Peña José M, Torres-Sánchez Jorge, Serrano-Pérez Angélica, de Castro Ana I, López-Granados Francisca
Institute for Sustainable Agriculture, IAS-CSIC, P.O. Box 4084, 14080 Córdoba, Spain.
Sensors (Basel). 2015 Mar 6;15(3):5609-26. doi: 10.3390/s150305609.
In order to optimize the application of herbicides in weed-crop systems, accurate and timely weed maps of the crop-field are required. In this context, this investigation quantified the efficacy and limitations of remote images collected with an unmanned aerial vehicle (UAV) for early detection of weed seedlings. The ability to discriminate weeds was significantly affected by the imagery spectral (type of camera), spatial (flight altitude) and temporal (the date of the study) resolutions. The colour-infrared images captured at 40 m and 50 days after sowing (date 2), when plants had 5-6 true leaves, had the highest weed detection accuracy (up to 91%). At this flight altitude, the images captured before date 2 had slightly better results than the images captured later. However, this trend changed in the visible-light images captured at 60 m and higher, which had notably better results on date 3 (57 days after sowing) because of the larger size of the weed plants. Our results showed the requirements on spectral and spatial resolutions needed to generate a suitable weed map early in the growing season, as well as the best moment for the UAV image acquisition, with the ultimate objective of applying site-specific weed management operations.
为了优化除草剂在杂草 - 作物系统中的应用，需要准确及时的农田杂草地图。在此背景下，本研究量化了使用无人机（UAV）收集的遥感图像对杂草幼苗进行早期检测的效果和局限性。区分杂草的能力受到图像光谱（相机类型）、空间（飞行高度）和时间（研究日期）分辨率的显著影响。在播种后40米和50天（日期2）拍摄的彩色红外图像，此时植株有5 - 6片真叶，杂草检测准确率最高（高达91%）。在此飞行高度下，日期2之前拍摄的图像比之后拍摄的图像效果略好。然而，在60米及更高高度拍摄的可见光图像中，这种趋势发生了变化，由于杂草植株较大，在日期3（播种后57天）的效果明显更好。我们的结果显示了在生长季节早期生成合适杂草地图所需的光谱和空间分辨率要求，以及无人机图像采集的最佳时机，最终目标是应用精准的杂草管理操作。
