The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
79 
soil moisture and ASAR backscattering, and soil moisture and 
PALSAR backscattering is compared. While processing the 
SAR data, the resolution of the images was resampled to 8 m 
for RADARSAT-1 and PALSAR data and to 30m for ASAR 
data. SAR data has different resolutions. The resolution of 
RADARSAT-1 and PALSAR data is three times better than the 
ASAR data. There is a pretty high correlation (R 2 = 0.86) 
between the soil moisture content and the PALSAR 
backscattering, which is the best among all the SAR images 
(Figure 4a). RADARSAT-1 gives better result (R 2 = 0.81) than 
ASAR (Figure 4b). ASAR is the worse (R 2 = 0.76) among the 
all (Figure 4c). This result is related not only with soil moisture 
content but also with soil texture. In addition, due to the fact 
that PALSAR has the biggest wavelength causing to penetrate 
deeper, gives higher correlation with the moisture content of the 
soil. The significance of linear association was tested for all 
SAR backscattering results from different satellites using 
Fisher’s F test for a = 0.05 significance level, and all were 
found significant (for the PALSAR F=431,5706952 and 
significance F=2,09369E-31, for the RADARSAT 
F=380,7293985 , significance F=2,81845E-34, for the ASAR 
F=244,5656022, significance F=l,07252E-24). 
In investigating the soil moisture change, the spatial resolutions 
of the each C band SAR data affect the average soil moisture 
value of the represented area. However, the polarisation does 
not affect the result significantly since both RADARAT-1 (HH 
polarised) and ASAR (VV polarised) give a good (i.e. 
acceptable) correlation with the soil moisture. With regard to 
the band difference; despite the resolutions of both images were 
the same, PALSAR (L) band gave better correlations than that 
of RADARSAT-1 (C band) for the same soil characters. 
Comparing the graphs, linear association from PALSAR 
analysis is about 5 % better than RADARSAT-1 analysis. It is 
also better than ENVISAT analysis by about 10 %. 
ASAR (C Band - W| 08 June 06 a 
Backscattering ln dB (cT°) 
RADARSAT (C Band-HH) 28 May 06 fc> 
Backscattering in dB (O 0 ) 
PALSAR (L Band-HHj -10 June 06 C 
Figure 4. Variation of backscattering coefficient with 
gravimetric soil moisture a) for ASAR b) for RADARSAT-1 
and c) for PALSAR 
6. CONCLUSIONS 
In this study the potential of RADARSAT, ASAR, and 
PALSAR data was investigated for estimating soil moistures 
over bare soils in Menemen Plane of Western Turkey. 
RADARSAT, ASAR and PALSAR images are collected on 28 
May 2006, 8 June 2006 and 10 May 2006 respectively. In most 
of the studies comparisons were made between the multi 
polarisations or multi incidence angles of the same sensor or 
comparisons made between the ASRAR and RADARSAT-1 
data. In this study, the estimates of soil moisture obtained from 
the SAR data of three different satellites for HH and VV 
polarisations and for C and L bands are compared to find the 
best sensor for measuring the bare soil moisture in agricultural 
areas as in Menemen Plain. 
It has been found out that for the bare soils having a relief of 
less than 1% and having no stoniness, the correlations between 
the soil moisture content and backscattering of ASAR, 
RADARSAT-l,and PALSAR images were 76%, 81% and 86% 
respectively. The RADARSAT-1 Fine Beam image has the 
same resolution (6.25m x 6.25m) with the resolution of 
PALSAR image (6.25m x 6.25m). Although they both were 
resampled to 8m, PALSAR gave better correlation than 
RADARSAT-1 image. Although the resolution of 
RADARSAT-1 and PALSAR images is far higher than that of 
the ASAR image (30mx30m), the significance of the results 
produced is almost similar in such a flat area. Despite the 
spatial resolution difference and polarization differences of 
RADARSAT-1 and ASAR images (8m-HH versus 30m-VV), 
the estimated soil moistures show high correlation with 
backscatter values for the both image types. From the point of 
view of monitoring and mapping the soil moisture content of 
agricultural fields; for the areas having larger fields, both SAR 
images can be utilized almost equivalently whereas for the 
areas having smaller fields RADARSAT-1 image gives better 
results. Regarding to the band difference, RADARSAT-1 (C 
band) and PALSAR (L band) images having the same 
resolution are compared, and as expected PALSAR data gave % 
5 better estimation than the RADARSAT-1 data. This means L 
band resulted in the best correlation between the ground soil 
moisture and the estimated soil moisture. 
Baghdadi et al. (2006) found out in their study that ASAR 
sensor does not seem to offer any advantage compared to the 
mono- polarization and multi incidence RADARSAT -1 sensors. 
They studied HH and HV polarizations for different incidence 
angles and recommended to study VV polarisation to see the 
potential of ASAR versus RADARSAT in estimating soil 
moisture. In this study it has been revealed that VV polarisation 
of ASAR sensor does not prove any better to RADARSAT-1 
sensor. If the price differences per scene are taken in to account, 
one should consider purchasing ASAR (VV) for the vast 
acreages. In this sense, 5% difference in R 2 values of ASAR 
and RADARSAT-1 correlations do not show any significance. 
Among all the sensors, the PALSAR is the most cost effective 
data and gives the best moisture estimation in bare soil. For the 
soils having the same characteristics as with the Menemen Plain, 
PALSAR images can be preferred for moisture estimations. 
This study revealed that the PALSAR which is designed to