Crop yields in smallholder systems are traditionally assessed using farmer-reported information in surveys, occasionally by crop cuts for a sub-section of a farmer's plot, and rarely using full-plot harvests. Accuracy and cost vary dramatically across methods. In parallel, satellite data is improving in terms of spatial, temporal, and spectral resolution needed to discern performance on smallholder plots. This study uses data from a survey experiment in Uganda, and evaluates the accuracy of Sentinel-2 imagery-based, remotely-sensed plot-level maize yields with respect to ground-based measures relying on farmer self-reporting, sub-plot crop cutting (CC), and full-plot crop cutting (FP). Remotely-sensed yields include two versions calibrated to FP and CC yields (calibrated), and an alternative based on crop model simulations, using no ground data (uncalibrated). On the ground, self-reported yields explained less than 1 percent of FP (and CC) yield variability, and while the average difference between CC and FP yields was not significant, CC yields captured one-quarter of FP yield variability. With satellite data, both calibrated and uncalibrated yields captured FP yield variability on pure stand plots similarly well, and both captured half of FP yield variability on pure stand plots above 0.10 hectare. The uncalibrated yields were consistently 1 ton per hectare higher than FP or CC yields, and the satellite-based yields were less well correlated with the ground-based measures on intercropped plots compared with pure stand ones. Importantly, regressions using CC, FP and remotely-sensed yields as dependent variables all produced very similar coefficients for yield response to production factors.

中文翻译：

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天上的眼睛，地面上的靴子：评估基于卫星和地面的作物产量测量和分析方法

小农系统中的作物产量传统上是使用农民报告的调查信息来评估的，有时是通过对农民地块的一部分进行减产，很少使用整块地的收成。不同方法的准确性和成本差异很大。与此同时，卫星数据在空间、时间和光谱分辨率方面正在改进，以识别小农地块的性能。本研究使用来自乌干达调查实验的数据，并评估基于 Sentinel-2 图像的遥感地块级玉米产量相对于依赖农民自我报告、子地块作物切割的地面措施的准确性(CC) 和全区作物扦插 (FP)。遥感产量包括校准到 FP 和 CC 产量（校准）的两个版本，以及基于作物模型模拟的替代方案，不使用地面数据（未校准）。在实地，自我报告的产量解释了不到 1% 的 FP（和 CC）产量变异性，虽然 CC 和 FP 产量之间的平均差异不显着，但 CC 产量捕获了四分之一的 FP 产量变异性。使用卫星数据，校准和未校准的产量都同样很好地捕捉了纯林分地块的 FP 产量变异性，并且都捕获了 0.10 公顷以上纯林分地块上半数的 FP 产量变异性。未校准的产量始终比 FP 或 CC 产量高 1 吨/公顷，与纯林分相比，基于卫星的产量与间作地块的地面测量相关性较差。重要的是，使用 CC 的回归，