Radiant Earth Foundation (formerly known as Radiant.Earth) announced today the release of its new open Earth imagery platform, fundamentally changing the way humanitarian aid workers, policymakers, researchers, journalists, and others use satellite images to understand and serve their communities. The platform is the first of its kind to offer instant, secure, and free access to Earth observation data on the cloud and help the global development community apply the data to real-world problems.
The overall goal of the event is to advance the interoperability of satellite data. The reality is that the use of satellite imagery is still a small niche, even though increased knowledge of our planet has the potential to make a huge difference in everyone’s lives. We believe a significant reason it remains a niche field is that going from raw pixels to actionable insight is still very difficult. As an industry, we force users to search for relevant data in many different locations and then put it on them to pre-process the imagery properly to perform their analysis.
As part of a recent Radiant.Earth workshop, 30 leading international experts participated in the launch of a new Technical Working Group on Machine Learning for Global Development. The group includes Earth observations (EO), machine learning (ML), and land cover (LC) classification experts, all working collaboratively towards the goal of developing a community standard on best practices for use of ML with EO, a commons for labeled training data catalogues, and a hierarchical schema for global LC classification.
Small island nations isolated in vast expanses of the Pacific Ocean may be the canaries in the coal mine for what could be climate change’s dangerous impact on a global scale. With nearly a third of the island nation’s population living on land less than 5m above sea level, they are especially vulnerable to the global threat of rising sea levels, extreme weather patterns, deteriorating soil quality, and coral bleaching, all of which damage not only coastlines, but also communities and livelihoods.
Advances in sensor technology, cloud computing, and machine learning (ML) continue to converge to accelerate innovation in the field of remote sensing. However, fundamental tools and technologies still need to be developed to drive further breakthroughs and to ensure that the Global Development Community (GDC) reaps the same benefits that the commercial marketplace is experiencing.
Data collaborative innovation — that is, a group of actors from different data domains working together toward solutions — might hold the key to finding solutions for some of the global challenges that the world faces.