中文摘要：

为探讨无人机载高光谱空间尺度对大豆产量预测精度的影响,该文以山东嘉祥圣丰大豆为研究对象,设计以多旋翼无人机为平台搭载Cubert UHD185成像高光谱传感器的无人机遥感农情监测系统,获取了大豆多个生育期的无人机高光谱数据。首先,该研究利用盛荚期-始粒期（R4-R5期）的高光谱影像,由21个不同光谱空间尺度提取的高光谱数据构建植被指数,通过植被指数方差分析结果可知所选冠层植被指数与不同品种大豆植株的生长状况密切相关,但是不同空间尺度下的F值仍存在较为明显的差异;其次,采用偏最小二乘回归建立产量与不同空间尺度的植被指数之间的回归模型,通过模型方程估算精度的曲线变化趋势进一步将最优空间尺度面积确认至9.03~10.13 m2,即当采样空间尺度区域长、宽与小区总长、宽比例介于4.25：5和4.5：5时,所得到的冠层光谱能够尽可能准确地估测大豆产量,此时估算产量和实测产量呈极显著相关（相关系数r=0.811 7,参与建模的样本个数270）。该研究可为使用高、低空高光谱影像进行作物表型信息解析和估产提供参考。

英文摘要：

Using unmanned aerial vehicle（UAV） remote sensing monitoring system can rapidly and cost-effectively provide crop physiological traits for crop breeding. UAV equipped with an imaging spectrometer to estimate soybean yield is of great significance for high-throughput and rapid access to large-scale soybean production. However, different sampling areas led to different spectral data, thus affecting the accuracy of soybean grain yield. The objective of this study was to explore the influence of different sampling area on the measuring accuracy of soybean yield, and to analyze the optimum sampling area for estimating soybean grain yield. A 3-by-275 field experiment was performed in 2015, which was arranged in a randomized complete block design with 3 repetitions. An agricultural UAV remote sensing monitoring system was established by a multi-rotor UAV equipped with Cuber UHD185 Firefly imaging spectrometer（Cubert UHD185）. Based on this system, the UAV flight experiments were conducted in Jiaxiang County, Shandong Province at multifarious reproductive growth stages, including the period from the initial blossoming stage to the fully blossoming stage（R1-R2）, the initial pod stage（R3）, from the full pod stage to the initial seed stage（R4-R5）, the full seed stage（R6） and from the full seed stage to the mature stage（R6-R7）. In order to get stable soybean canopy hyperspectral data, the calm and cloudless weather was selected to conduct the experiment. Hyperspectral data of each block were obtained according to the vector image georeferenced with the hyperspectral image. Since soybean yield was highly correlated with canopy reflectance measured by the UAV with Cubert UHD185 system in R4-R5 stages, the hyperspectral data obtained in R4-R5 stages were used to be further analyzed. Firstly, softwares such as Cubert-Pilot from Cubert Company and Agisoft PhotoS can from Agisoft LLC Company were used to realize image mosaic. The length and width of every block were minified in equal proportion for 20 ti