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Coupling a sugarcane crop model with the remotely sensed time series of fIPAR to optimise the yield estimation

机译:将甘蔗作物模型与fIPAR的遥感时间序列耦合以优化产量估算

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The objective of this study was to assess the efficiency of the assimilation of the fraction of intercepted photosynthetically active radiation (fIPAR) data derived from Satellite Pour l'Observation de la Terre SPOT images into the MOSICAS sugarcane crop growth model for estimating the yield at field scale on Reunion Island. Over 3 years, time series of SPOT satellite imagery were used to estimate the daily evolution of NDVI for 60 plots located on two climatically contrasted farms. Ground measurements of the fIPAR were performed on 5 reference fields and used to calibrate a relationship with the corresponding NDVI values. Forced and not forced simulations were run and compared with respect to their ability to predict the final observed yield. Forcing MOSICAS with fIPAR values derived from SPOT images improved the accuracy of the model for the yield estimation (RMSE = 12.2 against 14.8 t ha(-1)) closer to the 1:1 line. However, underestimations of the yield by the forced model suggest that some of the model parameters were not optimal. The maximal radiation use efficiency parameter (RUEm) was optimised for each field, and an analysis of variance showed the significant effect of the ratoon number of the field, of its cultivar and of the farm where it is planted. Accordingly, the RUEm was recalibrated for each cultivar for the number of ratoons and farms. New RUEm values ranged from 3.09 to 3.77 gMJ(-1), and new computations were run using the optimised values of RUEm The results indicate that recalibrating the maximal radiation use efficiency according to the number of ratoons improved the yield estimation accuracy by as much as 10.5 t ha-1 RMSE. This study highlights the potential of time series of satellite images to enhance the estimation of the yield by a forced ecophysiological model and to obtain better knowledge about the ecophysiological processes that are involved in crop dynamics with the recalibration method. (C) 2014 Elsevier B.V. All rights reserved
机译:这项研究的目的是评估将来自卫星陆地观测SPOT图像的截取的光合有效辐射(fIPAR)数据同化到MOSICAS甘蔗作物生长模型中以估计田间产量的效率留尼汪岛上的规模。在过去的3年中,使用SPOT卫星图像的时间序列估算了两个气候对比农场中60个样地的NDVI的每日演变。 fIPAR的地面测量在5个参考场上进行,并用于校准与相应NDVI值的关系。运行强制和非强制模拟,并比较它们预测最终观察到的产量的能力。用来自SPOT图像的fIPAR值强制MOSICAS可以提高接近1:1线的产量估算模型的精度(RMSE = 12.2对14.8 t ha(-1))。但是,强迫模型对产量的低估表明某些模型参数不是最佳的。针对每个田地优化了最大辐射利用效率参数(RUEm),方差分析显示了田间的再生数,栽培品种和种植农场的显着影响。因此,针对每个品种的再生和农场数量,对RUEm进行了重新校准。新的RUEm值介于3.09至3.77 gMJ(-1)之间,并且使用RUEm的优化值进行了新的计算。结果表明,根据再生数重新校准最大辐射使用效率可将产量估算精度提高多达10.5吨ha-1 RMSE。这项研究强调了卫星图像时间序列潜在的潜力,可以通过强制性的生态生理模型来增强对产量的估算,并通过重新校准方法获得有关作物动态的生态生理过程的更好知识。 (C)2014 Elsevier B.V.保留所有权利

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