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Incorporating yearly derived winter wheat maps into winter wheat yield forecasting model

机译:将年度导出的冬小麦图纳入冬小麦产量预测模型

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Wheat is one of the most important cereal crops in the world. Timely and accurate forecast of wheat yield and production at global scale is vital in implementing food security policy. Becker-Reshef et al. (2010) developed a generalized empirical model for forecasting winter wheat production using remote sensing data and official statistics. This model was implemented using static wheat maps. In this paper, we analyze the impact of incorporating yearly wheat masks into the forecasting model. We propose a new approach of producing in season winter wheat maps exploiting satellite data and official statistics on crop area only. Validation on independent data showed that the proposed approach reached 6% to 23% of omission error and 10% to 16% of commission error when mapping winter wheat 2-3 months before harvest. In general, we found a limited impact of using yearly winter wheat masks over a static mask for the study regions.
机译:小麦是世界上最重要的谷类作物之一。对全球范围内的小麦产量和产量进行及时,准确的预测对于实施粮食安全政策至关重要。 Becker-Reshef等。 (2010年)开发了使用遥感数据和官方统计数据预测冬小麦产量的广义经验模型。该模型是使用静态小麦图实现的。在本文中,我们分析了将年度小麦面罩纳入预测模型的影响。我们提出了一种仅利用作物面积的卫星数据和官方统计数据制作季节冬小麦图的新方法。对独立数据的验证表明,在绘制收获前2-3个月的冬小麦作图时,所提出的方法可达到6%至23%的遗漏误差和10%至16%的佣金误差。通常,对于研究区域,我们发现使用年度冬小麦面罩对静态面罩的影响有限。

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