# Removing Land Subsidence Impact from GPS Horizontal Motion in Tianjin, China
## 5 Conclusions  
In this paper, we provided a novel and practical approach to addressing the impact of land subsidence on GPS horizontal motion through a sequence-to-sequence deep learning model. We used GRUs to construct the models and applied the models to the GPS stations in the Tianjin subsidence area. Corresponding datasets were generated for each model for model training and testing. Vertical trend data from non-subsidence area GPS stations and local vertical un-trended data were used to generate model input data unaffected by land subsidence. The model prediction output, namely, the horizontal motion of each GPS station in the subsidence area of Tianjin without the impact of land subsidence, was obtained.  
Our analysis reveals that after mitigating the effects of land subsidence, the consistency of horizontal movements among GPS points in the Tianjin subsidence area significantly improves. Across the entire study region, the horizontal movement trends of GPS points within the subsidence zone align more closely with those of adjacent non-subsiding areas. The GPS-derived horizontal movements we obtained better reflect the authentic tectonic activity in the Tianjin region, providing a clearer representation of the true crustal deformation unobscured by subsidence-related disturbances.  
Additionally, our findings indicate that the impact of land subsidence on horizontal movements varies among different GPS points within the Tianjin subsidence area. There are also differences in how subsidence affects horizontal movements across various regions. This phenomenon implies the potential complexity of the mechanisms driving subsidence-induced horizontal displacements.  
This research contributes robust foundational data essential for studies in regional geodynamics and seismic hazard analysis, thereby enhancing the reliability of analyses in these fields. Moreover, it supports the progression toward a deeper understanding of the mechanisms and regularities governing surface deformation in regions experiencing land subsidence. For social risks posed by phenomena such as ground fissures and building deformations, which may be induced by land subsidence, our findings offer improved predictive capabilities concerning the potential hazards, thus aiding in the development of more effective risk assessment and management strategies.  
The present study is subject to certain limitations, notably the comparatively brief duration of the research period and the scarcity of high-precision horizontal displacement measurements. To mitigate these constraints, future investigations will consider extending the temporal scope of the dataset and incorporating advanced auxiliary techniques, such as LiDAR.  
Conceptualization, Z.P. and W.L.; methodology, Z.P.; validation, Z.P. and L.Z.; formal analysis, Z.P.; resources, Z.P.; writing--original draft preparation, Z.P.; writing--review and editing, W.L. and L.Z.; funding acquisition, Z.P. and L.Z. All authors have read and agreed to the published version of the manuscript. This research was funded by National Natural Science Foundation of China (No. 42404079), Tianjin Earthquake Agency Foundation (No.Yb202402).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
**Conflicts of Interest:** The authors declare no conflicts of interest.