×

You are using an outdated browser that does not fully support the intranda viewer.
As a result, some pages may not be displayed correctly.

We recommend you use one of the following browsers:

Full text

Title
Mapping without the sun
Author
Zhang, Jixian

Secondly, use high time/frequency GPS data to interpolate the
original results mentioned above. Then the quasi-GPS time
series data can be obtained with time domain interpolation.
Finally, Kalman filtering can be used to estimate and predict the
quasi-GPS data with both spatial and time domain interpolation
to get full surface subsidence deformation value of mining area
with high precision.
3. MAIN PROBLEMS OF GPS/INSAR DATA FUSION
The researches of InSAR/GPS data fusion fields already
acquired important progress, while this technique also needs to
be improved because of its problems. The main problems are as
follows:
1) At present, there isn’t a set of complete InSAR/GPS data
fusion theory and method. The GPS data correction researches
focused on a certain InSAR error.
2) The phase unwrapping algorithm takes great effect on InSAR
products precision, however, up to now no practical
unwrapping algorithm was applied.
3) Only GPS data was used to establish the model of
atmospheric delay error, whereas the InSAR data itself is
ignored. Theoretically, GPS data could create high precision
atmospheric delay model, but it can only apply single point
information and must use spatial interpolation to realize
modeling, this will cause the decrease of data precision
undoubtedly.
4. CONCLUSIONS
InSAR/GPS data fusion technique plays an important role in
monitoring the surface subsidence in mining area. GPS
technique can take its advantages on InSAR data, such as the
modeling of atmospheric delay error; the establishment of
InSAR satellite orbital parameters, the geometric correction of
InSAR data, and so on. While InSAR data could apply
furthermore detailed spatial information of the mining area
surface.
In monitoring the surface subsidence of mining area, the
following countermeasures are given as references to improve
the monitoring precision, the spatial and time resolution, and
the result reliabilities. Which may provide technical support for
realizing real-time dynamic monitoring of coal mining-induced
subsidence.
1) PS-InSAR technique should be used in InSAR/GPS data
fusion field widely. This could reduce the impact of spatial and
time resolution limitation of traditional InSAR greatly, and
improve the monitoring precision even to sub-centimetre.
2) Making associated use of permanent scatterer points, grade
levelling root control points and GPS levelling points
measurements, and adopting suitable data processing algorithm
(spatially the phase unwrapping algorithm) could improve the
calculation precision and reliability.
With the implement of the world’s GPS network engineering
and the improving of SAR resolution (including the
improvement of SAR satellites orbital parameter precision),
The integration of InSAR and GPS data’s application in
mining-induced subsidence monitoring will be more extensive.
InSAR/GPS data fusion technology may become one of the
most powerful means in monitoring the surface subsidence of
mining area hopefully.
REFERENCES
Diao, J., 2005. Study of Data Integration of GPS and InSAR
Monitoring Surface Subsidence. Dissertation of the degree of
Master of philosophy from Shandong University of Science and
Technology, pp. 3-7.
Chen, J., 2004. InSAR-GPS-GIS Data Integration and Applica
tion to Detection of Land Subsidence. Journal of Geodesy and
Geodynamics, 24(3), pp. 87-91.
Xu, C., Wang, H., et al., 2003. Prospect on the Integration of
GPS and InSAR data. Geomatics and Information Science of
Wuhan University, 28 (5), pp. 58 - 61.
Ge, L., Chris R., et al., 2001, Mining Subsidence Monitoring
Using the Combined InSAR and GPS Approach. The 10th FIG
International Symposium on Deformation Measurements,
California, Orange, pp.5-6.
Qiao, X., Li, S., et al., 2002. Monitoring Crustal Deformation
by GPS and InSAR in the Three Corge Area. Wuhan University
Journal of Natural Sciences, 7(4), pp. 451-457.
Fan, Q., Tang C., et al., 2006, Applications of GPS and InSAR
in Monitoring of Landslide Studies. Science of Surveying and
Mapping, 31(5), pp. 60-62.
Ge, L., Shao, W. and Chris R., 2000. The Double Interpolation
and Double Prediction (DIDP) Approach for InSAR and GPS
Integration. IAPRS, Vol. XXXIII, Amsterdam, pp. 205-212.
Volker, J., Ge, L., et al., 2003. Tropospheric Delay Corrections
to Differential InSAR Results from GPS Observations. Proc.
6th Int. Symp. on Satellite Navigation Technology Including
Mobile Positioning and Location Services (SatNav), Melbourne,
Australia, pp.22-25.
Shi, S., 2000. DEM Generation Using ERS-1/2 Interferometric
SAR Data. ACTA GEODAETICA ET CARTOGRAPHICA
SINICA, 29(4), pp. 317-323.
Ge, L., Eric, C., et al., 2003. Quantitative Subsidence Monitor
ing: The Integrated InSAR, GPS and GIS Approach. The 6th
International Symposium on Satellite Navigation Technology
Including Mobile Positioning & Location Services (SatNav),
Melbourne, Australia, pp.46-49.
Biirgmann, R., Hilley, G., Ferretti, A. and Novali, F., 2006.
Resolving Vertical Tectonics in the San Francisco Bay Area
From GPS and Permanent Scatterer InSAR Analysis. Geology,
34, pp. 221-224.
Zhang, J., Song, W., et al., 2007. Discussion on PS-InSAR
Technique and its Application in Mining-induced Subsidence
Monitoring. Proceedings of the 13th International Congress of
International Society for Mine Surveying, Budapest, Hungary,
(To be published).
ACKNOWLEDGEMENTS
This work is supported by the National Natural Science
Foundation (No.40571104) and the Excellent Youth Research