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Fractional vegetation cover retrieval using multi-spatial resolution data and plant growth model

机译:使用多空间分辨率数据和植物生长模型进行部分植被覆盖度检索

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Fractional vegetation cover (FVC) is widely relevant for land surface process. In this paper, an algorithm is addressed on FVC retrieval, with the combination of MODIS and Huan Jing satellite (HJ), which is a newly launched constellation by China. In the developed model, we considered angular effect and utilized spatial and temporal information to a great extent. MODIS and HJ surface reflectance products provide data supply for the algorithm and play cooperative roles. A vegetation growth model was introduced to constrain the uncertainty of HJ data in a temporal scale. The uncertainty of using this algorithm was assessed by error propagation theory and field experiments. Retrieved FVC became more reasonable after consideration of the correlation among time series observations and the introduction of more observational data. A priori information is necessary to constrain the inversion process.
机译:植被覆盖度(FVC)与地表过程广泛相关。本文提出了一种结合MODIS和环景卫星(HJ)的FVC检索算法,环景卫星是中国新发射的星座。在开发的模型中,我们考虑了角度效应,并在很大程度上利用了时空信息。 MODIS和HJ表面反射产品可为算法提供数据并发挥协同作用。引入植被生长模型来限制HJ数据在时间尺度上的不确定性。通过误差传播理论和现场实验对使用该算法的不确定性进行了评估。考虑时间序列观测之间的相关性和引入更多观测数据后,检索到的FVC变得更加合理。先验信息对于约束反演过程是必不可少的。

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