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结合主动微波遥感和被动光学遥感反映地表植被的各自优势,发展了一种主被动遥感协同估算干旱区草原植被生物量的模型。该模型将植被覆盖度作为水云模型的附加参数,将总体散射分为植被覆盖区散射和裸土区散射两部分,将水云模型应用到了植被覆盖稀疏区域。利用改进的水云模型和双极化ASAR数据,通过建立方程组估算植被生物量。将该方法用于乌图美仁草原植被生物量的估算,验证了该方法的有效性。结果表明:该主被动遥感协同估算模型能够成功地估算干旱区草原植被生物量,并且取得了较好的估算精度(R2=0.8562,RMSE=0.1813kg/m2)。最后,分析了该方法估算植被生物量的误差来源。
Combining the respective advantages of active microwave remote sensing and passive optical remote sensing to reflect the surface vegetation, a model of active and passive remote sensing to evaluate the vegetation biomass in arid area is developed. The model uses the vegetation coverage as an additional parameter of the water cloud model. The overall scattering is divided into two parts: the scattering of the vegetation cover and the scattering of bare soil area. The cloud model is applied to the sparse vegetation coverage area. Using improved water cloud model and dual-polarized ASAR data, vegetation biomass is estimated by establishing equations. The method was applied to estimate the biomass of vegetation in Uturathan grassland, which validated the validity of the method. The results show that this model can successfully estimate the biomass of grassland vegetation in arid area and obtain good estimation precision (R2 = 0.8562, RMSE = 0.1813kg / m2). Finally, the source of error of estimating vegetation biomass by this method is analyzed.