UK-China Agritech Challenge - Utilizing Earth Observation and UAV Technologies to Deliver Pest and Disease Products and Services to End Users in China (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. The Newton Fund builds research and innovation partnerships with developing countries across the world to promote the economic development and social welfare of the partner countries.