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Winter oilseed rape and winter wheat growth prediction using remote sensing methods

机译:冬季油菜和冬小麦生长的遥感预测

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摘要

Remote sensing is often used for yield prediction as well as for crop monitoring. This paper describes how Landsat satellite data can be used to derive a growth model calculated from normalised difference vegetation index that can predict winter wheat (Triticum aestivum) and winter oilseed rape (Brassica napus) phenological state using the Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie scale. Time series of Landsat images were chosen from the years 2004, 2008 and 2012, when winter oilseed rape was grown, and 2005, 2009, 2011 and 2013, when winter wheat was grown in the same experimental field. The images were selected from the whole growing season of both crops. An advantage of this method is the easy availability of the remote sensing and its easy application for deriving a prediction model from vegetation indices. Our results showed that Landsat images, after correct pre-processing, can be used for winter wheat and winter oilseed rape growth model prediction.
机译:遥感通常用于产量预测以及作物监测。本文描述了如何使用Landsat卫星数据通过归一化差异植被指数计算出的生长模型,该模型可以使用Biologische Bundesanstalt,Bundessortenamt和Chemische Industrie量表来预测冬小麦(Triticum aestivum)和冬季油菜(Brassica napus)的物候状态。 。 Landsat影像的时间序列选自2004、2008和2012年(当时种植冬油菜)和2005、2009、2011和2013年(当时同一实验田中种植了冬小麦)。这些图像是从两种作物的整个生长季节中选取的。这种方法的一个优点是遥感的易用性及其在从植被指数推导预测模型中的简便应用。我们的结果表明,经过正确的预处理,Landsat影像可用于冬小麦和冬季油料油菜生长模型的预测。

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