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

机译:使用Radarsat-2和Terrasar-X数据,在早期玉米覆盖区域进行土壤水分检索

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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:本研究的主要目的是使用SAR(合成孔径雷达)和用于早期玉米覆盖区域的光学卫星数据进行半经验土壤水分检索方法。首先,采用水云模型来消除植被冠层的效果,从而获得与土壤水分相关的裸土反应系数。然后,对土壤湿度估计的未确定系统,校准的整体方程模型具有两个土壤表面参数,与雷达拉特-2和Terrasar-X数据相结合构建土壤湿度检索方案。最后,可以通过最小化综合成本函数来源的土壤水分。基于2015年6月15日在农业领域获得的现场测量和多传感器SAR数据,实施了发达方法的定量评估。结果表明,通过在玉米覆盖区域上发达的方法获得了准确的土壤水分。估计结果的根均方误差小于0.05厘米 3 /厘米 3 并且确定系数大于0.7。

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