To say that establishing Radiant.Earth and our newly-launched imagery platform has been a whirlwind is an understatement. Over the last two years, there’s been conceptualizing, planning, endless consultations with experts in the field, deep dives into new technologies such as blockchain and machine learning, building a cohesive and talented team, and of course, addressing the growing demand for what we do: Provide Earth imagery and geospatial tools to the global development community to solve today’s most pressing problems.
Geospatial data and the expertise to interpret it can be helpful to journalists who are researching and reporting complex stories, such as the movements of populations at the intersection of land rights, ecotourism, and political power.
Contentious land development on the Mozambican side of the border with South Africa was billed as a way to protect rhinos and elephants from poachers while providing jobs for the local Cubo community and water for their cattle. However, according to the local villagers, it turned into a land grab by South African conservationists and tourism businesses, aided by corrupt politicians, bribes, and false promises.
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.
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.