Vegetation indices have long been used to monitor vegetation using spectral information. The red-edge (RE) bands have gained attention for improved yield prediction capabilities over traditional red/near-infrared-based indices. This study introduces the triple red-edge index (TREI), a novel vegetation index that leverages the three RE bands provided by the Sentinel-2 satellite. It aims to enhance the accuracy of crop yield predictions. The TREI exploits changes in the transition slope between the red slope, influenced by photosynthesis, and the near-infrared (NIR) slope, affected by cell structure and leaf layers. It was evaluated against indices utilising none, one, two, or three RE bands for yield prediction efficacy. The study also incorporates a simple model combining weather and remote sensing data to predict crop yields, testing the approach across 168 canola and 123 wheat fields. The validation results demonstrated that the TREI significantly improves crop yield predictions by incorporating all three RE bands and effectively describing the RE region. The TREI yielded the highest concordance correlation coefficient (CCC) values for both canola (CCC = 0.89) and wheat (CCC = 0.85) crops, indicating their effectiveness in crop yield prediction. The study concludes that the TREI index outperforms existing vegetation indices in predicting crop yield due to using the Sentinel-2 three RE bands. The highest CCC values corresponded to using the TREI index in the crop yield prediction with a CCC = 0.89 (canola) and CCC = 0.85 (wheat) according to the validation results.

中文翻译：

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澳大利亚大片地区田间作物产量预测的基于红边的植被指数评估


植被指数长期以来一直用于使用光谱信息来监测植被。与传统的基于红色/近红外的指数相比，红边 （RE） 波段的收益率预测能力更高，因此受到关注。本研究引入了三重红边指数 （TREI），这是一种利用 Sentinel-2 卫星提供的三个 RE 波段的新型植被指数。它旨在提高作物产量预测的准确性。TREI 利用了受光合作用影响的红色斜率与受细胞结构和叶层影响的近红外 （NIR） 斜率之间的过渡斜率变化。它根据不使用、一个、两个或三个 RE 波段的指数进行评估，以实现产量预测效果。该研究还结合了一个结合了天气和遥感数据的简单模型来预测作物产量，在 168 块油菜籽田和 123 块麦田中测试了该方法。验证结果表明，TREI 通过整合所有三个 RE 波段并有效描述 RE 区域，显着改善了作物产量预测。TREI 对油菜籽 （CCC = 0.89） 和小麦 （CCC = 0.85） 作物的一致性相关系数 （CCC） 值最高，表明它们在作物产量预测中的有效性。该研究得出的结论是，由于使用了 Sentinel-2 三个 RE 波段，TREI 指数在预测作物产量方面优于现有的植被指数。根据验证结果，最高 CCC 值对应于在作物产量预测中使用 TREI 指数，CCC = 0.89（油菜）和 CCC = 0.85（小麦）。