IDEAMAPS: Modelling Sub-Domains of Deprivation with EO and AI

IDEAMAPS is developing a participatory data-modelling ecosystem to produce maps of deprived areas ("slums") routinely and accurately at scale across cities in lower- and middle-income countries (LMICs). The Ecosystem is co-designed with local stakeholders with the aim of supporting decision-making and evidence-based policymaking. Within the IDEAMAPS Ecosystem, deprivation (multi-dimensional poverty) is modelled via a large set of subdomains (e.g., irregular layouts, waste accumulation) relating to the domains of deprivation (e.g., unplannedness, contamination). Earth Observation (EO) and AI are used to build these models at scale in environments where data is commonly absent. Models are built within intense community engagements using a Participatory AI approach, where empowerment and transparency about inputs, models and outputs are essential. Open and free EO data (e.g., Copernicus) and data with research access (e.g., SDGSat-1) are combined with public, official, and community-generated datasets to produce gridded surface maps of deprivation across cities. These outcomes support bottom-up planning and the localization of SDGs.