MODIS and AMSR-E sensors with 23 images of MOD13A2 for each year, 75 images of MOD11A1 for the year 2007, 87 for the year 2010 were used in this study.
To transform data in same spatial resolution AMSR-E soil moisture data was spatially interpolated to 12.
AMSR-E soil moisture was converted to vector points to interpolate the in-between values.
These values were extracted from both MODIS derived Soil Moisture Index and AMSR-E soil moisture spatially interpolated data.
The values of AMSR-E soil moisture are found to be in agreement with the rain data.
For instance, the GLDAS outputs can be evaluated against the large and medium networks; SM products retrieved from AMSR-E, SMOS, ASCAT, and SMAP can be evaluated against the medium network data; and the SM product from SMAP active signals can be compared with the small network data.
Figure 6 shows an example of comparing four SM products derived from AMSR-E ascending and descending signals with the upscaled SM in the large network.
Chan, 2006: Vegetation and surface roughness effects on AMSR-E land observations.
Ishikawa, 2007: Auto-calibration system developed to assimilate AMSR-E data into a land surface model for estimating soil moisture and the surface energy budget.