Xuhao Li

Dr. Xuhao Li


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 May 2024 in Remote Sensing
Verified
Journal Article
Open access
PDF file
QFQianyou Fan
Qianyou Fan
SZShuangcheng Zhang
Shuangcheng Zhang
YNYufen Niu
Yufen Niu
JSJinzhao Si
Jinzhao Si
XLXuhao Li
Xuhao Li
JJJianwen Jiang
Jianwen Jiang
The continuous downward movement exhibited by the Lashagou landslide group in recent years poses a significant threat to the safety of both vehicles and pedestrians traversing the highway G310. By integrating geomorphological interpretation using multi-temporal optical images, interferometric synthetic aperture radar (InSAR) measurements, and continuous global navigation satellite system (GNSS) observations, this paper traced the formation period of the Lashagou landslide group, and explored its kinematic behavior under external drivers such as rainfall and snowmelt. The results indicate that the formation period can be specifically categorized into three periods: before, during, and after the construction of highway G310. The construction of highway G310 is the direct cause and prerequisite for the formation of the Lashagou landslide group, whereas summer precipitation and spring snowmelt are the external driving factors contributing to its continuous downward movement. Additionally, both the long-term seasonal downslope movement and transient acceleration events are strongly controlled by rainfall, and there is a time lag of approximately 1–2 days between the transient acceleration and heavy rainfall events. This study highlights the benefits of leveraging multi-source remote sensing data to investigate slow-moving landslides, which is advantageous for the implementation of effective control and engineering intervention to mitigate potential landslide disasters.

30 November 2025 in Remote Sensing
Verified
Journal Article
Open access
PDF file
XLXuhao Li
Xuhao Li
QFQianyou Fan
Qianyou Fan
YNYufen Niu
Yufen Niu
SZShuangcheng Zhang
Shuangcheng Zhang
JZJinqi Zhao
Jinqi Zhao
Zhong LuZhong Lu
Zhong Lu
Frequent extreme climate events have intensified landslide hazards in mountainous regions, necessitating efficient identification and classification to understand movement mechanisms and mitigate risks. This study develops a novel, non-contact InSAR framework that seamlessly integrates three key steps—Identification, Inversion, and Classification—to address this challenge. By applying this framework to ascending and descending Sentinel-1 data in the complex terrain of the Jishi Mountain region, we first introduce geometric distortion masking and a C-Index deformation consistency check, which enables the reliable identification of 530 active landslides, with 154 detected in both orbits. Second, we employ a local parallel flow model to invert the landslide movement geometry without relying on DEM-derived prior assumptions, successfully retrieving the two-dimensional (sliding and normal direction) deformation fields for all 154 consistent landslides. Finally, by synthesizing these 2D deformation patterns with geomorphological features, we achieve a systematic classification of movement types, categorizing them into retrogressive translational (31), progressive translational (66), rotational (19), composite (24), and earthflows (14). This integrated methodology provides a validated, transferable solution for deciphering landslide mechanisms and assessing risks in remote, complex mountainous areas.

5 April 2025 in Remote Sensing
Verified
Journal Article
Open access
PDF file
SZShuangcheng Zhang
Shuangcheng Zhang
ZJZiheng Ju
Ziheng Ju
YNYufen Niu
Yufen Niu
Zhong LuZhong Lu
Zhong Lu
QFQianyou Fan
Qianyou Fan
YLYiyao Li
Yiyao Li
Edgecumbe, a dormant volcano located on Kruzof Island in the southeastern part of Alaska, USA, west of the Sitka Strait, has exhibited increased volcanic activity since 2018. To assess the historical and current intensity of this activity and explore its relationship with seismic events in the surrounding region, this study utilized data from the ERS-1/2, ALOS-1, and Sentinel-1 satellites. The Permanent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) and Small Baseline Subset InSAR (SBAS-InSAR) techniques were employed to obtain surface deformation data spanning nearly 30 years. Based on the acquired deformation field, the point-source Mogi model was applied to invert the position and temporal volume changes in the volcanic source. Then, by integrating seismic activity data from the surrounding area, the correlation between volcanic activity and earthquake occurrences was analyzed. The results indicate the following: (1) the coherence of interferograms is influenced by seasonal variations, with snow accumulation during the winter months negatively impacting interferometric coherence. (2) Between 1992 and 2000, the surface of the volcano remained relatively stable. From 2007 to 2010, the frequency of seismic events increased, leading to significant surface deformation, with the maximum Line-of-Sight (LOS) deformation rate during this period reaching −26 mm/yr. Between 2015 and 2023, the volcano entered a phase of accelerated uplift, with surface deformation rates increasing to 68 mm/yr after August 2018. (3) The inversion results for the period from 2015 to 2023 show that the volcanic source, located at a depth of 5.4 km, experienced expansion in its magma chamber, with a volumetric increase of 57.8 × 106 m3. These inversion results are consistent with surface deformation fields obtained from both ascending and descending orbits, with cumulative LOS displacement reaching approximately 210 mm and 250 mm in the ascending and descending tracks, respectively. (4) Long-term volcanic surface deformation, changes in magma source volume, and seismic activity suggest that the earthquakes occurring after 2018 have facilitated the expansion of the volcanic magma source and intensified surface deformation. The uplift rate around the volcano has significantly increased.