The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
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3. INPUT DATA 
ENVISAT and ALOS SAR imagery were tested using DInSAR 
for monitoring the ground deformation due to mining at the 
study area shown in Table 1. The spatial and temporal 
separations between the images of the interferometric pair are 
indicated as perpendicular baseline (Bperp) and temporal 
baseline (Btemp). 
Sensor 
Master 
(dd/mm/yyyy 
) 
Slave 
(dd/mm/yyyy 
) 
Bperp 
(m) 
Btemp 
(day) 
ALOS/ 
PALSAR 
14/6/2007* 
30/7/2007* 
515 
46 
30/7/2007* 
14/9/2007* 
143 
46 
15/12/2007** 
30/01/2008** 
351 
46 
ENVISAT 
/ASAR 
3/1/2008 
7/2/2008 
361 
35 
Tabled. Interferometric pairs tested using DInSAR for 
monitoring mine subsidence at the study area. Note: * and ** 
denote the ALOS data acquired in single and dual polarization 
mode, respectively. 
4. LIMITATIONS OF DINSAR MEASUREMENT 
Radar interferometry is the technique to measure geodetic 
information, e.g. elevation or height change, by exploiting the 
phase information of at least two images. The precision of the 
result depends on not only the wavelength of the microwave 
signals emitted by the SAR antenna, but also the geometry of 
interferometric pair. Shorter wavelengths are more sensitive to 
the height change of terrain than the longer wavelengths. 
However, the shorter wavelengths can be more influenced by 
vegetations. Geometry of interferometric pair determines the 
sensitivity of interferometric phases with respect to topography. 
After all, the precision of radar interferometry depends on how 
accurate the process is to convert the interferometric phases to 
height or height changes. The limitations of DInSAR 
measurement are discussed in the following subsections. 
4.1 Decorrelation 
The interferometric quality of an identical imaging pixel in two 
SAR images can be assessed by measuring the correlation 
between the pixels. The quantity of correlation, or the so-called 
coherence, can be considered as a direct measure for the 
similarity of the dielectric properties of the same imaging pixels 
between two SAR acquisitions. Decorrelation degrades the 
coherence between two SAR images and results phase noise. 
Decorrelation is site-specific. It depends upon local climate 
conditions, vegetation cover, complexity of the terrain 
(moderate v.s. hilly or mountainous), land use, etc. As a rule of 
thumb, decorrelation is more severe for the area having heavily 
vegetated cover, complex terrain or constantly changing climate 
conditions. Decorrelation can be classified into three main 
categories: spatial, temporal and volume decorrelation (Zebker 
and Villasenor, 1992). 
Spatial decorrelation is caused by the physical separation, or so- 
called perpendicular baseline, between the locations of the two 
SAR antennas. The maximum allowable baseline before the 
pixels get totally decorrelated is often referred to as the critical 
baseline (Zebker et al., 1994). The perpendicular baseline of the 
interferometric pair for DInSAR processing is therefore 
preferred to be as small as possible. 
Temporal decorrelation is caused by the variation of the 
dielectric properties of ground objects over time between two 
repeat-pass acquisitions. In repeat-pass interferometry the sub 
resolution properties of the imaged scatterers (sub-scatterers) 
may change between surveys, e.g. by meteorological 
differences at the time of image acquisitions, the movement of 
leaves and branches, water surface, or vegetation growth. 
Therefore, urban regions normally illustrate much higher 
coherence than vegetated/agricultural areas over a period of 
time. 
Volume decorrelation is also about the phase stability of the 
imaging cell (pixel) over time, especially over vegetated 
regions. The dielectric properties and alignments of tree leaves 
and branches in the canopy may result in the variation of the 
backscattered radar signals. They are also affected easily by the 
local weather conditions, such as rains and winds. Therefore, it 
is desirable to have a finer SAR imaging resolution in order to 
minimise the variation of the random scattering phases. 
The histograms of the coherence value of 4 selected 
interferometric pairs as given in Table 1 are shown in Figure 1. 
The mean coherence of the ALOS pair, 15/12/2007 - 
30/01/2008, illustrated higher value than other two ALOS pairs 
acquired in June, July and September in 2007. 
It is interesting to note that even the perpendicular baseline of 
the ALOS pair, 30/7/2007 - 14/9/2007, is 143m its coherence 
over the selected scene is not as good as expected. After 
comparing this coherence map to a high resolution optical 
image of the identical area, the areas showing low coherence 
value (<0.3) are actually farmlands. It suggests the local 
agriculture pattern may cause additional noise in the scene. 
Based on the coherence value shown in Figure 1, the 
decorrelation due to agriculture is more severe in summer (June 
- September) than winter (December - February). In addition, 
the ALOS data acquired on 15/12/2007 and 30/01/2008 are in 
single polarization mode, which has twice better imaging 
resolution than the images acquired in dual polarization mode. 
Therefore, the interferometric pairs with better imaging 
resolution will be less subject to volume decorrelation, hence 
high interferometric coherence value. 
The ENVISAT pair covers a similar period as the 3 rd ALOS 
pair. However, it has less mean coherence of 0.379. The 
decorrelation may be caused by the spatial decorrelation as the 
perpendicular baseline of this ENVISAT pair is about 361m. 
4.2 High phase gradient 
As mentioned earlier, the interferometric phase variation caused 
by land deformation is linearly depending on the height change 
of terrain. Therefore, a large vertical ground movement over a 
small spatial extent causes the rapid changes of phases in the 
differential interferogram. When the phase gradient gets too 
large, it becomes ambiguous and it is impossible to recover the 
height change accurately. The problem can be solved or 
reduced by having interferometric pairs with higher imaging 
resolution, signals with longer wavelength and/or a shorter site 
revisit cycle. This is demonstrated in Figure 2 by comparing the 
DInSAR results derived using ENVISAT (C-band, wavelength 
= 5.6cm) and ALOS (L-band, wavelength = 23.5cm) data.