"There is an urgent agronomic (reducing the amount of plant protection products applied to crops), environmental (pollution reduction), economic (lowering the cost of food production) and political (continuing public pressure for a reduction in ag-chem use) need to modernise and update agrochemical applications to crops from the traditional practice of applying a uniform rate across the whole crop to a much more targeted approach. SKAi aims to satisfy this need by building a smart camera and artificial intelligence platform for use by farmers, agronomists and agrochemical applicators. This platform will be integrated into the existing KORE ( [www.koresolution.com][0]) precision agricultural platform to extend its functionality to allow the support of in field smart cameras using image transfer and machine learning. Using this system, we hope to dramatically reduce the total amount of crop protection products applied to crops in the UK and worldwide. [0]: http://www.koresolution.com"

Creating a global ground station network aimed at servicing the small satellite market operating from LEO. The aim of the project is to create 7 test ground stations to confirm the cost, market and technical feasibility to aid in developing a robust exploitation plan.

This project will develop and implement new solutions enabling the improved utilisation of shared waterspace by traditionally manned, partially automated and fully autonomous surface vessels. Our focus is the interaction in potentially hazardous situations between mariners in conventional manned craft as they perceive and respond to ASVs operating both over the horizon (beyond line of sight) and in proximity to other vessels using newly fused visual and satellite data. There is a pressing need to guide and train pilots and other mariners and marine insurers in how to react to this evolving ASV technology as it enters a rapidly growing marketplace. Our main objectives are fourfold; to exploit satellite sensing technology to enable a higher fidelity world model to be provided to vessel operators and /or supervisors; to simulate new scenarios for ASV operations; to combine, for the first time, ASV control simulators and ship hydrodynamic simulators into a single suite capable of visualising different datasets in 3-D; and to evaluate new multi-vessel conflict scenarios in the real-world.

The CropForecast project proposes to improve crop disease forecasting using high resolution earth observation data, accurate digital elevation models and local weather data. Such improvements will increase the efficiency, sustainablility, and profitability of crop production.The current approach to crop disease forecasting has limited spatial resolution and can only generally provide forecasts at a multiple field scale. The proposed approach would allow more precise forecasting at a sub-field level to be achieved. The initial focus will be to track, predict and ultimately limit the spread of potato late blight (Phytophthora infestans) in the UK. The proposed system will give farmers an early warning system that highlights the risk to their crops based on incoming weather patterns, detailed elevation and aspect information and remotely sensed data from satellites using sophisticated modelling techniques.

The CropID system will classify horticultural crops using a machine learning approach integrating; multi-spectral satellite imagery, synthetic aperture radar data, soil properties, physical field characteristics. Image processing algorithms will be used to segment crops based on spectral reflectance, colour and texture. Satellite images acquired through the year will allow the system to build knowledge about individual fields. Soil properties will be used to focus the analysis on areas suitable for specific crops. The Launchpad grant will support the development of a working prototype which will demonstrate the capabilities of the system based on the requirements of a potential customer. Future developments could provide crop identification services for land use monitoring at a national scale. Other services could also be developed to provide crop health and yield forecasts to farmers.