Our Projects

DEPRIMAP - Unraveling the dynamics of deprived urban areas in the Majority World using AI and Earth Observation to foster evidence-based sustainable planning

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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.

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Data4HumanRights develops together with JEI and Community Mappers training materials to professionalize the training of community data collectors. We are presently developing a set of 28 short training units.

An interdisciplinary project that involving the use of a wide suite of remotely sensed indicators at different spatial and spectral resolutions, and the implementation of different modelling approaches, with the aim of creating a holistic and open-access tool for slum mapping at different scales, in sub-Saharan Africa.

Developing a community-led geo-spatial database for mapping deprived urban areas (e.g., informal settlements) that supports the decision making process for displacement socio-economic reconstruction in Khartoum, Sudan.

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.

To co-create an integrated data ecosystem that enables routine, accurate mapping of slums, informal settlements, and other deprived areas across LMIC cities 

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