Introduction

This chapter discusses the challenges faced by low-and middle-income countries (LMICs) in dealing with rapid transformation processes, including increasing inequalities, overconsumption of natural resources, high urbanisation rates, massive environmental degradation, and the growing impacts of climate change. The Majority World, where most of the world's population resides, is the epicentre of the ongoing urban transformation, but it lacks accurate, high-resolution, and timely data to support mitigation and adaptation processes. The article highlights the potential of Earth Observation (EO) data to address data gaps and tackle urban and environmental challenges in LMICs. The article discusses the advances in using AI and EO-based algorithms to measure and characterize urban and environmental inequalities, including climate change and environmental challenges, infrastructure inequalities, and mapping the morphology and dynamics of cities, sub-urban and peri-urban areas with EO. We emphasize the innovative use of existing datasets to provide locally relevant information to users and how EO can create societal impacts.