Rapid urbanization is transforming cities. Cities are challenged by severe housing and environmental issues, further exacerbated by the growing impacts of climate change. The problem of spatial inequalities is especially acute in cities of Low- and Middle-Income Countries (LMICs), although it is also present in High-Income Countries (HICs). To address these challenges, local adaptation strategies need to be underpinned by high-quality, timely, and reliable data that is detailed and specific to the local context. For this purpose, innovations in Earth Observation (EO) techniques, Artificial Intelligence (AI) methodologies, and information built together with local stakeholders need to be combined. This keynote offers an overview of various methodological advances and challenges, ranging from local to global scales, that combine EO/AI with Citizen Science approaches to facilitate evidence-based policymaking for sustainable development, in line with the Sustainable Development Goals (SDGs). For instance, in promoting climate adaptation, local discussions must be informed by detailed and reliable data on urban deprivation and climate impacts (e.g., floods, heat). Such data needs to consider social, economic, and environmental aspects to ensure comprehensive and effective adaptation measures. However, there are major challenges to fully realize the potential of EO data analysis. These challenges can be summarized as (a) Lack of in situ data availability, (b) Knowledge divide – most EO studies focus on the Global North, and c) Limited inclusion of local stakeholders in the development of mapping applications (limiting the relevance of the information). Much of the EO-based mapping is done without the inclusion and partnership with stakeholders living in mapped areas. The keynote will highlight advances in GeoAI-based methods for measuring urban inequalities across multiple dimensions (environmental, demographic, socio-economic, technological, hazards, climate change). It highlights novel datasets, societal relevance, and methodological innovations that provide locally relevant insights and societal impact.