Abstract This paper presents an operational methodology for the estimation of the harvest index (HI) in commercial fields planted with wheat crops (Triticum aestivum L.) using a Remote Sensing based approach. The approach proposed variants from the methodologies reported by Kemanian et al., (2007) and Sadras and Connor (1991) for the estimation of the HI using the ratio between variables related with biomass production, i.e. absorbed photosynthetically active radiation (APAR), crop transpiration (T) and crop transpiration coefficient (Kt) as defined in the FAO-66 manual. The estimation of these variables along the growing season integrates time series of Remote Sensing satellite images and meteorological data into the crop growth models. The proposed models for estimation of HI were calibrated using an extensive HI dataset obtained from 19 commercial fields (empirical data) planted with wheat. The fields were subject to different water and nutrient management, resulting in empirical HI values from 0.23 to 0.55. Future applications of the proposed approach are the operational estimation of wheat production at both regional and local scales and the estimation of the within-field variability of crop production considering the variability of HI values within the field.

中文翻译：

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使用基于遥感的方法估计小麦作物的收获指数

摘要 本文提出了一种使用基于遥感的方法估算种植小麦作物 (Triticum aestivum L.) 的商业田的收获指数 (HI) 的操作方法。该方法提出了来自 Kemanian 等人（2007 年）以及 Sadras 和 Connor（1991 年）报告的方法的变体，用于使用与生物量生产相关的变量之间的比率估计 HI，即吸收的光合有效辐射 (APAR)、作物蒸腾 (T) 和作物蒸腾系数 (Kt)，如FAO-66 手册中所定义。沿生长季节对这些变量的估计将遥感卫星图像和气象数据的时间序列整合到作物生长模型中。使用从种植小麦的 19 个商业田地（经验数据）获得的广泛 HI 数据集校准了用于估计 HI 的拟议模型。这些田地受到不同的水和养分管理，导致经验 HI 值从 0.23 到 0.55。拟议方法的未来应用是在区域和地方尺度上对小麦产量的操作估计，以及考虑田间 HI 值变化的作物生产田间变化估计。