PFI-RP: Fostering Agricultural ReMote Sensing (FARMS) - use of unmanned aerial systems to enable precision agriculture.

这个PFI项目被称为促进农业遥感联盟，或农场联盟，其更广泛的影响/商业潜力围绕着无人驾驶飞机系统（UAS）的遥感技术和数据分析，以精准农业为目标应用领域。这些努力的目标是一种代理作物，豆荚，以及我们的行业合作伙伴优先考虑的三种代理应用程序，即疾病风险建模，收获时间/调度和产量预测，以推动FARMS成为一个可持续的创新生态系统。这是至关重要的，因为尽管全球无人机农业市场规模为342亿美元，但由于过去对商业无人机飞行的限制，美国落后了。农场联盟将在纽约州北部找到发展的沃土，芬格湖地区经济发展委员会已将农业确定为战略增长领域。这一努力将使五指湖地区有机会成为美国东部农业和粮食生产的中心，并通过协调，将导致该行业的领导和增长。最后，至少有四名成像科学和六名商业研究生将在成像-精密-农业-商业的联系中接受培训，成为真正的跨学科科学家和管理者。拟议的项目将对光谱（颜色）和结构（3D）特征的识别做出重大贡献，这些特征来自与特定精准农业应用相结合的无人机平台。我们将改进目前相对简单和通用的方法，并开发新的方法，将过采样的UAS遥感数据提取到每个应用所需的度量的本质。成像科学家和植物生理学家之间的密切合作将为我们的行业合作伙伴提供关键的、具体的（优化的）解决方案，然后将其推向蓬勃发展的精准农业经济。简而言之，昂贵的无人机系统将用于获得商业、经济实惠和实用的无人机解决方案，这些解决方案可以过渡到精准农业领域。最后，这种方法将通过对目标场景和仪器本身进行适当的光谱校准来保证一致、可靠的图像处理——这将FARMS联盟与目前由精准农业服务提供商提供的类似、简单的光谱度量解决方案区分开来。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this PFI project, called the Fostering Agricultural ReMote Sensing Alliance, or FARMS Alliance, centers around the technology and data analytics of remote sensing from unmanned aircraft systems (UAS), with precision agriculture as the targeted application area. The efforts targets a proxy crop, snap bean, and three proxy applications prioritized by our industry partners as key to their commercial efforts, namely disease risk modeling, harvest timing/scheduling, and yield prediction to propel FARMS into a sustainable innovation ecosystem. This is essential, since although the UAS agricultural market is pegged at US$34.2B globally, the USA is lagging due to past restrictions on commercial UAS flights. The FARMS Alliance will find fertile ground for growth in Upstate NY, where the Finger Lakes Regional Economic Development Council has identified agriculture as a strategic growth area. This effort will afford the Finger Lakes region an opportunity to be a hub in the Eastern USA for agriculture and food production and with coordination, will lead to leadership and growth in the industry. Finally, at least four imaging science and six business graduate students will be trained at the nexus of imaging-precision-agriculture-business, equipped as truly trans-disciplinary scientists and managers.The proposed project will contribute significantly to the identification of both spectral (color) and structural (3D) signatures from UAs platforms that are coupled to specific precision agriculture applications. We will improve on the relatively simple and generic current approaches, and develop new methods to distill oversampled UAS remote sensing data to the essence of metrics required for each application. This close collaboration between imaging scientists and plant physiologists will lead to turn-key, specific (optimized) solutions for our industry partners, to then market to the burgeoning precision agriculture economy. In short, expensive UAS systems will be used to derive commercial, affordable, and practical UAS solutions that can transition to the precision agriculture sector. Finally, this approach will hedge consistent, reliable image processing via proper spectral calibration of the target scene and the instruments themselves - this sets the FARMS Alliance apart from similar, simple spectral metric solutions that currently are being offered by precision agriculture service providers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.