## 6 Conclusions  
The integration of PS/SDF/DS based on SNR time-series InSAR was applied to monitor ground displacement in a coal mine in Heze City from 20 May 2017 to 17 December 2018. The experimental results showed that there were four significant areas of subsidence in the study area. Furthermore, the monitoring results of the proposed method were compared to conventional PS-InSAR and SBAS-InSAR methods for verification. Some major conclusions could be drawn as below:  
1. Different InSAR techniques are used for ground displacement monitoring and different quantity of CPs are acquired, the different quantity of CPs lead to different displacement monitoring results (different ranges of displacement values), and the abundance of ground displacement information contained in different displacement value ranges varies.
2. Compared with the conventional time-series InSAR technique, the ground displacement monitoring results obtained by the proposed method have a wider range of values and provide a more comprehensive and refined presentation of ground displacement monitoring results.
3. The quantity of CPs and the density of spatial distribution obtained by the method proposed in this paper are significantly improved compared to the conventional time-series InSAR technique.
4. The displacement monitoring results from the proposed method is consistent with conventional time-series InSAR techniques in terms of displacement trends and distribution and more comparable to SBAS-InSAR in terms of displacement magnitude.  
[PERSON], [PERSON] ([PERSON]) and [PERSON] performed the experiments and produced the results. [PERSON], [PERSON] ([PERSON]) and [PERSON] drafted the manuscript. [PERSON], [PERSON], [PERSON] ([PERSON]), [PERSON] and [PERSON] contributed to the discussion of the results. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the Shandong Provincial Natural Science Foundation (ZR2020 QD049, ZR202 QD025 and ZR2021 QD155), State Key Laboratory of Geodesy and Earth's Dynamics, Innovation Academy for Precision Measurement Science and Technology, CAS, Wuhan 430077, China  
Figure 10: The average velocity of ground displacement correlation and difference distribution of homonymy points among conventional time-series InSAR techniques (PS-InSAR (**a–d**) and SBAS-InSAR (**e–h**)) and the proposed methods. The blue circles represent outliers, the red lines represent regression line and the colorful dots represent the corresponding CPs.  
(SKLGED2023-1-1), the Doctoral Scientific Research Foundation of Shandong Jianzhu University (X18097Z).  
Not applicable.  
Data Availability Statement: The SAR image data used in this paper can be freely accessed at: [[https://schiub.copernicus.eu/](https://schiub.copernicus.eu/)]([https://schiub.copernicus.eu/](https://schiub.copernicus.eu/)) (accessed on 3 April 2014). The land use classification data can be freely accessed at: [[https://livingatlas.arcgis.com/landcover/](https://livingatlas.arcgis.com/landcover/)]([https://livingatlas.arcgis.com/landcover/](https://livingatlas.arcgis.com/landcover/)) (accessed on 10 February 2022).  
The authors would like to express their gratitude to the European Space Agency (ESA) and Environmental Systems Research Institute (ESRI) for providing the data for this study. The provisions of GAMMA by GAMMA Remote Sensing AG, StaMPS by Stanford University and DSIpro by Sun Yat-sen University are also gratefully acknowledged.  
The authors declare no conflict of interest.