Soil water saturation condition is an essential factor that indicates the possible temporal and spatial hazard of inundations
in floodplains. To monitor wetness conditions over a long period of time and large areas, passive microwave data is used
to study the inundation pattern of large floodplains in Asia, such as the Poyang Lake floodplain. The polarization
difference brightness temperature at 37GHz is sensitive to the water extension even under dense forest. However, the
mixing of signals from open water, bare soil and vegetation makes it difficult to obtain the soil-water saturation
conditions from 37GHz data. That is because 37GHz microwave emission is attenuated by the vegetation canopy, which
shows seasonal changes in Asia floodplains. We developed a linear mixing model to eliminate the signal from vegetation
and derive the soil- water saturation condition from 37GHz data. Vegetation attenuation factors, in terms of vegetation
fractional area and LAI, have been estimated by correlation with the NDVI. Thus the vegetation attenuation function is
built according to the relationship between 37GHz and NDVI data of agricultural areas, with the help of Harmonic
analysis of time series to obtain continuous NDVI time series. Comparing the soil-water saturated area from 37GHz and
water extension area of Poyang Lake from SAR image data at higher spatial resolution, our result shows a good fit with
SAR data but relatively higher values.
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