is lower than that for trees even the area is fully covered 
by vegetation. The variation for SWI is considered to be 
caused by the difference of surface roughness, which is 
one of the dominant factors affecting SAR backscatter. 
3.SEASONAL CHANGES OF SAR BACKSCATTER 
IN PADDY FIELD 
The authors studied the actual changing patterns of SAR 
backscatter concerning to the change of land cover 
conditions in the paddy field at the same test site as Fig. 1. 
The flow of data analysis is shown in Fig.5. The three 
temporal SAR data in Fig.1 were co-registered each other 
and a MAP filter was applied in order to remove speckle 
noise. After principal component analysis was performed 
to the three SAR images, clustering was adopted as 
non-supervised classification method to obtain land cover 
classification image at the test site. As the result of 
clustering, total eight land cover classes were obtained. 
The land cover classification image is shown in Fig.6 
The graph in Fig.7 shows the changing patterns of NRCS 
derived from the SAR standard product by NASDA for 
eight land cover classes obtained by above analysis. 
The solid lines (C2, C3, C4, and C6) in the graph 
correspond to the patterns of paddy fields. The change 
of C4 and C6 between March and September was proved 
to be caused by the difference between bare soil condition 
and the rice growth from the ground survey. The change 
of C2 was considered due to the planting of second rice in 
the dry season. The change of C3 between March and 
April was estimated due to the change of soil moisture 
according to the result of regression analysis described in 
the previous section. Natural levee which distributes 
widely in the test site was easily identified as the class C8, 
which always resulted in high backscatter. 
As described above, in even L-band SAR images, much 
information about the seasonal changes of paddy and soil 
condition can be extracted from multitemporal data. 
These results seem to suggest the capability of JERS-1 
SAR data for actual monitoring of land cover conditions in 
tropical regions. 
4.CHANGES OF SAR BACKSCATTER 
BY FLOODING 
The authors studied the change of SAR backscatter in 
paddy fields when they were flooded. Fig.8 shows two 
SAR images observed in the rainy season in 1993 and 
684 
1995. The right image shows the SAR image taken on 
September 26th, 1995 when a big flood occurred in the 
Central Plain of Thailand. This image can be compared 
with the left image, which was taken almost in the same 
rainy season but in non-flood condition. 
According to a ground survey at the same time of SAR 
observation in 1995, the SAR data were proved to result 
in very low backscatter in the flooded areas as shown in 
Fig.9. Therefore, the flooded areas in the paddy fields 
were extracted by subtracting NRCS values from those of 
the data in non-flooded conditions, namely the data in 
September, 1993. According to all weather character- 
istics of SAR, the SAR data are considered to be effective 
data source for the detection of flood in the rainy season. 
5.CONCLUSION 
Regression analysis using JERS-1 SAR and Landsat TM 
data acquired on the same day suggested that the change 
of L-band SAR backscatter is related to the change of soil 
moisture and vegetation coverage conditions with 
positive correlation. Case studies concerning to the 
change of land cover in paddy fields by seasonal variation 
and flooding proved that these changes can be detected 
as the change of L-band SAR backscatter. Therefore 
the result of these case studies indicates the effectiveness 
of L-band SAR data by JERS-1 for the monitoring of 
several types of changes of land cover conditions in 
tropical regions, where data acquisition is necessary even 
in bad weather conditions of the rainy season. 
This study was conducted as the joint research between 
RESTEC and NRCT and also supported by the Special 
Coordination Fund of the Science and Technology 
Agency of Japan. 
REFERENCES 
Takeuchi,S. and R. Suwanwerakamtorn, 1995a. Analysis 
of the Influence of Land Cover Conditions on SAR 
Backscatter Using Simultaneous SAR and TM Data. 
J. of JSPRS, vol. 34, no. 5, pp.45-48. 
Takeuchi,S. and R. Suwanwerakamtorn, 1995b. Land 
Cover Change Analysis Using Multitemporal SAR Data 
- A Case Study in the Central Plain of Thailand -. 
Proceedings of the 19th Japanese Conference on 
Remote Sensing, pp.113-114. 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B7. Vienna 1996