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PANGAEA
PANGAEA is a new evaluation and benchmarking protocol that covers a diverse set of datasets, tasks, resolutions, sensor modalities, and temporalities. This challenge is open-ended, giving participants the flexibility to explore, experiment, and iterate on their models over time. Alongside the open challenge, we’ll be launching regular Data Sprints – short, high-impact tasks that run for about two months each and focus on specific use cases within the PANGAEA dataset. These sprints will come with their own goals, deadlines, and prizes. […]
EASi Workshop // HYPERVIEW2
The new HYPERVIEW2 Challenge is implemented as part of the Explainable AI in Space (EASi) workshop, that KP Labs, ESA, and the Φ-Lab Challenges team are organising as part of the European Conference on Artificial Intelligence (ECAI), which is hosted in Bologna, Italy from 25th–30th October 2025. […]
MapYourCity Challenge
Your city holds secrets ready to be revelead. We invite you to be part of this story and join the #MapYourCity challenge. […]
OrbitalAI Challenge
“This exciting challenge aimed to explore the cutting-edge possibilities of in-orbit data processing and its potential to drive progress in earth sustainability, business, industry, and science. […]
AutoICE Challenge
An extraordinary challenge has been created to bring together Artificial Intelligence (AI) and Earth Observation (EO) players to address the challenge of “automated sea ice mapping” from Sentinel-1 SAR data. […]
Sentinel 2 Challenge
Agriculture plays a central role globally by providing food for humans and livestock or material for industrial processes. It is a driver of economic growth and will play an essential role in reducing the impact of climate change and greening our economies. […]
HYPERVIEW Challenge
Maintaining farm sustainability through improving the agricultural management practices by the usage of recent advances in Earth observation and artificial intelligence has become an important issue nowadays. It can not only help farmers face the challenge of producing food at an affordable price, but can also be crucial step toward the planet-friendly agriculture. […]
Food Security Challenge
Remote sensing is entering a new era of time-series analysis. Daily revisit times of satellites allow for near real-time monitoring of many areas across the globe. However, there has been little exploration of deep learning techniques to leverage this new temporal dimension at scale. […]
Air Quality & Health Challenge
The ESA Φ-lab Air Quality & Health challenge was a joint effort of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Copernicus Atmosphere Monitoring Service (CAMS). It focused on developing AI-powered solutions to facilitate the downscaling of analyses and forecasts of surface concentrations of particulate matter (PM2.5) and nitrogen dioxide (NO2). […]
