Enabling wide area persistent remote sensing for agriculture applications by developing and coordinating multiple heterogeneous platforms

通过开发和协调多个异构平台，实现农业应用的广域持续遥感

• 批准号: ST/N006852/1
• 负责人: Wen-Hua Chen
• 金额: $ 153.86万
• 依托单位: Loughborough University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FN006852%2F1
• 关键词: Enabling; wide; area; persistent; remote

This project is to develop wide area, persistent remote sensing capability for agriculture applications by developing and coordinating a number of sensing platforms such as satellites, unmanned aerial vehicles, airships, and even ground unmanned vehicles. It is aimed to provide an unprecedented high density of spatial and temporal information required in sustainable agriculture. Agriculture is currently facing serious challenges in securing food supply to the world population. Global population will continue to grow in the near future with an increasing aging-population structure. Thus the demand for food is expected to continue to rise as global population grows and a rising middle class desires more meat and dairy products in rapidly developing countries like China. Similarly, the total demand for energy and fresh water will increase as a result of economic growth in China. The increased frequency of extreme weather events occurring will seriously hamper food production. Sustainable intensive agriculture is widely perceived to be the answer to the challenge, which aims to increase food production without adversely damaging natural resources and environment. This increased food production is achieved through breeding cultivars with increased resource efficiency and yield potential, better deployment of these cultivars, and better crop husbandry to reduce crop losses due to adverse factors (e.g. pests, diseases, flooding, drought). Remote sensing plays a key role in developing sustainable agriculture for China and other countries. Remote sensing provides timely, synoptic, cost-effective and repetitive information about crops, their growth environments and other key relevant elements such as migratory insects and diseases. The observed data from the remote sensing can find a wide range of applications; for example, not only providing timely information for farm management or early detection of diseases but also for understanding the biological science involved in agriculture and developing statistical crop modelling for future predictions. Despite all the advances in remote sensing platforms particularly unmanned aerial vehicles, they are still not able to provide required wide area persistent remote sensing capability; for example, both macroscopic and microscopic data are required in understanding outbreak and the propagation of some diseases and pests. This project is to advance the current remote sensing capability by two approaches: 1) further improving the current sensing platforms particularly airships and small scale unmanned aircraft including both pointing systems and vehicles; 2) more importantly coordinating different types of existing sensing platforms (i.e. satellites, unmanned aircraft, or airship) based on their performance and characteristics. With the aim of reducing operation cost and the reliance on the operator's experience/skills while fulfilling the remote sensing requirements for a specific application, both strategical and tactical decision making, planning and coordination tools for the deployment of the platforms will be developed to automate most of the remote sensing tasks for agriculture using autonomous system technologies.

该项目旨在通过开发和协调卫星、无人驾驶飞行器、飞艇甚至地面无人驾驶飞行器等多个传感平台，发展用于农业的广域、持续遥感能力。其目的是提供可持续农业所需的前所未有的高密度空间和时间信息。农业目前在确保世界人口粮食供应方面面临严重挑战。在不久的将来，全球人口将继续增长，人口结构将日益老龄化。因此，随着全球人口的增长和中国等快速发展国家中产阶级的崛起，对食品的需求预计将继续上升。同样，由于中国的经济增长，对能源和淡水的总需求将增加。极端天气事件发生的频率增加将严重阻碍粮食生产。可持续的集约农业被广泛认为是应对这一挑战的办法，其目的是在不对自然资源和环境造成不利破坏的情况下增加粮食生产。通过培育具有更高资源效率和产量潜力的栽培品种，更好地利用这些栽培品种，以及更好的作物管理以减少不利因素（例如害虫，疾病，洪水，干旱）造成的作物损失，实现粮食产量的增加。遥感在中国和其他国家发展可持续农业方面发挥着关键作用。遥感提供关于作物、其生长环境和其他关键相关要素如移栖昆虫和疾病的及时、天气、成本效益高和重复性的信息。通过遥感观测到的数据可以得到广泛的应用;例如，不仅为农场管理或疾病的早期检测提供及时的信息，而且还有助于了解农业所涉及的生物科学，并为未来的预测建立作物统计模型。尽管遥感平台特别是无人驾驶航空器取得了种种进展，但它们仍然无法提供所需的大面积持续遥感能力;例如，在了解某些疾病和害虫的爆发和传播方面，既需要宏观数据，也需要微观数据。该项目将通过两种方法提高当前的遥感能力：1）进一步改进当前的遥感平台，特别是飞艇和小型无人驾驶飞机，包括指向系统和车辆; 2）更重要的是根据其性能和特点协调不同类型的现有遥感平台（即卫星，无人驾驶飞机或飞艇）。为了降低运营成本和减少对运营商经验/技能的依赖，同时满足特定应用的遥感要求，将开发用于部署平台的战略和战术决策、规划和协调工具，以便使用自主系统技术自动完成大多数农业遥感任务。

项目成果

Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind.

• DOI: 10.3390/s18072132
• 发表时间: 2018-07-03
• 期刊: Sensors (Basel, Switzerland)
• 作者: Coombes M;Fletcher T;Chen WH;Liu C
• 通讯作者: Liu C

Deep CNN based droplet deposition segmentation for spray distribution assessment

基于深度 CNN 的液滴沉积分割用于喷雾分布评估

• DOI: 10.1109/icac55051.2022.9911061
• 发表时间: 2022
• 作者: Chen T

Distributed Optimization on Unbalanced Time-Varying Topologies: Theories and Experiments

• DOI: 10.23919/chicc.2018.8484051
• 发表时间: 2018-07
• 期刊: 2018 37th Chinese Control Conference (CCC)
• 作者: Zhenhong Li;Tianqiao Zhao;Z. Ding

Initial alignment of Inertial Navigation System based on a predictive iterated Kalman filter

• DOI: 10.23919/chicc.2018.8483957
• 发表时间: 2018-07
• 期刊: 2018 37th Chinese Control Conference (CCC)
• 作者: Guanghao Cheng;Songyin Cao;Lei Guo;Wenhua Chen

Bearing-Only Formation Control With Prespecified Convergence Time

具有预设收敛时间的纯方位地层控制

• DOI: 10.1109/tcyb.2020.2980963
• 发表时间: 2020-03
• 期刊: IEEE Transactions on Cybernetics
• 影响因子: 11.8
• 作者: Zhenhong Li;Hilton Tnunay;Shiyu Zhao;Wei Meng;Sheng Q.Xie;Zhengtao Ding
• 通讯作者: Zhengtao Ding