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Soil Moisture Retrieval Over Early Corn Covered Area Using Radarsat-2 and Terrasar-X Data

机译:利用Radarsat-2和Terrasar-X数据反演早期玉米覆盖区的土壤水分

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The main objective of this study is to develop a semi-empirical soil moisture retrieval approach using SAR (Synthetic Aperture Radar) and optical satellite data for early corn covered areas. Firstly, the water cloud model was employed to eliminate the effects of vegetation canopy, thus to obtain the bare soil backscatter coefficient associated with soil moisture. Then, against the underdetermined system for soil moisture estimation, the calibrated integral equation model with two soil surface parameters was integrated to construct soil moisture retrieval scheme in combination with Radarsat-2 and TerraSAR-X data. At last, soil moisture can be derived by the minimization of the comprehensive cost function. Based on the field measurements and multi-sensor SAR data acquired on 15 June 2015 over agricultural area, quantitative evaluation of the developed approach was implemented. The results indicate that accurate soil moisture was obtained by the developed approach over the corn covered areas. The root mean square error of the estimated results are less than 0.05 cm3/cm3, and determination coefficients are greater than 0.7.
机译:这项研究的主要目的是利用SAR(合成孔径雷达)和光学卫星数据为玉米早期覆盖地区开发一种半经验的土壤水分反演方法。首先,利用水云模型消除植被冠层的影响,从而获得与土壤水分相关的裸土后向散射系数。然后,针对欠定的土壤水分估算系统,结合Radarsat-2和TerraSAR-X数据,整合了具有两个土壤表面参数的校准积分方程模型,以构建土壤水分检索方案。最后,通过最小化综合成本函数可以得出土壤水分。基于2015年6月15日在农业地区获得的现场测量结果和多传感器SAR数据,对该开发方法进行了定量评估。结果表明,通过开发的方法可以在玉米覆盖地区获得准确的土壤水分。估计结果的均方根误差小于0.05 cm 3 /厘米 3 ,并且确定系数大于0.7。

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