# InSAR-CTPIM-Based 3D Deformation Prediction in Coal Mining Areas of the Baisha Reservoir, China
## 7 Conclusions  
In this paper, a three-dimensional time series deformation prediction method, InSAR-3D-CTPIM, based on InSAR differential interferometric phasing, was proposed and applied to the prediction of time series deformation on the surface of the Jiansheng coal mining area southwest of the Baisha Reservoir in Henan Province, China. A combination of simulation and real experiments was used to verify the reliability of the method. The results of the simulation experiment showed that the RMSE of the model was \(\pm\)2.2 mm vertically upwards. In the real experiment, the InSAR-3D-CTPIM prediction parameters were solved using the 13-scene images during the period from 13 November 2015 to 19 November 2016 as the observation, and then the prediction model was used to obtain the prediction parameters of the mining area for the period from 1 December 2016 to 7 March 2017, in the vertical, east-west and north-south directions. The prediction results of vertical, east-west and north-south deformations were obtained for the period from 1 December 2016 to 7 March 2017, using the prediction model. The predicted results showed that the maximum subsidence in the vertical, east-west and north-south directions of the mine area reached 181 mm, 46 mm and 40 mm, respectively. The deformation of the mine area showed an overall non-linear subsidence trend in the time series, and the level data were consistent with the values predicted by the method used in this study.  
Moreover, compared with the traditional linear model and the traditional static probability integral model prediction method, the modeling accuracy of this method was improved by 34.3%, and the deformation prediction accuracy was enhanced by 28.5%. Under the influence of the high noise of 0.6 rad, the RMSE of deformations caused by InSAR-3D-CTPIM was less than 4.2 mm, while the RSME caused by the traditional static PIM method was 6.1 mm, indicating that the method in this paper can effectively avoid the secondary transmission of errors and improve the deformation prediction accuracy. However, this method does not take into account the spatial correlation of the highly coherent points in the mining basin and the spatial correlation of different points in the InSAR-three-dimensional time series modeling.  
Conceptualization, M.L.; methodology, T.Z. and J.S.; software, M.L.; validation, J.Y. and T.Z.; formal analysis, M.L. and J.S.; investigation, M.L. and J.Y.; resources, M.L. and J.Y.; data curation, J.S.; writing--original draft preparation, M.L. and T Z; writing--review and editing, J.S.; visualization, T.Z.; supervision, J.S. and T.Z.; project administration, M.L.; funding acquisition, J.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China [grant numbers 42074033], the Provincial Natural Science Foundation of Hunan [grant numbers 2022]J30589], Science and Technology Innovation Project of Hunan Provincial Department of Transportation (2022-11) [grant numbers 20230118 CH], and Science and Technology Program Project of Hunan Provincial Department of Natural Resources [grant numbers kq2209011].  
Not applicable.  
Data are contained within the article.  
Thanks to [PERSON] and [PERSON] from Changsha University of Science & Technology for helping with data curation and visualization for this study.  
Author [PERSON] was employed by the company Hunan Zhongkan Beidou Research Institute Co. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.