Performance of Conditional Merging Spatial Interpolation Technique Combining AMSR-E Soil Moisture and In-Situ Soil Moisture Data Over the Korean Peninsula

Abstract

This study compared to spatial interpolation methods (ordinary Kriging and conditional Merging) for predicting soil moisture content at ungauged locations in Korea. For the analysis, the soil moisture data retrieved from Advanced Microwave Scanning Radiometer-Earth observing system (AMSR-E) and 24 gauges of hourly in-situ data sets from the Rural Development Administration(RDA) of Korea were used. In order to verify interpolation performance, leave-one-out crossvalidation method was used. The method of conditional merging (CM) showed better performance than the method of ordinary Kriging (OK) at the 9 among total 24 gauges analyzed. From the temporal view point, the method of CM produced better soil moisture map over Korean Peninsula than OK did for the 68 days out of total 113 days considered for the analysis. The method of CM showed better performance on the western side of Korean peninsula due to high spatial gauge density. Overall, the result of this study indicates that the performance of spatial interpolation of the in-situ soil moisture data can be improved by adding the information regarding the spatial characteristics acquired from the satellite soil moisture data.