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 …
The amount of available satellite imagery data has been substantially growing since the start of the Sentinel missions. Nevertheless, applications of AI to EO data are still scarce. The main goal of the AiTLAS project is to facilitate the uptake of EO data by AI experts and vice versa – the uptake of (advanced) AI …
Hyperspectral imaging can capture hundreds of images acquired for narrow and continuous spectral bands across the electromagnetic spectrum, hence can allow us to precisely analyze the materials that are present in a scene of interest. However, the large volume of hyperspectral images (HSIs) makes their manual analysis and transfer very costly and time-expensive, especially when …
EO data allows us to gather massive global information about our planet Earth’s physical, chemical and biological systems via satellites carrying remote sensing devices. When large amounts of data are concerned, such as those captured by remote sensing devices on satellites used in EO, our computers and AI algorithms can be used to help us …
