Studies On Microwave Dielectric Behavior Of Moist Salt Soil And Its Effect On Backscattering Coefficients Extracted From Radar Image

Today, Soil salinization is a global crucial issue. An estimated 9.5 X 108hm2 of land are affected by salinity and sodicity. It occupies 7.26% of the earth's terrain. The total area of salt-affected land in China is 1.0X108hm2. The large scale application of improper irrigation techniques results in the salinization of large tracts of arable land. Soil degradation and salinization devastate vast farmlands, grasslands and forests, especially in arid and semi-arid regions. At present, there are about 1 billionhectares of salinized land in the world. Thus, the monitoring of salinity and the mapping of the extent of the salinized soils are high priorities.The objectives of this study were:1. to discover the relationship between the dielectric properties of soil and its salinity, and water content over a (0.2-20GHz) range of microwave frequencies by measuring the real and imaginary parts of the dielectric constants of the soil samples prepared in a laboratory with controlled moisture content and salinity;2. to prove the impact of the dielectric properties of moist salinized soils, especially the imagery parts, on backscattering coefficients recorded in a SAR image by comparing the complex dielectric constants and the salinity of soil samples collected in Jilantai Salt Lake with backscattering coefficients extracted from a RADARS AT image of the same region.The results show that:1. for dry salt soil, The frequency and the salinity of soils have little influence on dielectric constant of soil samples. For moist salt soil, the imaginary part ? has greater sensitivity to soil salinity in the frequency range of 0.2-6GHz.2. for moist salt soil, at C-band, when salinity of soil is 1.5% is about 0.5. AtL-band when salinity is >0.3% >0.5, salinity is >1% > 1. AtP-band, when salinity is >0.3% is >1. As a result, we can not omit the effectof salinity on complex dielectric constant of soil and backscattering coefficient extracted from radar image.3. Dobson semi-empirical mixing model was established for non-salt soil, it is not fit to moist salt soil. We added salinity factor into Dobson model based on the data of complex dielectric constant of moist salt soil samples. This improved mixing dielectric model yields an excellent fit to measured data.4. using improved Dobson model, we can regress the moisture content and salinityof soil from = (or Fresnel reflection coefficient) at P(or L)-band and C-band. The results of regress is well agreement with measurement.5. using known backscattering coefficient models, the results of analysis on moist salt soil show that salinity of soil has a good correlation with backscattering coefficient.6. soil samples collected in Jilantai Salt Lake were measurement using coaxingprobe technology. The results were compared with the or" backscatteringcoefficients extracted from a RADARSAT image (C-HH) that was acquired at same time with the soil sampling at the Jilantai Salt Lake area. We discovered thatthe correlation coefficient between or" extracted from the RADARSAT image and measured in the soil sample is 0.70, whereas the correlation coefficient of and is 0.27. The correlation coefficient between a" and the soil sample salinity is 0.69. This suggests that soil salinity has a significant contribution to the backscattering coefficient, a" recorded in a SAR image. Consequently, a SARimage can be a useful tool for monitoring soil salinity.