基于星载SAR的冬小麦估产模型比较分析

旨在让农业部门等提前预知小麦产量，从而准确判断粮食生产形式，制订相关政策。应用2014年4月中旬和5月初星载合成孔径雷达(SAR)——RADARSAT-2各一幅，选择安徽省寿县和怀远县冬小麦产区，通过试验田产量和反演的雷达影像后向散射系数，建立冬小麦线性估产模型，在此基础上对2013和2014年估产模型精度进行比较。结果表明：通过星载SAR的同极化HH和交叉极化HV方式建立的估产模型对寿县涧沟镇冬小麦估产精度分别为68.37%和74.01%，对怀远县龙亢镇冬小麦估产精度分别为63.10%和69.10%。特别是针对倒伏区域冬小麦估产模型精度差异进行理论详细分析，指出冬小麦大面积倒伏区域，基于交叉极化(HV)估产模型精度高于同极化(HH)估产模型精度。最后指出将来可选择四极化SAR影像，针对不同的生长方式有针对性的选择不同极化方式进行估产。模型结果分析结论为将来冬小麦估产模型参数纠正及推广奠定基础和积累经验。

Comparative Analysis of Winter Wheat Yield Estimation Model Based on SAR

The study aims to inform agriculture administrators of winter wheat yield in advance, thus formulate food production form and relevant policy. Experimental fields of winter wheat yield data in May before harvest, and the synthetic aperture radar(SAR) double polarized—RDARSAT-2 that were photographed in April and May in Shouxian and Huaiyuan County in Huaihe River Region were adopted for winter wheat yield estimating. The liner yield estimating models were established by adopting backscattering coefficient and experimental fields yield. Then precision of yield estimating models of 2013 and 2014 were compared. Yield estimating models established by co-polarized (HH) and cross-polarized (HV) were adopted for winter yield estimating in Shouxian County, their precision were 68.37% and 74.01%, respectively, and their precision were 63.10% and 69.10% in Huaiyuan County, respectively. Yield difference of winter wheat in the lodging region was analyzed in detail. The precision of yield estimating model based on cross-polarized (HV) was higher than that based on co-polarized (HH). Finally, the four polarized SAR image would be chosen for yield estimating according to different winter wheat growth patterns. The results of this model analysis could form the research base and gather experience for parameter correction and popularizing of winter wheat yield models.