## 2 Materials and Methods
### Data Processing Strategy  
There are two classical modes, including the relative positioning and precise point positioning, in the GNSS data processing domain. The relative positioning can eliminate all satellite ends and station ends errors, and improve the resolution of phase ambiguities. The relative positioning algorithm in GAMIT/GLOBK package version 10.6, with BDS data handling function enabled, is employed in this study [19; 20]. The same setting of parameters and strategies of data processing was applied for both BDS and GPS data in order to avoid strategically errors in the comparison of positioning results. The ionosphere-free combination was introduced in forming observation equations to eliminate the first-order ionosphere delay effects, and the second-order ionosphere effects are corrected by models reported by [PERSON] et al. [21]. As the second-order ionosphere effects are correlated with the total electron content and geomagnetic field, the Vertical Total Electron Content (VTEC) maps from the Center for Orbit Determination in Europe (CODE) and the newly updated geomagnetic field model IGRF12 from the international geomagnetic reference, were applied to eliminate their influences [21]. The VMF1 mapping function was employed in the modeling of the dry part of troposphere delay effects, with atmosphere pressure and temperature parameters collected from station-wise meteorological files and GPT2 grid files, to improve the accuracy of estimated station position parameters on the vertical component [22]. The wet part of troposphere delay effects was set as unknown hourly parameters in the final estimation of position coordinates, together with two daily gradient parameters in the north-south and east-west directions, respectively. The IGS14 absolute phase center model was applied to correcting the variation of phase center for satellites and receivers. Satellite final orbits were determined with ephemeris produced by Wuhan University ([[ftp://ics.gnsslab.cn](ftp://ics.gnsslab.cn)]([ftp://ics.gnsslab.cn](ftp://ics.gnsslab.cn))), which include BDS and GPS satellite ephemeris. Other classical parameters and models are all referred to the newly updated results from MIT ([[http://www-gpsg.mit.edu](http://www-gpsg.mit.edu)]([http://www-gpsg.mit.edu](http://www-gpsg.mit.edu))). The sampling frequency was set to 30 s, and the cut off of elevation angle is 10\({}^{\circ}\). During the data processing stage, station position and earth  
Figure 1: The distribution map of the station deployed with BDS/GPS dual mode receivers. The blue and red solid triangles represent the location of BDS/GPS dual-frequency stations, with the total number being 62. The red solid triangles are stations analyzed in this study, with the number being 44 and their data integrity being over 95% in the period of the analysis. rotation parameters were simultaneously estimated as unknowns in the final loosely constrained daily solution. Figure 2 shows the ratio of ambiguity determined as integer value for both GPS and BDS observations, respectively. A total of 86.9% daily ambiguities are fixed to be integers for GPS observations. The number drops to 66.8% for BDS observations on average, together with significant temporal variations. The scope of BDS ambiguity resolution is about 40-90%, which may be attributed to the temporally uneven distribution of BDS satellites [23]. Two sets of quasi-observation files (H files) are produced on GAMIT for BDS and GPS observations, respectively. To finally resolve station position parameters, we used the daily constrained bias-fixed solutions of the parameters and their associated covariance matrices as quasi-observations in GLOBK to generate position time series in the International Terrestrial Reference Frame 2014 (ITRF2014). Three types of combination strategies, GPS, BDS and GPS/BDS combined were implemented. In the GPS/BDS combined solution, the weights of both H files were set to be equal due to their similar quality of observations.