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土壤湿度是农作物估产和旱情监测的关键参量。目前常用的土壤湿度反演模型都建立在随机粗糙地表条件下,对周期性垄行结构的土壤并不适用。基于RADARSAT-2全极化数据和野外实测数据,分析了交叉极化(vh)后向散射系数对垄行方位角无明显响应;同极化(hh,vv)对方位角的响应为余弦函数,但在方位角为90o±2o位置易出现偏离曲线的异常高亮度值。通过雷达影像上采样点的实测值和Oh模型推算的理论值,拟合得到周期性地表和随机地表之间的误差函数,进而对同极化影像进行纠正。纠正后的同极化比(p)去除了方位角和异常值的影响,交叉极化比(q)受到异常值的影响。通过Oh模型中的p和vh对研究区的地表参数进行反演,17个检验点的验证结果表明,预测的土壤湿度平均相对误差为11.13%,标准差为0.0256cm3/cm3;预测的均方根高度平均相对误差为13%,标准差为0.1315cm。结果与随机粗糙地表土壤湿度和均方根高度的反演精度相当,证明了该模型的有效性。
Soil moisture is a key parameter for crop assessment and drought monitoring. The commonly used models of soil moisture inversion are based on stochastic rough surface conditions and are not suitable for soil with periodic ridge structure. Based on RADARSAT-2 data and field measurements, it is analyzed that the cross-polarization (vh) backscattering coefficient has no obvious response to the azimuth of the ridge. The response of the same polarization (hh, vv) to the azimuth is the cosine function , But in the azimuth of 90o ± 2o position prone to abnormal curve of abnormal high brightness value. Through the measured values of the sampling points in the radar image and the theoretical values estimated by the Oh model, the error function between the periodic surface and the random surface is fitted to correct the same polarization image. Corrected co-polarization ratio (p) removes the effect of azimuth and outliers, and the cross-polarization ratio (q) is affected by outliers. The inversion of the surface parameters of the study area by p and vh in the Oh model shows that the average relative error of soil moisture is 11.13% and the standard deviation is 0.0256cm3 / cm3. The validation of the mean square The average relative root height error was 13% with a standard deviation of 0.1315 cm. The results are comparable with those of the random rough surface soil moisture and root mean square height, which proves the validity of the model.