Climate change and global migration are at the centre of policymakers' efforts. The World Bank has dedicated an entire report to the topic of water, climate change, and development [1]. Together with the World Bank colleagues we have assembled a new dataset to make climate-induced migration visible with the use of explainable machine learning techniques. We showcase how social data science can help policy to make more informed decisions on some of the largest challenges of our times. Severe storms, rising sea levels, and prolonged droughts; the impact of climate change is real and it is increasingly impacting our life.

In a world where we produce enough food to feed everyone, 811 million people still go to bed hungry each night; that's one in every 10 people worldwide. The COVID-19 pandemic, climate change, and complex social-economic factors make the situation even more dire. By contrast, space, satellite, and Artificial Intelligence (AI) technologies have radically transformed humanity's ability to observe and model Earth's systems. It's inevitable then that we pose the question: how can Earth observation (EO) and AI help those in need? To find an answer, the Φ-lab at the European Space Agency, together with the World Food Programme (WFP) Innovation Accelerator, are launching the new EO & AI for SDGs Innovation Programme.