This study applied conditional merging (CM) spatial interpolation technique to obtain the satellite and in-situ composite soil moisture data. For the analysis, 24 gages of hourly in-situ data sets from the Rural Development Administration (RDA) of Korea and the satellite soil moisture data retrieved from Advanced Microwave Scanning Radiometer-Earth observing system (AMSR-E) were used. In order to verify the performance of the CM method, leave-one-out cross validation was used. The cross validation result was spatially interpolated to figure out spatial correlation of the CM method. The results derived from this study are as follow: (1) The CM method produced better soil moisture map over Korean Peninsula than AMSR-E did for the over 100 days out of total 113 days considered for the analysis. (2) The method of CM showed high correlation with gage density and better performance on the western side of Korean peninsula due to high spatial gauge density. (3) The performance of CM is not affected by the non-rainy season unlike to AMSR-E data is. Overall, the result of this study indicates that the CM method can be applied for predicting soil moisture at ungaged locations.