! 2004
(13)
ig. Eq.
(14)
s than
its
maller
tive to
(13)).
SAR
cy for
vel of
results
sives a
| noise
tive to
ir, a 1-
12,800
ye seek
require
n Nov.
region,
26°N 1
/ China
quake,
‘mation
(UTC),
" 35km,
90's in
je and
is very
China's
ate the
icement
ferential
' east to
northern
Ike. The
)km and
Remote
by less
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
disturbance, distinct and clear tectonic evidence because there
exists scare vegetation, uncovered surface, and dry atmospheric
condition, and desolate and uninhabited around the area. For
these potential advantages, this area has become the optimal
region for using remote images to detect and investigate
geological movement such as tectonics, fault, earthquake et al.
Jianhua Li (1998) analyzed 1:100 0000 Landsat satellite images
and recognized the Mani earthquake as active evidence of the
Margaichace-Ruolacuo fault. On the remote sensing images, a
series of valleys were distorted consistently along the
Margaichace-Ruolacuo fault, evidently showing the fault
features slipping along its trend. Around the Margaichace-
Ruolacuo fault zone, linear fault reticule features are distinct
and clear, evidently showing the appearance of left-lateral
slipping movement. Measurement results have been reported
that the maximum left-slip displacement of the first-level water
system reaches 3500m (Li Jianhua, 1998).
The data set related to our study area are ERS1/2 SLC SAR
images (April 15, April 16, 1996 ERS-1 and Dec. 2, 1997 ERS-
2) provided by European Space Agency. There are two scenes
for each imaging date, so there are six scenes in total for data
processing related to the study.
3.2 Methods of Surface Deformation Mapping
The data processing procedure of differential SAR
interferometry can be divided into two big steps. Firstly,
performing registration between the two focusing SAR images
acquired before and after surface deformation, then conjugating
to generate the prime interferogram; Secondly, from the prime
interferogram subtracting the unprimed interferogram generated
from SAR images acquired before surface deformation or
simulated interferogram generated from existing DEM, thus
surface deformation interferogram is obtained.
The software for data processing in this study mainly related to
using the EarthView Interferometric SAR Processor of Atlantis
Scientific Inc. Canada. This processing software allows for the
user feedback rectification of the parameters influencing
resultant interferogram, and can meet the geoscientist’s need for
various geo-applications of SAR interferometry. The epicenter
of Mani is just located between the two scenes of ERS image
Frame 2889 and Frame 2907. So it is required to manipulate
two set of SAR images, and then mosaic the two resultant
interferogram.
The basic steps of InSAR data processing in our study can be
presented as follows:
(1) Using the ERS-1 image acquired on April 15, 1996 as slave
image and the ERS-2 image acquired on April 16, 1996 as
master image, which form a tandem pair, then extrácting the
DEM of the study area.
(2) Using the ERS-2 image acquired on Dec. 2, 1997 as slave
image and the same image of April 16, 1996 as master image,
forming primed interferogram by multiplying each complex
pixel in master image by the complex conjugate of the matching
pixel in the slave image.
(3) Using the DEM generated from the first step, and the
baseline parameters of the second processing step, generating
the unprimed simulating interferogram.
733
(4) Finally, subtracting the unprimed interferogram from the
primed interferogram, then obtaining differential deformation
interferogram along slant range.
There are some data processing steps that are either done
differently here than in previous studies or should be elaborated
upon for the sake of explaining the resolution and interpretation
of our results. These include re-estimation of baselines from
twenty GCPs collected from 1:10,0000 topographic map in
order to improve the accuracy of DEM extraction (Kimura H,
1997), and flat phase removal method. The flat earth correction
method using the EarthView Software removes those fringes
due to earth curvature and imaging geometry reference to sea
level. So this method leads to evidently residual phase gradient
on the interferogram because the average altitude of study area
is 5000m. In order to avoid evident errors in DEM and surface
deformation information extraction, the residual phase gradient
must be removed (Goldstein R. M, Zebker H. A, 1988). As to
the topographic interfergram, the flat region in study area was
selected to estimate the residual phase gradient. After removing
the residual phase gradient, the topographic interferogram was
unwrapped and then derived DEM, which RMS is 18.7m with
comparison to 1:100 000 topographic map. For the deformation
detection interferogram, the region far away from epicenter and
with regular fringes was selected to estimate the residual phase
gradient and then removed, where impossibly exist surface
displacement.
Finally, the two resultant surface deformation detecting
interferograms were mosaicked with the match errors within
half of fringe (see Figure 2). From the mosaic interferogram, we
can infer that the fringe errors of surface deformation detecting
interferogram in this study, which derived from errors of
topography and flat phase gradient, also lie within the level of
accuracy.
3.3 Deformation Differential
Interferogram
Analysis Based on
The effects influencing interferometric data decorrelation,
reported by Zebker (Zebker H. A. and Villasenor J, 1992), can
be mainly attributed to these four factors: 1) baseline
decorrelation; 2) additive —noise/spcekle; 3) temporal
decorrelation for random phase component due to the
complicated interference pattern produced by radar signal
interaction with multiple ground scatterers within an image
resolution element; 4) geometric decorrelation. In this study, we
analyzed these factors related to the surface deformation
detecting interferogram along the Margaichace-Ruolacuo fault,
combining with the regional environmental conditions.
The derived deformation detecting interferogram show several
areas of fringe disturbance (Figure 2), and the areas other than
the area around Margaichace-Ruolacuo fault mostly are
associated with lakes. Because the lake water is characteristic of
seasonal variation, we inferred that the fringe disturbance
associated with lakes arca sound reasonable for lake-water
backscattering decorrelation. This deformation could be either
earthquake related or indicate a seasonal change of the lake-
water between spring and summer.
One of the most significant sources of error in InSAR
processing is that of phase noise. Atmospheric disturbances,
thermal noise, baseline effects on correlation cause phase noise.
We can essentially ignore the former in this area because of the
intense dryness of the atmosphere. The second, thermal noise, is
