Abstract:

The knowledge of the surface soil moisture content can be very helpful for retrieving the spatialtemporal distribution of waterlogging in agriculture fields. According to the characteristics of ASAR GM data, this paper retrieved surface soil moisture over the cotton fields using 79 ASAR GM images data from 2007-2011 during cotton growing seasons, the auxiliary parameters were calculated using MODIS data, the main methods include the follows: we obtained spatial distribution of landuse classification using crop time series characteristics and MODIS data, corrected the matrix pixels data of  backscattering coefficient  using the landuse classification data, and separated backscattering coefficient influenced by soil and vegetation using the semiempirical watercloud model, the parameters of which were calculated by ASAR GM data under water saturation state using nonlinear statistic mode and the vegetation water content in these methods came from NDVI data calculated from MODIS data, the finally corrected soil  backscattering coefficient was used to calculated soil surface moisture by ASAR GM timeseries data. The advantage of our approach is that no auxiliary data is needed.By comparing the method value and measured data in the cotton field in Sihu area, the results indicated that this method is correct (R2=0779 n=25), the estimation precision reaches 963% in root mean square error