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

PFI-RP: Fostering Agricultural ReMote Sensing (FARMS) - use of unmanned aerial systems to enable precision agriculture.
PFI-RP:促进农业遥感 (FARMS) - 使用无人机系统实现精准农业。
批准号:
1827551
负责人:
Jan van Aardt
金额:
$74.68万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-15 至 2024-08-31

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中文摘要
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英文摘要
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.
期刊论文(6)
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科研奖励(0)
会议论文
DOI: 10.1117/1.jrs.14.024519
发表时间: 2020-06-05
期刊: JOURNAL OF APPLIED REMOTE SENSING
影响因子: 1.7
作者: [Hassanzadeh, Amirhossein, van Aardt, Jan, Pethybridge, Sarah Jane]
通讯作者: Pethybridge, Sarah Jane
DOI: 10.3390/rs13193975
发表时间: 2021-10
期刊: Remote. Sens.
影响因子: --
作者: [Fei Zhang;A. Hassanzadeh;J. Kikkert;S. Pethybridge;J. Aardt]
通讯作者: Fei Zhang;A. Hassanzadeh;J. Kikkert;S. Pethybridge;J. Aardt
DOI: 10.3390/rs13163241
发表时间: 2021-08-01
期刊: REMOTE SENSING
影响因子: 5
作者: [Hassanzadeh, Amirhossein, Zhang, Fei, Pethybridge, Sarah J.]
通讯作者: Pethybridge, Sarah J.
DOI: 10.3390/rs13112180
发表时间: 2021-06
期刊: Remote. Sens.
影响因子: --
作者: [R. Chancia;J. Aardt;S. Pethybridge;Daniel Cross;J. Henderson]
通讯作者: R. Chancia;J. Aardt;S. Pethybridge;Daniel Cross;J. Henderson
AIR: Consortium for 3D Innovation (C3I)
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    1127728
  • 项目类别:
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  • 资助金额:
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  • 财政年份:
    2011
  • 负责人:
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