基于花后累积地上生物量比例的冬小麦动态收获指数估算

针对已有基于遥感信息的收获指数估算对籽粒灌浆过程中作物生物量变化和收获指数变化过程考虑不足且估算精度有待进一步提高的现状，该研究以冬小麦为研究对象，基于冠层高光谱数据、地上生物量和动态籽粒产量等数据，在提出灌浆至成熟阶段动态收获指数（Dynamic Harvest Index, DHI）和构建花后累积地上生物量比例动态参数（Dynamic fG, D-fG）基础上，提出了敏感波段中心构建归一化差值光谱指数（Normalized Difference Spectral Index, NDSI）估算D-fG的作物动态收获指数估测技术方法并进行精度验证。在此基础上，通过敏感波段宽度扩展确定了冬小麦D-fG估算敏感波段最大宽度，并实现了最大波宽下D-fG和DHI的遥感获取。结果表明，筛选的5个敏感波段中心λ（366 nm, 489 nm）、λ（443 nm, 495 nm）、λ（449 nm, 643 nm）、λ（579 nm, 856 nm）、λ（715 nm, 849 nm）构建NDSI进行D-fG遥感估算均达到了较高精度水平，均方根误差（Root Mean Square Error, RMSE）在0.036～0.050之间，归一化均方根误差（Normalized Root Mean Square Error, NRMSE）在10.46%～14.59%之间；基于敏感波段中心的DHI估算中，RMSE在0.039～0.053之间，NRMSE在10.50%～14.28%之间；估算D-fG的5个敏感波段中心最大波段宽度分别为30、68、58、20和86 nm，基于最大波宽获取DHI估算结果中，RMSE在0.054～0.055之间，NRMSE在14.38%～14.65%之间。可见，该研究所提收获指数遥感估算方法具有一定的可行性，为获取冬小麦动态收获指数提供了新思路和新方法，也为窄波段高光谱卫星遥感和宽波段多光谱卫星遥感获取大范围作物收获指数空间信息提供一定技术参考。

Estimating the dynamic harvest index of winter wheat using the fraction of accumulated aboveground biomass after flowering

The harvest index (HI) has been served as a predictor of the crop yield in fields. An accurate and rapid HI estimation is highly required using remote sensing. However, the current estimation cannot fully consider the change of crop biomass and HI in the process of grain filling so far. It is very necessary to improve the accuracy of HI estimation in recent years. Taking the winter wheat as the research object, supported by the canopy hyperspectral data and aboveground biomass data in different growth periods after flowering, this study aims to estimate the Dynamic Harvest Index (DHI) based on the fraction of accumulated aboveground biomass after flowering. In this paper, the concept of DHI from grain filling to maturity was proposed, and the dynamic fG parameter (D-fG) was developed, which was defined as the ratio of the aboveground biomass accumulation after flowering to that in the given period. The fitting accuracy R2 two-dimensional diagrams were drawn between the Normalized Difference Spectral Index (NDSI) and D-fG. The sensitive band centers to the winter wheat D-fG were obtained by determining the centers of gravity of the local maximum region of R2 values. Then, on the basis of the statistical relationship model between the measured D-fG and DHI, the estimation and accuracy verification of the DHI of winter wheat based on the D-fG remote sensing parameter information was carried out. At the same time, the sensitive band width was determined when the normalized root mean square error (NRMSE) and the mean relative error (MRE) reached the maximum permissible error (15%). Furthermore, the maximum width of sensitive band was determined for the winter wheat D-fG estimation, further to realize the D-fG remote sensing estimation and DHI remote sensing acquisition under the maximum width of the sensitive band. The results showed that the high level of accuracy was achieved in the D-fG remote sensing estimations using the NDSI of selected five sensitive band centers (such as λ(366 nm, 489 nm), λ(443 nm, 495 nm), λ(449 nm, 643 nm), λ(579 nm, 856 nm) and λ(715 nm, 849 nm)). Among them, the root mean square errors (RMSE) were between 0.036 and 0.050, the NRMSEs were between 10.46% and 14.59%, and the MREs were between 9.49% and 12.78%, respectively. In the DHI estimation using D-fG based on the canopy hyperspectral sensitive band centers, the RMSEs were between 0.039 and 0.053, the NRMSEs were between 10.50% and 14.28%, and the MREs were between 9.27% and 13.25%, respectively. The maximum band widths of five sensitive band centers for D-fG estimation were 30, 68, 58, 20 and 86 nm, respectively. In the D-fG remote sensing estimation using NDSI constructed by the band centers with the maximum band widths, the RMSEs were between 0.051 and 0.052, the NRMSEs were between 14.85% and 14.98%, and the MREs were between 13.43% and 14.82%. In the DHI estimation using D-fG obtained from the NSDI constructed by the maximum width bands, the RMSEs were between 0.054 and 0.055, the NRMSEs were between 14.38% and 14.65%, and the MREs were between 12.95% and 13.70%. Consequently, the remote sensing estimation method of the winter wheat DHI was feasible. The finding can also provide a strong technical reference for the narrow band hyperspectral and wide band multispectral satellite remote sensing data to obtain the spatial information of crop harvest index at the regional scale.