ONEKANA - Earth ObservatioN-based modElling for maKing thermAl iNequality visible in African cities

Context and objectives

ONEKANA is motivated by the need to make urban thermal inequity visible in LMIC countries. It focuses on sub-Saharan African (SSA) cities, where the urban poor living in deprived urban areas (DUAs), including ‘slums’, are more exposed to temperature variations and heat impacting their health and well-being than other urban dwellers due to several factors pertaining to area-level urban typology (e.g., building density, proportion of green areas) and household-level typology (e.g., building materials, overcrowding). Climate change further worsens inequity in this respect, due to the increase in extreme weather events such as heat waves. 

While Earth Observation (EO) has the potential to assess the magnitude of population exposure, there remain several scientific challenges that need to be addressed including the fact that EO-derived covariates (such as land surface temperature, built forms, vegetation, etc.) relate only weakly or with great uncertainty to air temperature, and that temperature, deprivation, and population data are sparse for training models on sub-Saharan African cities. 

Our research hypothesis is that using open or low-cost Earth Observation data, open geospatial data, and Citizen Science data, it is possible to model areas that are exposed to both high levels of deprivation and high levels of temperature variations/extreme heat, and to quantify the vulnerable population exposed to such conditions for the prioritisation of local adaptation measures towards green and sustainable cities. It stems from research carried out in the SLUMAP and PARTIMAP projects in which we developed EO and citizen science methods for mapping and characterising DUAs and modelling the perception of deprivation severity within DUAs by the local communities. 

Project outcome

Expected scientific results

Innovative scalable methods and models that involve AI, EO and Citizen Science and make use of open or low-cost data, to output fine-grained predictions of population distribution, deprivation and air temperature in DUAs. Estimates of urban population exposed to both high levels of deprivation and temperature variations/extremes. 

Societal and environmental relevance 

  • Producing evidence of climate vulnerabilities of the urban poor, for setting priorities (most vulnerable first) and campaigning for more climate-resilient urban spaces.
  • Stimulating awareness and supporting advocacy with data.
  • Fostering low-cost local adaptation measures, to improve living quality in deprived urban areas.

Expected products and services

Open-source spatial models to estimate the population distribution, deprivation, and near-surface air temperature variations in DUAs, and the resulting maps and population exposure estimations. 

Potential users 

Community-based Organisations (CBOs), Non-governmental Organisations (NGOs), local policy makers, and international bodies (e.g., UN-Habitat).

Project leader(s): ULB - IGEAT - ANAGEO (Analyse Géospatiale)
Location: Country:
  • Kenya
  • Nigeria
  • Argentina

  • Mostly Nairobi (Kenya) and Lagos (Nigeria), with a small-scale experiment in a city of Argentina