结合HJ1A/B卫星数据和生态因子的籽粒品质监测

该研究引入温度、降水、太阳辐射和土壤肥力等影响小麦籽粒蛋白质含量的重要生态因子，结合遥感数据进行小麦籽粒蛋白质含量监测。以北京郊区的小麦种植区为实验区，获取多时相的HJ1A/B 卫星数据，多个气象站点全生育期气象数据和土壤养分数据，以及收获时小麦籽粒蛋白质含量。分别构建了遥感光谱蛋白质含量模型、生态因子籽粒蛋白质含量模型、光谱生态因子蛋白质含量模型。结果表明:北京地区冬小麦以5 月11 日（开花期左右）NDVIgreen 值与籽粒蛋白质含量相关性最好，达到极显著水平，因此该时期为冬小麦籽粒蛋白质含量遥感监测的最佳时相，并将利用该时期的NDVIgreen 参与光谱蛋白质含量模型、光谱生态因子蛋白质含量模型的构建。对光谱蛋白质含量模型、生态因子籽粒蛋白质含量模型、光谱生态因子蛋白质含量模型进行F 检验，表明各模型均达到极显著水平，3 种模型的决定系数分别为:0.782，0.635，0.843，相对误差分别为:0.151，0.123，0.049。说明综合利用遥感数据和生态因子的监测结果比单独利用遥感数据或单独利用生态因子的精度高。引入生态因子的小麦籽粒蛋白质含量遥感监测有助于提高监测精度，并增加监测模型的农业机理。

Monitoring wheat quality based on HJ1A/B remote sensing data and ecological factors

Temperature, precipitation, solar radiation and soil fertility are important ecological factors for wheat grain protein content (GPC), which are combined with remote sensing data to monitor GPC in this research. Experiments were carried out in suburban areas in Beijing. Multi -temporal HJ1A/B satellite data, meteorological data for the whole growing season from the corresponding meteorological stations, soil nutrient data and GPC obtained at maturity were acquired. Spectral GPC model, ecological factors GPC model and spectral ecological factors GPC model were constructed respectively. The results show that NDVIgreen corresponding to May 11 (around anthesis stage ) has best correlation with GPC in the research area. The correlation coefficient reaches significant level, thus May 11 was the best time for monitoring GPC by remote sensing. NDVIgreen values on May 11 were used for constructing spectral GPC model and spectral ecological factors GPC model. F-test shows that spectral GPC model, ecological factors GPC model, spectral ecological factors GPC model reach extremely significant levels with determination coefficients of 0.782, 0.635, 0.843, and relative error of 0.151, 0.123, 0.049 respectively. The results indicate that accuracy of spectral ecological factors GPC model combined with remote sensing data and ecological factor is higher than GPC model based on only spectral data or only ecological factors. Introduction of ecological factors into spectral protein GPC model helps to improve monitoring accuracy and agricultural mechanism of monitoring models.