(28-Mar- 
gnificant 
ı beneath 
) retrieve 
ce fields, 
ted in to 
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the area. 
ed (high 
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NDVI as 
note that 
e 5) was 
| were in 
' color in 
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and the 
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1 though 
  
  
  
t-2000), 
tion (2) 
IAPRS & SIS, Vol.34, Part 7, "Resource and Environmental Monitoring", Hyderabad, India, 2002 
  
60.00 
50.00 
40.00 
30.00 
20.00 
10.00 
0.00 
-13.00 -8.00 -3.00 2.00 
Backscattering Coefficient(dB) 
ex 
= 
& 
= 
= 
e 
han 
= 
M 
= 
= 
= 
th 
  
  
  
Figure 4. Relation between SAR backscatter and soil moisture 
using RADARSAT extended low beam mode data 
  
Figure 5. Soil moisture map derived from Radarsat SAR, 
Extended Low beam mode data of 23-Mar-2000, showing three 
underlying conditions of rice fields( Red : saturated soil Cyan: 
high soil moisture, Yellow: fields with standing water). 
  
Figure 6. NDVI map derived from IRS-LISS-III image (31- 
Mar-2000), Showing three categories of rice fields - Yellow: 
Low NDVI, Cyan: Medium NDVI, Red: High NDVI (range 
from .38-.49) 
6. DISCUSSION 
Soil moisture status of rice fields well before maturity is a 
crucial input to plan suitable crop rotation practice to increase 
cropping intensity. The objective of this investigation was to 
analyze the feasibility of assessing soil moisture status of rice 
fields after full canopy coverage using SAR data. Rice is 
predominantly grown under wetland condition in India, where 
at least 5-10 cm standing water is maintained up to 50-60 days 
of transplantation. Hence, only after grain filling stage, one can 
attempt to assess the soil moisture status of the fields. This 
study showed that backscatter from low incidence angle was 
found sensitive to soil moisture status at this stage of the crop. 
Feasibility of distinguishing flooded fields from that of non- 
flooded fields also was demonstrated. 
7. CONCLUSIONS 
RADARSAT extended low beam SAR data has an incidence 
angle, which is more near to optimum for soil moisture studies 
so far available from space borne platforms. The analysis of 
extended low beam SAR data resulted strong correlation with 
soil moisture under rice crop cover. It was feasible to 
distinguish fields with standing water, saturated field condition 
and wet high moist condition when the crop had attained full 
vegetative cover. High incidence angle data (S6) resulted little 
or no variation under full vegetative crop cover, indicating 
saturation of backscatter. Though at present the study is limited 
to a qualitative estimation of soil moisture, there exist a strong 
possibility of deriving an inversion algorithm to estimate 
volumetric soil moisture range. It is necessary to model the 
canopy attenuation factor in addition to roughness factor to 
improve accuracy of soil moisture quantification. Efforts are 
underway to use steep and shallow angle data to quantify soil 
moisture using physical based semi-empirical models. The 
accuracy of such models is expected to meet the requirement of 
crop rotation and crop intensification analysis studies of rice 
regions. 
8. REFERENCES 
Beaudoin A, Le Toan T and Gwyn QH, 1990, SAR observation 
of the C-band backscatter variability due to multiscale 
geometry and soil moisture, JEEE Transactions on Geoscience 
and Remote Sensing, 28, pp. 886-895 
Choudhury, B. J. and R. E. Golus (1988). Estimating soil 
wetness using satellite data. /nt. J. Rem. Sens., 9, pp. 251-1257. 
Dobson, M.C. and Ulaby, F.T., 1981. Microwave backscatter 
dependence on soil roughness, soil moisture and soil texture: 
Part III soil tension, ZEEE Transactions on Geoscience and 
Remote Sensing, 19, pp. 51-61. : 
Lee J.S., 1986, Speckle suppression and analysis for synthetic 
aperture radar images. Optical Engineering, 25, pp. 636-643. 
Mohan, S., Mehta, N.S., Mehta, R.L., Patel, Parul, Rajak, D.R., 
Srivastava, H.S., DAS, D.K., Sharma, S., Saxena, C.M. and 
Sutrodhar, A.K., 1993. Soil Moisture estimation using ERS-i 
SAR data, Proc. Second ERS-1 Symposium. Hamburg, 9-14 
Oct. 1993, pp. 875-878 
Patel, Parul, Mohan, S., DAS, D.K., Sharma, S., Sutrodhar, 
A.K. and Khawas, B., Feb 2000. Evaluation of Multi-incidence 
angle Radarsat SAR data for soil moisture Estimation, Physical 
Methods for Soil characterization, Narosa Publishing House, 
New Delhi, India. 
RSI, 2000. Radarsat Illuminated- Your guide to products and 
services. RADARSAT International, Canada.