The CostCutting4Sugarcane project aims to develop a platform delivering agronomic advice and yield forecasts for sugarcane producers and processors that reduces costs and optimise production. The solution combines SatEO optical imagery, radar-based data and agronomic models. The main users of the CostCutting4Sugarcane service are sugarcane mill

The proposed service is based on a solution for contactless delivery services using YAPE (Your Autonomous Pony Express), an autonomous driving droid, for the last mile delivery both in outdoor and indoor contexts. The solution is
particularly relevant in hospitals during the COVID-19 time as an aid to maintain the physical distance and to minimise the risk of spreading of the virus.

BePI is a health and security service for early surveying of COVID-19 disease outbreaks thanks to drones and rovers able to identify people with relevant symptoms, and support enforcement of lock-down and social distancing measures.

This project focuses on the link between smallholder farmers and the processors of high-value crops with the purpose of developing a crop monitoring platform to improve yield forecast of harvests from smallholders. The service improves the visibility and traceability of both quantity and quality of raw products expected by agri-processors, who can better plan their logistics and supply chain. By being registered in the platform, smallholder farmers receive localised weather forecasts, agricultural advice, personalised pest warnings and price indications for their harvest.

The project develops a supply chain automation service to automate transport tasks in industrial, urban and rural environments using a fully autonomous transport system. The self-driving transport system is used for industrial applications and middle mile supply chain automation.

Quantitative optical remote sensing methods for monitoring vegetation stress indicators for assessing ecosystem services and wetland health with regard to global sustainability goals.

Early prioritization of areas to promote biodiversity by fusing multimodal earth observation data with open geodata and AI.

Utilisation of COPERNICUS data for climate-resilient urban planning using the example of heat, water & vegetation.

BIGFE - Recording water quality and water area extent of inland waters by remote sensing.

In BIGFE, satellite products freely available from the European COPERNICUS satellite programme are  processed, harmonised and validated for a selection of approx. 100 water bodies. Target variables are chlorophyll, turbidity, secchi depth, water temperature and cyanobacteria. Besides surface water quality, a new tool is developed for water surface area dynamics (WaterMaskAnalyzer).

Monitoring for climate adaptation.

The UrbanGreenEye project is to establish satellite data as a tool for action in municipal administration and planning processes in the determination of climate adaptation-relevant parameters. The aim is to create a uniform information and decision-making basis for municipal planning instruments.