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Satellite and UAV data for Precision Agriculture Applications

机译:精密农业应用的卫星和无人机数据

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The evolution behind Agriculture 4.0 relies on the intelligent use of data collected by using advanced technologies mounted on board of tractors, mobile ground robots, unmanned aerial vehicles and satellites. Today a field could be monitored over a season owing to data acquired by using drones and satellite with different spectral, spatial and temporal resolution. Data are used in precision agriculture scenarios to monitor the growth, detect the presence of weeds, identify areas affected by nitrogen/water stress but the common factor is the high demand for updated data. This paper evaluates different datasources as Landsat-8, Sentinel-2, PlanetScope and UAV on a test-site characterized by areas that have different vigour considering different agronomic management thesis. A comparison over the sub-areas by using different approach enables the understanding of how these heterogeneous data-sources could work together also supporting the decision of agronomists. The evaluation shows that data acquired at a close time could be compared but there are some potential issues that require attention in post-processing as the geometric accuracy to ensure a proper coregistration and georeferencing.
机译:农业4.0背后的演变依赖于通过使用安装在拖拉机,移动地机器人,无人机和卫星的高级技术收集的数据智能使用。今天,由于使用具有不同光谱,空间和时间分辨率的无人机和卫星获取的数据,可以在一个季节监测一个领域。数据用于精密农业场景以监测生长,检测杂草的存在,识别受氮/水胁迫影响的区域,但常见因素是对更新数据的高需求。本文评估了不同的数据源作为Landsat-8,Sentinel-2,行星车和UAV,其特征在于考虑不同的农艺管理论文的不同活力的区域。通过使用不同方法对子区域的比较使得能够了解这些异构数据源如何共同支持农艺学家的决定。评估表明,可以比较在关闭时间的数据,但是有一些潜在的问题需要在后处理中注意力作为几何精度,以确保适当的核心记录和地理学。

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