Abstract Crop biomass (Bio) is one of the most important parameters of a crop, and knowledge of it before harvest is essential to help farmers in their decision making. Both green and dry Bio can be estimated from vegetation spectral indices (VIs) because they have a close relationship with accumulated absorbed photosynthetically active radiation (APAR), which is proportional to total Bio. The aims of this study were to analyze the potential capacity of spectral vegetation indices in estimating corn green biomass based on their relationship with the photosynthetic vegetation sub-pixel fraction derived from spectral mixture analysis and to analyze the best interval of VI accumulation (days) for corn grain yield estimation. Field data of center pivots cultivated with corn during the irrigation seasons of 2015 and 2018 and Landsat 8 and Sentinel 2 images were used. The EVI produced the best results; Pearson's correlation coefficient, RMSE and Willmott’s index reached 0.99, 6.5%, and 0.948, respectively. Among the nine potential VIs analyzed, the EVI, SAVI and OSAVI were considered the first, second and third best performing for corn green Bio estimation, respectively, based on their comparison to the photosynthetic vegetation sub-pixel fraction (fPV), and the time intervals that extended until 120 days after sowing showed the best results for corn grain yield estimation.

中文翻译：

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基于光谱植被指数与光合植被亚像素分数的关系，使用光谱植被指数进行玉米绿色生物量估算的潜力

摘要 作物生物量 (Bio) 是作物最重要的参数之一，在收获前了解它对于帮助农民做出决策至关重要。绿色和干燥的 Bio 都可以通过植被光谱指数 (VI) 进行估算，因为它们与累积吸收的光合有效辐射 (APAR) 密切相关，而后者与总生物量成正比。本研究的目的是分析光谱植被指数在估计玉米绿色生物量方面的潜在能力，基于它们与光谱混合分析得出的光合植被亚像素分数的关系，并分析 VI 积累的最佳间隔（天）玉米籽粒产量估算。使用了 2015 年和 2018 年灌溉季节期间用玉米种植的中心枢纽的田间数据以及 Landsat 8 和 Sentinel 2 图像。EVI 产生了最好的结果；Pearson 相关系数、RMSE 和 Willmott 指数分别达到 0.99、6.5% 和 0.948。在分析的 9 个潜在 VI 中，EVI、SAVI 和 OSAVI 分别被认为是玉米绿生物估计的第一、第二和第三最佳表现，基于它们与光合植被子像素分数 (fPV) 的比较，以及时间延长至播种后 120 天的间隔显示了玉米籽粒产量估算的最佳结果。