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MONITORING OF LAND COVER CONDITIONS IN PADDY FIELDS 
USING MULTITEMPORAL SAR DATA 
Shoji Takeuchi*, Mitsunori Yoshimura* and Rasamee Suwanwerakamtorn** 
* Remote Sensing Technology Center of Japan (RESTEC) 
** National Research Council of Thailand (NRCT) 
ABSTRACT: The synthetic aperture radar (SAR) data by the Japanese Earth Resources Satellite 1, JERS-1, are 
expected to be used effectively for the purpose of monitoring of land cover conditions in tropical regions since the SAR 
The authors conducted case studies for monitoring of land 
cover conditions in the paddy fields in Thailand using multitemporal JERS-1 SAR data. Two case studies concerning to 
the change of land cover by seasonal variation and flooding proved that these changes can be detected as the change of 
L-band SAR backscatter. 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 
data can be obtained repetitively in any weather condition. 
necessary even in bad weather conditions of the rainy season. 
KEY WORDS: SAR, Multitemporal Data, Backscatter, Soil Moisture, Vegetation Coverage, SWI, PVI, Flood. 
1.INTRODUCTION 
Land cover change monitoring using multitemporal data 
is one of the important and practical applications in 
remote sensing fields. However, the observations by 
conventional optical sensors are much affected by 
weather conditions. Especially in tropical regions, 
observation in rainy season has been almost impossible 
using optical sensors. On the other hand, the Synthetic 
Aperture Radar (SAR) can observe in any weather 
condition and the SAR data can be used practically to 
monitor land cover changes which occur in the season of 
bad weather conditions like the rainy season. The 
authors studied the applicability of the SAR data by the 
Japanese Earth Resources Satellite 1, JERS-1, for the 
monitoring of the land cover change in paddy fields at a 
test site of the Central Plain of Thailand. 
2.RELATION BETWEEN SAR BACKSCATTER 
CHANGE AND LAND COVER CONDITIONS 
The authors have conducted the preliminary analysis of 
the multitemporal JERS-1 SAR data taken in 1993 at the 
test site of Thailand and the result suggests that those 
data contain much information about the seasonal 
variations in SAR backscatter for various land cover types. 
Three images in Fig.1 show seasonal changes of L-band 
SAR backscatter among the middie of dry season (March 
16th) , the end of dry season (April 29th) and rainy 
Season (September 8th). The change of SAR 
backscatter is represented by the Normalized Radar 
Cross Section (NRCS) which can be derived from the 
SAR level 2.1 product using the calibration coefficient 
given by NASDA. 
683 
For the purpose to investigate the physical meanings of 
the SAR backscatter change, regression analysis was 
performed between SAR backscattering intensity and two 
parameters for representing land cover conditions, Soil 
Wetness Index (SWI) and Perpendicular Vegetation Index 
(PVI) using JERS-1 SAR and Landsat TM images 
acquired on the same day (April 29th, 1993). These 
parameters can be estimated in the two dimensional 
plane composed by the intensity of TM band 3 (visible- 
red) and band 4 (near infrared) as shown in Fig.2 . The 
SWI is defined as the regression line derived from points 
regression of bare soils and indicates the degree of soil 
moisture content. The PVI is defined as the line 
perpendicular to the SWI line and indicates the degree of 
vegetation coverage. The maximum value of PVI 
corresponds to the averaged value of PVI for the areas 
fully covered by vegetation. 
The two images were co-registered each other and twenty 
pairs of the averaged values in 5 x 5 window areas for 
SAR and TM images which were sampled from the bare 
soil areas and the vegetated areas were used for the 
regression respectively. Fig.3 and 4 show the results 
from the regression analysis between SAR-NRCS and 
SWI and between SAR-NRCS and PVI respectively. 
The results indicate positive correlation for both of the 
relations between SAR backscatter and soil moisture and 
between that and vegetation coverage, although the 
correlation coefficients are moderate values. There are 
seen relatively large variations of NRCS for large PVI 
samples and for dry bare soil samples, which are the 
factors decreasing correlation coefficients. The variation 
for PVI is considered to be caused by the differences of 
vegetation types, that is, the SAR backscatter for grasses 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B7. Vienna 1996