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

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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.