Research On The Inversion Ofparameters And Microwave Scattering Characteristics Of Winter Wheat

Wheat is the main food for China and the world, wheat occupies the secondposition in China’s grain crop. Therefore, it is very important to estimate the growth areaof wheat, monitor growth potential (especially the important phonologicalperiod),evaluate overall yield. So far, it has made great achievements on using remote sensingtechnology to monitor crops real-time, rapidly and long-term. Optical remote sensinghas applied earlier than microwave remote sensing, and has achieved some results.Compared with microwave remote sensing image, optical remote sensing dataareobtained more easily, which makes the optical remote sensing is superior to microwaveremote sensing in a certain extent. But the optical remote sensing is easily affected byweather, so that optical remote sensing can not monitor the growth of vegetationcontinuous accurately. Microwave remote sensing has the characteristics of all-weather,all-day, and has a certain ability to penetrate through the vegetation, compensate for thedeficiencies in this regard of optical remote sensing, so microwave remote sensing hasbeen developed and applied.In order to apply microwave remote sensing technique to monitor wheat growtheffectively, it has had to studyand master the mechanism of microwave scattering fully,otherwise it is very difficult to interpret its backscattering characteristics. This paperanalyzes the backscattering properties of wheat comprehensively based on theapplication of microwave remote sensing technique.The main contents of this paper include the analysis of the law of wheatbackscattering coefficient, the summary of backscattering characteristic of wheat andthe inversion of surface parameters. First of all, wheat backscattering coefficient wasmeasured by the ground-based measurements, at the same time, surface parameters(vegetation parameters, soil parameters and other related parameters) were real-timecollected. Based on the multi-band (L, S, C, X), multi-polarization (HH, VV, VH, HV)scattering data, this paper summarizes the change law of scattering coefficient with thechanges of incident angle, azimuth angle, wave frequency, wave polarization and thephase. Secondly, the empirical formula of soil parameters and vegetation parameters is established, and analyzes the correlation between C-band backscattering coefficient andsoil water content, biomass.Semi-empirical model of co-polarization (HH, VV)combining biomass and LAI is established, which has high accuracy applied to the SAR(Synthetic Aperture Radar) image data. In conclusion, C-band radar data has a goodpotential for monitoring wheat growth status. Finally, using the simplified MIMICSmodel simulate the wheat backscattering coefficient, comparing the simulated data withmeasured data, it is found that the simplified MIMICS model can better simulatewheatbackscattering coefficient, especially in the S-band.