UK-China Agritech Challenge - Utilizing Earth Observation and UAV Technologies to Deliver Pest and Disease Products and Services to End Users in China

中英农业科技挑战赛——利用地球观测和无人机技术为中国最终用户提供病虫害产品和服务

基本信息

批准号：
BB/S020977/1
负责人：
Martin Wooster
金额：
$ 42.14万
依托单位：
King's College London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FS020977%2F1
关键词：
UK China Agritech Challenge Utilizing

项目摘要

(KCL) This project aims to develop time-series tools for pest and disease monitoring, forecasting and management in China, providing service products at national and local levels to enhance pest and disease control of wheat rust and locusts in particular. It will also develop advanced UAV-based tools that provide more efficient spraying of control measures (biopesticides) to provide alleviation of these problems without causing chemical pollution. In this context, the King's team will be developing ways to downscale satellite-based maps of land surface temperature to scales more akin to those of the fields within which the crops grow, in order to aid the development of mathematical models that can be used to forecast and monitor the efficacy of the bio-control measures and the spread of wheat rust. They will develop UAV-based methods to deliver maps of crop parameters from aerial imagery, which will be used to help both development of the downscaled satellite datasets and to provide an understanding of the crop structures that can be used to help in the development of the spraying technologies and planning tools that will be developed for the aerial platforms. Finally they will also develop methods to remotely sense locust surface temperatures from thermal imaging, in order to contribute to the development of better models of locust internal body temperature upon which the final mathematical models of bio-pesticide development rate depends.(Loughborough) Our proposal aims to develop a long term sustainable innovative partnership in agriculture technology between the UK and China through a comprehensive approach to deal with these two major agricultural pests/diseases. It will do so from a monitoring,forecasting and management perspective, combining cutting edge technology, modelling and biological information.The project is structured under six work packages that follow the cycle of a dynamic Agri-Tech service: observe to understand the nature of the problem and locate the pest/crop problem (WP1), orientate through development of forecast models to provide strategic risk awareness (WP2), decide providing useful information where to control pests at national and local levels (WP3), and act locally using precise application of bio pesticides via UAV deployments (WP4). The scopeof the project primarily falls into Agri-Tech Challenge 1 "Precision agriculture, agriculture digitisation and decision management tools" but also makes significant contributions to Challenge 2 "Improving the efficiency of sustainable agriculture". A key theme is to develop technologies for integrating data collected by UAVs, earth observation satellites,and bioscience applications related to disease/pest modelling. The project will develop autonomous and smart planning tools for agricultural remote sensing and plant protection, ultimately for the benefit of end users to reduce the cost and improve the effectiveness of their operations. One of the key outcomes is the development and application of novel technical systems for the monitoring and prediction of crop disease/pest outbreaks, As a novel technology, biopesticides treatment of orthoptera will be investigated and demonstrated, along with the modelling and prediction of yellow rust and orthoptera, real-time remote sensing methods will facilitate time specific and site specific treatment along with improved general farming management. Combining this with the work on biopesticides will significantly reduce the use of chemical pesticides and the risk of the development of crop's resistance to them, and will increase biodiversity due to lack of chemical pesticides. In addition to these benefits, the project will open up new business opportunities for both the UK, and Chinese industrial partners outside of China.

（KCL）该项目旨在开发用于害虫和疾病监测，中国预测和管理的时间序列工具，在国家和地方提供服务产品，以增强对小麦锈和蝗虫的害虫和疾病的控制。它还将开发基于无人机的高级工具，可提供更有效的控制措施（生物农药）的喷涂，以减轻这些问题而不会引起化学污染。在这种情况下，国王的团队将开发方法，以降低卫星的地表地图的地表地图，以缩放更类似于农作物种植的田野，以帮助开发数学模型，这些模型可用于预测和监测生物对照测量的效果和麦芽锈的传播。他们将开发基于无人机的方法来从空中图像中传递作物参数的地图，这些方法将用于帮助开发缩小的卫星数据集的开发，并提供对可用于开发用于航空平台的喷雾技术和规划工具的作物结构的理解。最后，他们还将开发方法，从热成像中从热成像中倾斜地表面温度，以促进更好的蝗虫内部温度模型的开发，其最终的生物农药发展速率的数学模型取决于。（Loughborough）我们的建议旨在通过在英国与中国之间的长期可持续性伙伴关系来开发与全面的国家之间的长期可持续伙伴关系，以实现两次全面的方式，这些方法是全面的。 It will do so from a monitoring,forecasting and management perspective, combining cutting edge technology, modelling and biological information.The project is structured under six work packages that follow the cycle of a dynamic Agri-Tech service: observe to understand the nature of the problem and locate the pest/crop problem (WP1), orientate through development of forecast models to provide strategic risk awareness (WP2), decide providing useful information where to control pests at national和本地级别（WP3），并通过无人机部署（WP4）精确地应用生物农药在本地采取行动。该项目的范围主要属于农业技术挑战1“精确农业，农业数字化和决策管理工具”，但也为挑战2“提高可持续农业效率”做出了重大贡献。一个关键主题是开发用于整合由无人机，地球观察卫星和与疾病/害虫建模有关的生物科学应用收集的数据的技术。该项目将开发自主和智能的规划工具，用于农业遥感和植物保护，最终为了使最终用户的利益降低成本并提高其运营的有效性。主要结果之一是，新型技术系统在监测和预测作物疾病/有害生物爆发中的开发和应用，作为一种新型技术，将研究和证明对正前翅目生物农药的处理，以及对黄色生锈和矫形器的建模和预测，实时遥感方法将有助于特定于时间的特定时间和特定于养殖场所，并有助于实时遥感。将其与生物农药的工作相结合，将大大减少化学农药的使用以及产生农作物对它们的耐药性的风险，并且由于缺乏化学农药而增加了生物多样性。除这些好处外，该项目还将为英国和中国以外的中国工业伙伴开放新的商机。