玉米生物量及水分利用效率是反映作物长势和作物品质的重要指标。为实现农业精准管理，本文以不同水
分处理的青贮玉米为研究对象，探讨无人机多光谱遥感平台结合作物生长模型估测青贮玉米生物量及水分利用效
率的可行性。首先，将基于高时空分辨率无人机多光谱图像估测的关键作物参数蒸腾系数 k t 输入到简单的水分效
率模型中，来拟合不同水分胁迫处理下玉米水分利用效率 WUE 和标准化水分利用效率 WP * ;然后，采用拟合的
WUE、WP * 估算相同水分和不同水分状况下的玉米生物量，并进行验证;基于高时空分辨的无人机多光谱遥感图像
获取了大田尺度上的 WUE、WP * 和生物量的空间分布图。结果表明，基于无人机多光谱、气象和土壤水分数据计
算的实际蒸腾量 ∑ T c，adj 和 ∑ k t k sw k st (k sw 、k st 为环境胁迫因子)与玉米生物量具有极显著(P ＜0. 001)的相关性，
不同水分处理下 WUE 的决定系数 Ｒ 2 均不小于 0. 92，WP * 的 Ｒ 2 均不小于 0. 93。在同一水分胁迫下，使用拟合的
WUE 和 WP * 对生物量的估测精度几乎相同，玉米 V Ｒ4 生育期估测精度较高，WUE 的 ＲMSE 为126 g/m 2 ，WP * 的
ＲMSE 为 91. 7 g/m 2 ，一致性指数 d 均为 0. 98，但在 Ｒ5 Ｒ6 生育期内精度不高。在不同水分胁迫下，使用 WUE 和
WP * 估测生物量时，WUE 容易受到水分胁迫影响，精度较低(ＲMSE 为 306 g/m 2 ，d = 0. 93)，而 WP * 的精度较高
(ＲMSE 为 195 g/m 2 ，d =0. 97)。研究表明，将无人机遥感平台与作物生长模型相结合能够很好地估测大田玉米生
物量及水分利用效率。
其他摘要
Biomass and crop water use efficiency (CWUE) are important indicators to reflect plant
growth productivity and quality，and their accurate real-time acquisition is the guarantee to achieve
accurate agricultural management． To assess the feasibility of unmanned aerial vehicle (UAV) remote
sensing platform combined with water use efficiency growth models to estimate crop biomass and CWUE，
the silage maize was employed as the research object． The key crop parameter transpiration coefficient
(k t ) estimated based on the multispectral image of the high-resolution space-time UAV was firstly
inputted into two simple water efficiency models to fit the WUE and WP * of the silage maize under
different water stress conditions，and then the biomass of silage maize under the same and different water
conditions was estimated by the fitted WUE and WP * values． The results showed that the correlation
between the biomass and ∑ T c，adj and ∑ k t k sw k st based on the multispectral UAV platform combined
with meteorological and soil water content data reached extremely significant level (P ＜0. 001)． Underthe different stress conditions，the lowest determinant coefficients of fitted WUE and WP * were 0. 92 and
0. 93，respectively． Under the same water stress condition，the accuracy of biomass estimation by using
the fitted WUE and WP * values was almost the same，which was shown in the following aspects: in the
V Ｒ4 growth period of maize，the accuracy of biomass estimation based on the fitted WUE indicating
with ＲMSE was 126 g/m 2 ，d was 0. 98，the accuracy of biomass estimation based on the fitted WP *
indicating with ＲMSE was 91. 7 g/m 2 ，d was 0. 98，but the accuracy was not high in the Ｒ5 Ｒ6 growth
period． When WUE and WP * values were used to estimate biomass under different water stress
conditions，WUE was susceptible to water stress with low accuracy (ＲMSE was 306 g/m 2 ，d was 0. 93)，
while WP * had higher accuracy (ＲMSE was 195 g/m 2 ，d was 0. 97)． At the same time，the spatial
distribution maps of WUE，WP * and biomass on the field scale were obtained based on the multispectral
remote sensing image of UAV． Overall，the combination of UAV remote sensing platform and crop growth
model can well estimate the field silage maize biomass and water use efficiency．
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