Table S4 : 
Stations velocities in the ITRF 2000, 1-sigma uncertainties(1) and residual velocities with respect to belonging plates. 

	Station	Long(E) Lat(N)	ITRF-2000 (mm/yr)		Residual(**) (mm/yr)
				VE	VN	dVE	dVN	VE	VN
	INDIA PLATE								
INDIA	 IISC	77.57	13.021	40.02	33.32	0.19	0.08	-0.8	-0.76
	 HYDE	78.551	17.417	41.44	34.66	0.65	0.23	1.31	0.58
	 MAHE	80.148	28.963	37.17	33.59	0.81	0.31	-0.17	-0.47
	 NEPA	81.575	28.134	38.28	35.67	0.8	0.32	0.27	1.66
	 BHAI	83.418	27.507	37.04	34.32	0.94	0.37	-1.67	0.4
	 SIMR	84.984	27.165	40.57	32.6	1.17	0.48	1.34	-1.22
NEPAL	 SURK	81.635	28.586	33.42	36.16	1.96	0.9	-4.47	2.15
	 SIMI	81.826	29.967	34.49	24.57	1.88	0.91	-3.01	-9.43
	 RANJ	82.573	28.063	37.91	33.42	2.33	1.03	-0.4	-0.55
	 TANS	83.554	27.874	38.59	33.51	2.2	0.93	-0.05	-0.41
	 JOMO	83.718	28.781	36.74	25.1	2	0.8	-1.68	-8.81
	 POKH	83.978	28.199	37.58	33.48	2.37	0.97	-1.09	-0.41
	 DAMA	85.108	27.608	40.87	33.52	1	0.44	1.73	-0.29
	 NAGA	85.521	27.693	40.12	32.43	0.84	0.34	0.89	-1.35
	 GUMB	85.877	27.91	40.33	28.01	0.93	0.43	1.06	-5.74
	*MALD	73.526	4.189	33.47	68.49	2.36	0.66	-8.17	34.51
	SUNDA PLATE 							
MYANMAR	 WETL	95.778	22.367	30.91	7.82	2.36	0.87	-3.84	11.55
	 BODA	96.111	22.36	28.95	0.8	3.13	1.19	-5.79	4.67
	 KUNT	96.317	22.324	29.63	-1.61	2.61	0.94	-5.09	2.35
	 THIT	95.809	22.162	29.6	11.07	2.44	1.2	-5.10	14.82
	 YWEN	96.535	22.06	28.78	-5.44	0.98	0.39	-5.88	-1.39
	 KWEH	95.286	22.049	29	12.83	0.96	0.38	-5.69	16.36
	*MDPG	96.097	22.009	7.21	2.13	0.84	0.37	-27.45	6.00
	 LEPA	96.011	22.003	31.33	8.13	2.57	1.1	-3.34	11.96
	 SAYE	95.919	21.991	28.84	9.15	1.65	0.87	-5.83	12.94
	 YANG	96.172	21.989	28.86	1.57	2.55	0.98	-5.80	5.47
	 LEGY	95.757	21.986	28.12	9.76	1.8	0.9	-6.55	13.49
	 HTIS	95.595	21.962	31.33	11.13	1.9	0.87	-3.34	14.79
	 TNYO	95.981	21.934	29.21	6.3	2.99	1.14	-5.44	10.12
	 ZIBI	96.321	21.89	28.4	-2.76	2.2	0.9	-6.23	1.20
	 MYOT	95.716	21.691	30.32	10.13	2.03	0.87	-4.29	13.84
	 CHAU	95.919	21.672	30.2	10.46	2.44	1.08	-4.40	14.25
	 NYAN	96.081	21.636	32.48	8.77	3.15	1.22	-2.11	12.63
	 KINV	96.323	21.473	28.76	-5.99	2.13	1.17	-5.79	-2.03
	 MIND	93.897	21.383	34.35	20.91	1.22	0.53	-0.23	23.86
	 LAUN	94.537	17.692	39.97	25.62	1.48	0.69	6.26	28.84
	 TAUN	97.094	20.75	31.06	-6.24	1.24	0.52	-3.31	-1.96
	 HPAA	97.715	16.938	33.55	-4.77	1.31	0.52	0.09	-0.23
 

INDOCHIN PHON	102.101	21.684	35.7	-8.43	1.44	0.61	1.3	-2.09
	 OTRI	99.371	18.335	30.95	-3.23	0.74	0.86	-2.81	1.99
	 VIEN	102.516	18.026	36	-5.37	1.44	0.56	2.42	1.14
	 NONN	108.263	16.004	31.08	-9.17	0.74	0.27	-1.79	-0.36
	 UTHA	100.013	15.384	31.55	-4.17	0.4	0.18	-1.44	1.32
	 SRIS	104.416	14.901	33.83	-10.04	0.98	0.67	1.09	-2.76
	 KHON	105.852	14.119	33.74	-6.36	1.51	0.56	1.26	1.5
	 CHON	101.045	13.121	32.34	-4.33	0.37	0.15	0	1.58
	 BANH	99.076	10.61	33.02	-2.53	1.14	0.6	1.4	2.57
	*SIEM	103.815	13.409	35.42	-13.41	2.4	0.86	3.07	-6.37
	*PENH	104.918	11.574	16.17	-15.03	2.9	0.95	-15.62	-7.55
	*QT04	107.087	10.353	26.03	-6.63	2.15	0.7	-5.33	1.72
	 BENG	102.252	-3.786	26.04	14.34	0.65	0.2	-0.09	20.75
	 TEDA	97.82	0.571	27.99	29	0.68	0.22	0.02	33.58
MALAYSIA PHUK	98.304	7.759	32.49	-1.83	0.36	0.14	1.81	2.95
	 ARAU	100.28	6.45	31.83	-4.81	0.42	0.27	1.63	0.79
	 IPOH	101.126	4.588	31.14	-6.62	0.47	0.27	1.62	-0.67
	 KTPK	101.718	3.171	30.21	-7.08	0.36	0.2	1.22	-0.89
	 GETI	102.105	6.226	31.76	-6.76	0.38	0.24	1.66	-0.41
	 DOP4	102.321	6.039	33.22	-8.91	1.7	0.55	3.18	-2.48
	 SEGA	102.732	2.486	29.3	-4.12	1.25	0.68	0.58	2.48
	 KUAL	103.139	5.319	31.05	-7.01	0.22	0.09	1.28	-0.24
	 KUAN	103.35	3.834	30.71	-5.38	0.37	0.17	1.49	1.47
	 UTMJ	103.64	1.566	29.22	-9.94	0.45	0.23	0.86	-2.97
	 NTUS	103.68	1.346	29.45	-8.39	0.33	0.13	1.18	-1.4
	 TANJ	106.176	-1.881	27.25	-8.07	0.67	0.2	0.28	-0.08
	 MEDA	98.638	3.555	32.71	-0.15	0.28	0.1	3.56	4.77
	 SAMP	98.715	3.622	32.64	-0.22	0.28	0.1	3.46	4.73
	*USMP	100.304	5.358	37.28	-9	0.56	0.34	7.47	-3.39
	*DOP5	100.385	6.14	35.17	-3.81	1.68	0.57	5.08	1.83
	*DOP1	101.446	3.025	24.02	2.08	1.71	0.52	-4.91	8.16
	*DOP3	102.622	3.464	34.6	2.37	1.72	0.53	5.51	8.93
	*DOP2	103.608	1.377	30.49	-10.55	1.7	0.51	2.21	-3.59
	*CCBS	103.959	1.342	48.48	3.1	1.96	0.61	20.21	10.2
BORNEO	 TABA	108.891	0.863	29.71	-10.13	0.89	0.22	1.64	-1.07
	 KUCH	110.195	1.632	26.49	-11.25	0.92	0.37	-1.87	-1.68
	 BINT	113.067	3.262	27.54	-11.67	0.56	0.2	-1.39	-1
	 MIRI	114.002	4.372	26.17	-10.56	0.56	0.22	-3.13	0.46
	 BATU	114.791	-3.867	26.48	-9.6	0.68	0.21	0.25	1.72
	 BRUN	115.031	4.966	26.43	-11.76	0.44	0.15	-3.05	-0.35
	 LABU	115.245	5.283	26.4	-11.8	0.44	0.15	-3.18	-0.31
	 KINA	116.039	5.905	25.41	-10.8	0.53	0.19	-4.35	0.98
	 D005	116.486	6.394	26.15	-9.84	1.92	0.59	-3.76	2.11
	 PUER	118.851	10.086	33.43	-15.23	0.75	0.23	2.53	-2.43
	*T030	110.219	1.586	18.33	-9.19	4.1	1.1	-10.01	0.39
	*SIBU	111.843	2.27	16.94	-9.47	2.42	0.93	-11.64	0.73
	 BLKP	116.815	-1.272	23.94	-14.06	0.98	0.28	-3.32	-1.99
	 TNJB	117.641	0.558	20.2	-14.39	1.58	0.5	-7.74	-2.02
	 MTAW	117.882	4.263	22.76	-17.07	0.35	0.11	-6.44	-4.62
	 TAWA	117.979	4.251	22.74	-17.09	0.35	0.11	-6.46	-4.6
	 SAND	118.121	5.842	27.72	-18.01	0.7	0.26	-1.98	-5.47
	 ZAMB	122.073	6.973	18.1	-11.53	0.77	0.24	-11.83	2.41
JAVA	 BAKO	106.849	-6.491	22.73	-8.88	0.21	0.07	-2.26	-0.63
	 BUTU	110.208	-7.635	30.8	-7.37	0.82	0.23	6.26	2.2
	 BALI	114.68	-8.147	27.49	-10.94	0.61	0.2	3.07	0.34
S CHINA	 CC06	125.445	43.791	29.6	-11.44	1.37	0.67	-3.52	3.64
	 TSKB	140.087	36.106	-4.53	-8.53	0.18	0.1	-35.48	10.84
	 XIAN	109.221	34.369	33.41	-15.88	0.58	0.41	-2.12	-6.69
	 SHAO	121.2	31.1	31.94	-14.29	0.19	0.1	-2.13	-0.66
	 WUHN	114.357	30.532	33.22	-13.72	0.15	0.09	-1.58	-2.56
	 KUNM	102.797	25.03	30.29	-19.76	0.36	0.21	-4.69	-13.13
	 TAIW	121.537	25.021	38.67	-19.72	1.22	0.44	5.12	-5.97
	 CAMP	107.313	20.999	35	-10.28	0.68	0.28	0.98	-1.84
	*QT02	106.791	20.696	32.53	-16.37	2.02	0.8	-1.46	-8.14

Stations are grouped by regions. Sites names in bold were used to calculate rotation parameters for India and Sunda Plates.

* Stations rejected from the solution.
** Residual velocities are relative to the respective plate.


(1) It is notorious that GPS positions determination are affected by biases which are not modelled in the processing (seasonal variations, tribrach offsets, mismounting of antennas, monuments erratic motion, etc...). It is possible to accurately quantify and analyse these biases with permanent stations providing continuous and long time series. Then a proper model of noise can be adjusted to the data. And then an accurate uncertainty can be inferred. For obvious reasons, it is much more difficult to do with campaign data, especially when only 2 or 3 campaigns determine the velocity.
However, stochastic noise on the campaign positions, by the mean of a random walk process (known as Markov process to the GLOBK users) can be applied to the sites. Using a value of 2 mm/sqrt(yr) (which gives a maximum of 6mm for two positions 10 years apart) leads to a realistic estimation of their velocity uncertainty, but also loosen the definition of the reference frame and the tie between regional and local stations measured not simultaneously (there's no free lunch). Doing so, we obtain a solution in which our local and regional stations exhibit velocity uncertainties typically around 1 mm/yr (1 sigma). The velocities themselves don't change by more than 1-2 mm/yr, which is within this range of uncertainty, depending on one's preference for 1, 2 or 3-sigma level. Even more important, these slight changes are randomly distributed and don't affect much the pole determinations.

