“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. […]
Read More… from OrbitalAI 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. […]
Read More… from AutoICE 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. […]
Read More… from Sentinel 2 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. […]
Read More… from HYPERVIEW 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. […]
Read More… from Food Security Challenge
The AI4EO 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). […]
Read More… from Air Quality & Health Challenge
