To co-create an integrated data ecosystem that enables routine, accurate mapping of slums, informal settlements, and other deprived areas across LMIC cities
LAGOS, Nigeria - NAIROBI, Kenya - KANO, Nigeria
The Bill & Melinda Gates Foundation
The IDEAMAPS Data Ecosystem project is co-designing and developing a participatory data-modelling ecosystem to produce deprived area maps routinely and accurately at scale across cities in lower and middle-income countries (LMIC) to support multiple local stakeholders in their decision-making.
The Data Ecosystem combines artificial intelligence (AI) analysis of earth observation data with community mapping and engagement to improve how we define and understand areas of deprivation (“slums”) in cities. The project integrates multiple public, official, and community-generated datasets to produce granular surface maps of deprived areas across individual cities.
Working with collaborators from the pilot cities in Nigeria (Lagos and Kano) and Kenya (Nairobi), the IDEAMAPS project is generating new data and enhancing the capabilities of various stakeholders to understand and address urban poverty, health, and well-being. The result is that community members and decision-makers will have an improved, co-produced evidence base, as well as strengthened communication networks based on common understandings and trust. These outcomes will support pro-equity interventions to effectively address current issues on urban planning, slum upgrading and urban health.
Explore Our Platform
PHASE 1 OUTPUTS AND ACTIVITIES:
Project launch events in Lagos, Nairobi, and Kano
Participatory Action Research Groups meet in Lagos
Publications and Reports:
Modelling Brief #1: Process to select datasets to model
Mapping Deprived Urban Areas Using Open Geospatial Data and Machine Learning in Africa
The IDEAMAPS Network has produced an evolving family of projects with local teams in cities across the world.Our family of projects develop datasets of urban deprivation and assets (IDEAMAP Sudan, SLUMAP, IDEAtlas, and the IDEAMAPS Data Ecosystem), and foster capacity among stakeholders to use data for decision-making (Data4HumanRights, IDEAMAP Sudan).
· Buenos Aires, Argentina
· Lagos, Nigeria
· Nairobi, Kenya
· Dhaka, Bangladesh
with more cities to be included as the project progresses.
DEPRIMAP - Unraveling the dynamics of deprived urban areas in the Majority World using AI and Earth Observation to foster evidence-based sustainable planning
DEPRIMAP aims to map, model, and analyze deprived urban areas (DUAs) in the Majority World using advanced geospatial data and machine learning techniques. The project focuses on understanding the socio-economic vulnerabilities and environmental risks faced by DUAs contributing to more resilient and sustainable urban planning.
Mexico City, Mexico - Medellín, Colombia - Salvador, Brazil - Buenos Aires, Argentina - Lagos, Nigeria - Nairobi, Kenya - Mumbai, India - Jakarta, Indonesia
The primary objective of IDEAtlas is to develop, implement, validate and showcase advanced AI-based methods to automatically map and characterize the spatial extent of slums from Earth Observation (EO) data.
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