Artificial Intelligence for Automated Mapping of Land Use and Land Cover.

smartCO2 – A roadmap towards smart EO services for CO2 inventorying and control

VegetationDynamics - Towards automatized, scale independent, high resolution, high temporal dynamic vegetation water content monitoring 4.0 - Developing First Time Big Data EO Breakthrough Technologies for Vegetation Indices by Hybridising Sentinels 1 and 2.

LandMon – Exploitation of next generation satellite missions for operational land monitoring

EO-NOVA – Evaluating the potential of emerging EO sensor platforms for novel value-added commercial applications

CropMon – Enabling an operational Sentinel-2 Crop Monitoring Service

A project carried out by Φ-lab in conjunction with UNICEF has been selected as one of the UN agency’s top research initiatives of 2022. The success of the project, which developed an Artificial Intelligence (AI) solution for quantifying dengue fever outbreaks, has led to its operationalisation phase receiving significant funding from the Wellcome Trust.

Continuing its joint initiatives with ESA Φ-lab, UNICEF is appointing two researchers to work on a project that forms part of the UN Secretary-General’s Digital Cooperation Roadmap. The project maps current access to electricity and the Internet for schools around the world in support of an ambitious UNICEF target to provide connectivity for every child by 2030.

Advanced Cloud-Native Solution for Efficient Remote Sensing Image Processing using ML/DL Techniques

MUSLS: Persistent Multi-Sensor Land Surveillance and Change Monitoring