FluViSat is a proof-of-concept study that demonstrates the potential of satellite-collected video imagery to provide accurate and timely quantification of water movements and river flows for the benefit of water management globally. The study is being led by the UK Centre for Ecology and Hydrology, in partnership with the Luxembourg-based company, RSS-Hydro, and the Queensland …
In the frame of the CORTEX project, AGENIUM Space develops a set of solutions to simplify high performance Deep Neural Networks to make possible AI analysis on-board. AGENIUM Space reduces networks complexity and optimize DNN execution in on-board hardware (SoC FPGA). The company evaluates different solutions to prepare on-board analysis before launch, as training models …
The project analyses the potential of artificial intelligence technologies for a digital twin of the earth and determine a roadmap for further developments. digital twin of the earth will allow science and policy users alike to gain insights of our earth system and will help with decision support. There are two key user groups of …
Brain in Space is an on-the-ground test environment replicating Spire’s “Low Earth Multi-Use Receiver” (LEMUR) satellite that replicates the functionality and performance of a nanosatellite in space, including the latest and most powerful Artificial Intelligence / Machine Learning modules. The Brain in Space testbed is a major step in the development of AI-assisted processing of …
The aim of the project is to develop a demonstrator “Crowds & Machines” (C&M) that provides strategic information concerning the impact of Covid-19 on food security and political (in)stability. Crowds & Machines enables decision makers to track the impact of Covid-19, design scenarios and act on those scenarios effectively. If successful, Crowds & Machines will …
The United Nations (UN) World Food Programme (WFP) is saving lives in emergencies and changing lives for millions through sustainable development. The “WFP Innovation Accelerator” based in Germany explores the disruptive innovations, technologies and business models for the mother organisation WFP. This project seeks out cutting-edge innovations that use EO and AI technologies to address …
POPCORN is a novel data processing approach for satellite data post-process correction. POPCORN combines the best aspects of the conventional physics-based retrieval algorithms and state-of-the-art machine learning techniques. The aim of the POPCORN project is to develop novel machine-learning-based post-process correction methodology that will improve the Earth observation satellite data accuracy. The methodology will be …
QueryPlanet aims at democratizing the access of Artificial Intelligence to the Earth Observation community by developing open-tools for the creation of AI-ready EO dataset and use-cases that leverage such datasets to build global insights applications. Material and datasets develop under QueryPlanet are open-access. The project aims at providing open-source tools for the exploitation of Earth …
The objective of this activity is to develop the most accurate free and open cloud mask for Sentinel-2 with global coverage and to make it available for global Earth Observation community and promote its usage. For this it is required to separate cloud free areas from cloud- and cloud shadow-corrupted areas as accurately as possible …
FDL Europe is a research collaboration between the ESA’s ɸ-Lab, ESA Esrin and Trillium Technologies and the University of Oxford, in partnership with private industry players such as Google Cloud, Nvidia – Scan, D-Orbit and Planet, in which the latest tools and techniques in Artificial Intelligence (AI) and Machine Learning (ML) are applied to research …
