Effective estimation of crop yield on a regional scale in a short time with low cost would only be possible utilizing remote sensing. Several approaches have been proposed based on remotely sensed data for estimating Aboveground Biomass (AGB). In this study, three satellite-based approaches, including Radiation Use Efficiency (RUE). The soil water atmosphere plant (SWAP) model, and FAO33, were evaluated in the irrigated wheat and barley fields in the Qazvin irrigation network, Iran. To this end, the leaf area index (LAI) and relative evapotranspiration (ET_rel) were extracted from the Landsat data and incorporated into the methods. A comparative analysis was undertaken to evaluate the performance of the satellite-based approaches using percent absolute error (PAE). By updating SWAP with satellite-derived LAI and surface incoming solar radiation, the PAE decreased significantly. Results of different Spectral Indices (SIs) in the RUE method showed that NDVI performed best with PAE of 1.52 percent and RMSE of 664.6 kg ha⁻¹. Also, the RUE method with RMSE of 664.6 kg ha⁻¹ had 4.7 and 23.8 lower PAE compared to the SWAP (RMSE = 2221.4 kg ha⁻¹) and FAO33 (RMSE = 4394.2 kg ha⁻¹), respectively. However, this was not the only criteria for a well-performed method, because earlier AGB forecast was only feasible by making use of SWAP since the satellite-derived parameters were only incorporated into the model about one month before the harvest.

只有利用遥感技术，才能在短时间内以低成本有效地估算作物产量。已经提出了几种基于遥感数据的方法来估计地上生物量（AGB）。在这项研究中，三种基于卫星的方法，包括辐射使用效率（RUE）。在伊朗的Qazvin灌溉网络中，在灌溉的小麦和大麦田中对土壤水气植物（SWAP）模型和FAO33进行了评估。为此，叶面积指数（LAI）和相对蒸散量（ET _rel）是从Landsat数据中提取出来的，并纳入了方法中。使用绝对误差百分比（PAE）进行了比较分析，以评估基于卫星的方法的性能。通过使用卫星衍生的LAI和地面入射太阳辐射更新SWAP，PAE显着降低。RUE方法中不同光谱指数（SI）的结果表明，NDVI表现最佳，PAE为1.52％，RMSE为664.6 kg ha ^-1。同样，与SWAP（RMSE = 2221.4 kg ha ^-1）和FAO33（RMSE = 4394.2 kg ha ^-1）相比，RMSE为664.6 kg ha ^-1的RUE方法的PAE分别低4.7和23.8。）， 分别。但是，这并不是执行良好方法的唯一标准，因为较早的AGB预测仅通过使用SWAP才可行，因为卫星衍生参数仅在收割前一个月才纳入模型。