M_S6.5, the 2017 Jinghe M_S6.6, and the 2020 Jiashi M_S6.4 events.

Comparisons between InSAR-derived coseismic deformation fields and field-surveyed seismic intensities reveal a strong correlation. In population centers, deformation of 0.5~1.5cm corresponds to intensity Ⅶ, while deformation exceeding 1.5cm corresponds to intensity Ⅷ. Using these relationships, a linear regression model was developed between deformation and intensity levels. Furthermore, based on both a single-factor evaluation(coseismic deformation) and a multi-factor framework that integrates InSAR deformation, coseismic stress changes, population density, source distance, and sedimentary thickness, intensity assessments were performed using the AHP-entropy weight method.

The results indicate that:

(1)D-InSAR can rapidly monitor large-scale surface deformation after an earthquake, providing comprehensive and accurate coseismic deformation patterns. Unlike traditional methods dependent on sparse seismic station data, InSAR directly reflects the spatial distribution of regional deformation and supplies valuable geological background information for seismic intensity evaluation, especially in regions with limited building-type diversity or seismic station coverage.

(2)There is a clear relationship between seismic intensity and coseismic deformation. Mapping deformation fields onto intensity scales allows for the rapid estimation of earthquake intensity levels. Using historical deformation-intensity relationships enhances early evaluations of both the intensity grade and its spatial extent in future earthquakes.

(3)Multi-factor evaluation combining InSAR deformation with stress change, population density, focal distance, and sediment thickness improves the reliability of seismic intensity assessments compared to single-factor approaches. This method integrates both natural factors(e.g. geology, topography) and socioeconomic factors(e.g. population distribution), thereby capturing the complexity and diversity of earthquake impacts.

Overall, the AHP-entropy weight-based multi-factor evaluation framework demonstrates strong potential for application in earthquake risk assessment, disaster prevention and mitigation. At the same time, this study discusses the limitations of applying InSAR for thrust-earthquake intensity evaluation, offering insights for future research. The findings support more accurate and rapid post-earthquake assessments and highlight the value of InSAR technology in evaluating strong earthquake intensity in Xinjiang.

Key words: D-InSAR, coseismicdeformation, seismic intensity

摘要：

为探索地震烈度与地震发生后地表形变的关系, 解决震后快速评估新疆逆冲型地震烈度的难题, 文中以新疆2015年皮山6.5级、 2017年精河6.6级、 2020年伽师6.4级3个逆冲型地震为例, 通过对比研究不同地震的InSAR同震形变场与实际调查地震烈度数据, 发现同震形变场与地震烈度之间存在较高的相关性。研究结果表明: 1)InSAR技术能够有效地识别出震区的同震形变场, 为震后的地震烈度评估提供了重要的数据支持, 对评价房屋结构类型单一和缺少强震动台站观测数据区域的烈度评估提供了重要依据; 2)利用人口聚集区的同震形变进行烈度评估的手段, 以及利用历史地震事件的烈度-形变关系模型和同震形变场大小估计当前地震的烈度等级的方法可在地震烈度早期评估中发挥重要作用, 有助于我们今后调查地震烈度等级和烈度影响的范围判断; 3)利用AHP-熵权法对InSAR形变量、 库仑应力变化值、 人口密度、 震源距离、 沉积层厚度这5个因子进行加权叠加并进行烈度评估研究可提高地震烈度评估结果的可靠性, 该方法可为地震烈度评估提供一种新的思路。同时, 文中还讨论了InSAR同震形变场的逆冲型地震烈度评估方法的局限性, 为今后的研究提供了参考。

关键词: D-InSAR, 同震形变, 地震烈度