Airborne Hyperspectral Images and Ground-Level Optical Sensors As Assessment Tools for Maize Nitrogen Fertilization
Airborne Hyperspectral Images and Ground-Level Optical Sensors As Assessment Tools for Maize Nitrogen Fertilization
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DOI：
10.3390/rs6042940
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发表时间：
2014-04-01
期刊：
影响因子：
5
通讯作者：
Zarco-Tejada, Pablo
中科院分区：
文献类型：
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作者：
Quemada, Miguel;Luis Gabriel, Jose;Zarco-Tejada, Pablo
利用传感器估算作物氮(N)状态有助于根据作物需求调整肥料水平，降低农民成本和氮素对环境的损失。在这项研究中，我们评估了从田间数据和航空图像中获得的高光谱指数在制定玉米氮肥建议方面的潜力。采用随机田间试验方法，于2012年在2个不同日期（二次施肥前和开花期）进行6种氮肥施用量为0 ~ 200 kg中心点N中心点ha（-1）的4个重复试验。地面读数由SPAD（(R)）、Dualex（(R)）和Multiplex（(R)）传感器获取，机载数据由高光谱和热传感器在实验地点上空300米处飞行获取。利用高光谱图像计算每个地块的绿度、叶绿素和光化学指数。Pearson系数用于量化传感器读数与农艺测量值之间的相关性。采用基于足氮指数的统计程序，确定各指数在区分缺氮和足氮地块上的准确性。研究发现，在评估作物氮素状况和预测开花产量方面，基于空中测量的指数与地面设备测量的指数一样可靠。在茎伸长时，反射率、R750/R710和荧光检索（SIF760）是唯一与作物产量相比产生显著结果的指标。现场水平的SPAD读数、机载R750/R710指数和SIF760在区分氮充足和缺氮处理时的错误率最低，但仍建议在商业现场应用之前减少误差。
Estimating crop nitrogen (N) status with sensors can be useful to adjust fertilizer levels to crop requirements, reducing farmers' costs and N losses to the environment. In this study, we evaluated the potential of hyperspectral indices obtained from field data and airborne imagery for developing N fertilizer recommendations in maize (Zea mays L.). Measurements were taken in a randomized field experiment with six N fertilizer rates ranging from zero to 200 kg center dot N center dot ha(-1) and four replications on two different dates (before the second fertilizer application and at flowering) in 2012. Readings at ground level were taken with SPAD((R)), Dualex((R)) and Multiplex((R)) sensors, and airborne data were acquired by flying a hyperspectral and a thermal sensor 300 m over the experimental site. The hyperspectral imagery was used to calculate greenness, chlorophyll and photochemical indices for each plot. The Pearson coefficient was used to quantify the correlation between sensor readings and agronomic measurements. A statistical procedure based on the N-sufficient index was used to determine the accuracy of each index at distinguishing between N-deficient and N-sufficient plots. Indices based on airborne measurements were found to be as reliable as measurements taken with ground-level equipment at assessing crop N status and predicting yield at flowering. At stem elongation, the reflectance ratio, R750/R710, and fluorescence retrieval (SIF760) were the only indices that yielded significant results when compared to crop yield. Field-level SPAD readings, the airborne R750/R710 index and SIF760 had the lowest error rates when distinguishing N-sufficient from N-deficient treatments, but error reduction is still recommended before commercial field application.