72
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
-* DlnSAR (27 Dec 2006 - 11 Feb 2007)
Estimated subsidence from ground survey data (27 Dec 2006-11
Feb 2007)
Figure 10. Validation of DInSAR-derived subsidence profiles
against ground truth.
4.4 Accumulated Subsidence
The accumulated subsidence has been derived for the period 29
Jun 2007 to 14 Feb 2008 (230 days) using the 6 ascending
ALOS PALSAR images (Figure 11). In the most ideal situation,
the height displacement between 29 Jun 2007 and 14 Feb 2008
should be directly calculable from the differential interferogram
29 Jun 2007~14 Feb 2008. However, similar to other
differential interferograms over long time spans, it is usually
very difficult to unwrap the interferometric phase correctly due
to high deformation gradient and decorrelation. Therefore an
alternative technique was used to compute the subsidence for
the period 29 Jun 2007~14 Feb 2008 by accumulating the
subsidence from successive SAR pairs. The simplest way to
determine the accumulated subsidence is to combine all
subsidence maps generated from each ALOS pairs. However,
the error in each DlnSAR result will also be accumulated.
In order to reduce the geocoding error between each DlnSAR
result and the noise due to accumulating the deformation, a
simple approach has been developed, as outlined below. (1) All
ALOS PALSAR images were first resampled with respect to a
reference master. (2) DlnSAR analysis was then carried out to
measure the deformation of the same points in each co-
registrated images, i.e. interferograms 2-6 in this study (Table
1). (3) The deformations calculated from the five differential
interferograms were added together (in slant range) prior to
geocoding the accumulated deformation map. (4) Geocode the
accumulated deformation map. Given the assumption that the
expectation of the atmospheric delay for a point in k
acquisitions is 0 (Kampes et al., 2006), the atmospheric noise
would also be reduced by this method. The descending pair is
not included in the accumulated subsidence map because the
descending image may measure different scattering objects to
the ascending image for the same pixel. Hence the deformation
measured from the descending pair may not be consistent with
the ascending pair if their deformation values are accumulated.
Horizontal deformation which causes inconsistencies between
ascending pair and descending pair is another issue which needs
to be considered.
Figure 11. Accumulated subsidence of all subsidence maps for
the period 29 Jun 2007 ~ 14 Feb 2008 (230 days).
5. CONCLUDING REMARKS
This study illustrated the capability of ALOS PALSAR for
mine subsidence monitoring in Australia. Simulations have
shown that the new satellites ALOS, TerraSAR-X and
COSMO-SkyMed perform much better than the satellites
launched before 2006 for this monitoring application.
Differential interferograms from ALOS PALSAR and
ENVISAT ASAR images with similar temporal coverage were
generated. Strong phase discontinuities and decorrelation have
been observed in almost all ENVISAT interferograms, whereas
these issues are almost invisible in ALOS PALSAR
interferograms due to its better spatial resolution and longer
wavelength. Six successive subsidence maps derived from
eight ALOS PALSAR images using both ascending and
descending passes were obtained. More than 50cm subsidence
has been found in the Westcliff Mine over 46 days. The
DlnSAR results derived from ALOS PALSAR data were
validated with ground survey data at both mine sites. RMSE of
1.7cm and 0.6cm has been found in the Appin and Westcliff
mine areas respectively. This study demonstrated an easy to
implement approach to calculating the accumulated subsidence
from a series of SAR images by resampling a series of SAR
images into a reference master. This approach could minimise
geocoding error between each DlnSAR result and the error due
to accumulating the results over several DlnSAR results.
ACKNOWLEDGEMENTS
This research work has been supported by the Cooperative
Research Centre for Spatial Information through Project 4.09,
whose activities are funded by the Australian Commonwealth’s
Cooperative Research Centres Programme. The Australian
Research Council has been supporting DlnSAR research at
UNSW over a number of years. The Australian Coal
Association Research Program has also supported research for
ground subsidence monitoring using DlnSAR. The authors wish
to thank the European Space Agency and the Earth Remote
Sensing Data Analysis Center (ERSDAC) for providing the
ENVISAT ASAR and ALOS PALSAR data, respectively.
METI and JAXA retain ownership of the ALOS PALSAR
original data. The PALSAR L-l.l products were produced and
distributed to the IAG Consortium for Mining Subsidence
Monitoring. The authors also wish to thank BHP-Billiton for
providing the ground survey data and other spatial data.