作物生物量快速精确的监测对于农业资源的合理利用与农田的精准管理具有重要意义。近年来,遥感技术因其独特的优势已被广泛用于作物生物量的估算中。本文主要针对不同宽波段植被指数在冬小麦生物量(文中的生物量均是指地上干生物量)估算方面的表现进行探索。首先利用欧洲空间局最新的Sentinel-2A卫星数据提取出17种常见的植被指数,之后分别构建其与相应时期内采集的冬小麦地上生物量间的最优估算模型,通过分析两者间的相关性与敏感性,获取适宜进行生物量估算的指数。最后,绘制了研究区的生物量空间分布图。结果表明,所选的植被指数均与生物量显著相关。其中,红边叶绿素指数(CI_(re))与生物量的估算精度最高(决定性系数R~2为0.83;均方根误差RMSE为180.29 g·m~(–2))。虽然相关性较高,但部分指数,如归一化差值植被指数(NDVI)等在生物量较高时会出现饱和现象,从而导致生物量的低估。而加入红边波段的指数不仅能够延缓指数的饱和趋势,而且能够提高反演精度。此外,通过敏感性分析发现,归一化差值指数和比值指数分别在作物生长的早期和中后期对生物量的变化保持较高的敏感性。由于红边比值指数(SR_(re))和MERIS叶绿素敏感指数(MTCI)在冬小麦全生长季内一直对生物量的变化保持高灵敏性,二者是生物量估算中最为稳定的指数。 Rapid and accurate monitoring of crop biomass is of great importance to the rational utilization of agricultural resources and the precise management of farmland. In recent years, remote sensing has been widely used in crop biomass estimation for its unique advantages. This paper mainly explores the performance of different broad-band vegetation indices in estimating the biomass of winter wheat (biomass in the paper refers to above-ground dry biomass). First, 17 kinds of common vegetation indices were extracted from the latest Sentinel-2A satellite data of the European Space Agency. Then, the optimal estimation models for the above-ground biomass of winter wheat collected during the corresponding period were constructed. By analyzing the correlation between the two With sensitivity, obtain an index that is suitable for biomass estimation. Finally, the spatial distribution of biomass in the study area is plotted. The results showed that all selected vegetation indices were significantly correlated with biomass. Among them, the estimation accuracy of the red edge chlorophyll index (CI_ (re)) and biomass was the highest (the decisive coefficient R ~ 2 was 0.83; the root mean square error RMSE was 180.29 g · m -2). Although the correlation is high, some indices, such as the NDVI, will saturate at higher biomass, leading to underestimation of biomass. The index of red edge band can not only delay the index saturation but also improve the inversion accuracy. In addition, the sensitivity analysis showed that the normalized difference index and the ratio index maintained high sensitivity to the changes of biomass in the early and middle and late stages of crop growth respectively. Both the red edge ratio index (SR_ (re)) and the MERIS chlorophyll sensitivity index (MTCI) have been highly sensitive to changes in biomass throughout the winter wheat growing season, both of which are the most stable indices for biomass estimation.