Fusion of multispectral imagery and spectrometer data in UAV remote sensing for precision farming

从卫星系统获得的遥感图像在从国家和省级作物类型测绘到作物状况/损害评估、产量估计和土壤湿度监测等更多区域应用的各种尺度上的农业管理应用方面已得到证实。然而，基于卫星的图像受到图像分辨率、成本和灵活性的限制。最高分辨率的卫星图像（~1.2 m多光谱像素）是昂贵的，并且在云层覆盖和竞争性图像订单的情况下，不容易实现适当的图像采集时间。新兴的无人飞行器（UAV）技术价格低廉，可以由用户或通过合同快速灵活地部署。对于个体农场规模的精准农业应用，需要非常高的空间分辨率和时间灵活性。放置在无人机上的成像传感器可以实现小于10厘米的像素尺寸，数据采集可以根据农民的需求定制。

Remotely sensed imagery obtained from satellite systems has proven capabilities in agriculture management applications at a variety of scales from national and provincial crop type mapping to more regional application in crop condition/damage assessment, yield estimation and soil moisture monitoring. Satellite-based imagery, however, is limited by image resolution, cost, and flexibility. The highest resolution satellite imagery (~1.2 m multispectral pixels) is costly and appropriate image acquisition timing is not easy to achieve given cloud cover and competing imagery orders. Emerging uninhabited aerial vehicle (UAV) technologies are inexpensive and can be deployed quickly and flexibly by the user or through contracts. For precision agriculture applications at the individual farm scale, very high spatial resolution and temporal flexibility are required. Imaging sensors placed on UAVs can achieve pixel sizes of less than 10cm and data acquisition can be customized to farmers' needs.