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(1)

12 m antenna

140” antenna

Ionosphère

Résolu grâce au bi-fréquence

Limitations de la précision

τ

ion1 = α Ne / f12

τ

ion2 = α Ne / f22

=> Ne =

[ τ

ion2 -

τ

ion1

] /

α (1/ f22 - 1/ f12 ) troposphère

L’effet horizontal s’auto compense L’effet vertical demeure

Résolu grâce à des mesures longues

PROPAGATION

1: propagatives

(2)

2

One way phases are affected by stations and satellites clock uncertainties

Double differences Are free from all clock uncertainties but

=> Measurement of distances between points (= baselines)

=> Relative positioning

Single differences are affected by stations clock uncertainties

Or

satellites clock uncertainties

Limitations de la précision

2: mesure du temps

(3)

centre de phase des antennes

Limitations de la précision

Centrage des embases Résolu grâce au centrage forcé

TECHNIQUE

Résolu grâce à l’utilisation d’antennes identiques

3: instrumentales

(4)

4

GPS est précis, à condition de :

1. GPS bi-fréquence pour éliminer l’ionosphere

2. Mesures longues pour « moyenner » la troposphère

3. Mesures relatives de distances entre stations

4. Utilisation d’antennes identiques, orientées

parallèlement, et du centrage forcé sur les

repères pour éviter les biais instrumentaux

(5)

Precision and repeatability

10 measurements of the same baseline give slightly different values :

80 km +/- 10 mm How many

measurements are between 80 and 80+δ The histogram curve is a Gaussian statistic The baseline

repeatability is the sigma of its

Gaussian scatter

(6)

6

Network repeatabilities

Network of N points (N=9)

(N-1) (=8) baselines from 1st station to all others (N-2) (=7) baselines from 2nd station to all others

=> subtotal = (N-1)+(N-2) total number of baselines

= (N-1)+(N-2)+…+1

= N(N-1)/2 (36 in that case)

(7)

Typical repeatabilities (60 points => ~1800 bsl)

Repeatabilities are much larger than formal uncertainties !

(8)

8

1 order of magnitude Improvment over a decade

1-2 mm 1-10 cm

1-2 cm 1-10 mm

(9)

Accuracy vs. precision (1)

Fix point :

measure 1 hour every 30 s

=> 120 positions

with dispersion ~+/- 2 cm 5 hours later, measure again 1 hour at the same location

=> Same dispersion but constant offset of 5 cm

Precision = 2 cm Accuracy = 5 cm

(10)

10

Accuracy vs. precision (2)

Measure path, 1 point every 10s

=> 1 circle with 50 points 10 circles describe runabout with dispersion ~ 2 cm

Next day, measure again

=> Same figure but constant offset of 6 cm

Precision = 2 cm Accuracy = 6 cm

(11)

Mapping in a reference frame (sketch)

Measure short lines with a good precision is easy.

Quantify deformation within a small network is easy

BUT

Determine the motion of the whole network with respect to the rest of the world is more difficult

In order do do this…

We need to know how to map

into a reference frame ⇒ compute Helmert transformations

(12)

12

Mapping in a reference frame (1)

… when station

displacement is constant with time

Constraining campaign positions (and or velocities) to long term positions (and or velocities) works fine …

if the station motion is linear with time, then estimating the velocity on any time span will give the same value

(13)

Mapping in a reference frame (2)

… when station

displacement is not constant with time

Constraining campaign positions (and or velocities) to long term positions (and or velocities) does not work

if the station motion is not linear with time, then estimating the velocity on different time span will give different values

(14)

14

Mapping in a reference frame (3)

some stations are better than others …

(15)

From position to velocity uncertainty

If one measures position P1 at time t1 and P2 at time t2 with precision ∆P1 and ∆P2, what is the velocity V and its

precision ∆V ?

V = (P2 - P1) / (t2 - t1)

∆V = (∆P2

X

+ ∆P1 ) / (t2 - t1)

Uncertainties don’t add up simply, because sigmas involve probability.

∆V =

[

(∆P2 )2 + (∆P1 ) 2

]

1/2

/

(t2 - t1)

(16)

16

Velocity uncertainties

It is only needed that we wait a given time between position measurements to detect deformation velocities

Reasonnable (but wrong) idea:

Geodesy is like good wine: measurements, even (and mostly) bad ones, gain value by aging

The more we wait, the more precise the velocity is

(17)

In practice…: BRAZ : 2000->2007

4,650 4,700 4,750 4,800 4,850 4,900 4,950

0 500 1000 1500 2000 2500

days

horizontal position (m)

4,800 4,810 4,820 4,830 4,840 4,850 4,860 4,870 4,880 4,890 4,900

0 100 200 300 400 500 600 700

4,810 4,815 4,820 4,825 4,830 4,835 4,840 4,845 4,850

0 100 200 300 400 500 600 700

7 years

2 years 2 years

+ zoom

4,820 4,825 4,830 4,835 4,840 4,845 4,850

0 100 200 300 400 500 600 700

2 years

+ zoom + detrended

4,820 4,825 4,830 4,835 4,840 4,845 4,850

0 500 1000 1500 2000 2500

All 7 years + zoom + detrended

(18)

18

18,0 1

deviation month

4,830 4,831 4,832 4,833 4,834 4,835 4,836 4,837 4,838 4,839 4,840 4,841 4,842 4,843 4,844 4,845

0 5 10 15 20 25 30 35

4,830 4,831 4,832 4,833 4,834 4,835 4,836 4,837 4,838 4,839 4,840 4,841 4,842 4,843 4,844 4,845

0 10 20 30 40 50 60 70

4,830 4,831 4,832 4,833 4,834 4,835 4,836 4,837 4,838 4,839 4,840 4,841 4,842 4,843 4,844 4,845

0 20 40 60 80 100

4,830 4,831 4,832 4,833 4,834 4,835 4,836 4,837 4,838 4,839 4,840 4,841 4,842 4,843 4,844 4,845

0 50 100 150 200

4,830 4,831 4,832 4,833 4,834 4,835 4,836 4,837 4,838 4,839 4,840 4,841 4,842 4,843 4,844 4,845

0 50 100 150 200 250 300 350 400

4,830 4,831 4,832 4,833 4,834 4,835 4,836 4,837 4,838 4,839 4,840 4,841 4,842 4,843 4,844 4,845

0 100 200 300 400 500 600

4,830 4,831 4,832 4,833 4,834 4,835 4,836 4,837 4,838 4,839 4,840 4,841 4,842 4,843 4,844 4,845

0 100 200 300 400 500 600 700 800

1 month

In practice…: BRAZ : 2000->2007

2 months

-7,8 2

3 months

-13,2 3

6 months

-6,4 6

12 months

-1,3 12

18 months

-1,0 18

24 months

-0,2 24

(19)

precision of velocity determination

-20,0 -15,0 -10,0 -5,0 0,0 5,0 10,0 15,0 20,0

0 3 6 9 12 15 18 21 24 27

months

difference from trend (mm/yr)

-0,2 24

-1,0 18

-1,3 12

-0,1 11

0,0 10

-0,3 9

-1,8 8

-3,1 7

-6,4 6

-7,7 5

-9,9 4

-13,2 3

-7,8 2

18,0 1

deviation month

(20)

20

precision of velocity determination

-20,0 -15,0 -10,0 -5,0 0,0 5,0 10,0 15,0 20,0

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 months

difference from trend (mm/yr)

(21)

Velocity ellipses

(22)

22

Maintenant, que mesure-t-on

exactement avec GPS ?

(23)

140” antenna

GPS antenna on tripod

Geodetic Geodetic marker marker Campagnes de répétition

(24)

24

(25)

Repeated Campaigns

(26)

26

12 m antenna

140” antenna

Stations permanentes

(27)
(28)

28

Permanent station

(29)

Au premier ordre, la géodésie sur une décennie « colle » bien avec la géologie sur 3 Ma!

=>Les plaques ont donc des déplacements stables sur ce type de durée mais…. GPS trouve Arabie, Inde et Nazca plus lentes actuellement

Arabie et Inde => ralentissement

À grande échelle: les plaques

(30)

30

La déformation autour des frontières de plaques

Uy = 2.V0

/

Π arctang (x

/

h)

Le concept: déformation élastique à cause du

frottement Le modèle: le flux mantellique localise la déformation sous une plaque élastique

La solution analytique:

une courbe en arctangente

(31)

Arctang profiles

Uy = 2.V0

/

Π arctang (x

/

h)

(32)

32

La faille de Sagaing en Birmanie

Vigny et al., 2003 Vigny et al., 2003

(33)

Conclusion:

z

Quand les stations sont bien à l’intérieur des plaques (loins des marges qui se déforment) GPS mesure la tectonique des plaques

z

Quand les stations sont dans les marges qui se

déforment, GPS ne mesure pas la vitesse des failles (qui est en général zéro si la faille est bloquée), mais la déformation élastique qui s’accumule en réponse au blocage. C’est au travers d’un modèle (Okada par exemple) que l’on retrouve …. La vitesse limite (càd la tectonique) et l’épaisseur élastique, mais toujours pas la vitesse de la faille, concept qui ne veut pas dire

grand-chose.

(34)

34

Le cycle sismique:

Shimazaki et Nakata, 1980 Wallace, 1987

Vitesse

court terme de la faille:

~constante

~variable

Références

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