Our Outputs

Academic papers and research outputs from the IDEAMAPS network.

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2024
2024 IDEAMAPS Data Ecosystem Stakeholder Workshops Report
Test of the web platform, validation activities, and summary of results
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2024
2024 IDEAMAPS Data Ecosystem Stakeholder Workshops Report
Test of the web platform, validation activities, and summary of results
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2023
Mapping Deprived Urban Areas Using Open Geospatial Data and Machine Learning in Africa
An output of the Data Ecosystem project, this study demonstrates an approach to map deprived areas within and across cities using open-source geospatial data.
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2023
Co-Design Phase #1 Report
Co-Design Phase #1 Report follows on the Data Ecosystem project work carried out in Lagos and Nairobi in 2023 and discusses the participatory research approach.
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2023
Modelling Brief #1: Process to select datasets to model
Updates from the Data Ecosystem modelling team
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2022
“Domains of deprivation framework” for mapping slums, informal settlements, and other deprived areas in LMICs to improve urban planning and policy: A scoping review
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2020
Need for an Integrated Deprived Area “Slum” Mapping System (IDEAMAPS) in Low- and Middle-Income Countries (LMICs)
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PROJECTS WE’RE CURRENTLY WORKING ON

2024-2028
Currently Active
DEPRIMAP

·      Buenos Aires, Argentina

·      Lagos, Nigeria

·      Nairobi, Kenya

·      Dhaka, Bangladesh

with more cities to be included as the project progresses.

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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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2022 - 2025
Currently Active
IDEAMAPS Data Ecosystem

LAGOS, Nigeria - NAIROBI, Kenya - KANO, Nigeria

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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Currently Active
IDEAtlas

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.

More Active Projects
A global network of slum mappers.
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