Cities across sub-Saharan Africa and South Asia are expanding faster than official data can track. Transport planners and development institutions face:
- Incomplete road inventories: Formal road network datasets are often years out of date, with informal and peri-urban roads absent from official records.
- Rapid and unplanned urban growth: New settlements appear outside official boundaries, leaving planners with an inaccurate picture of where people live and how they move.
- High cost of ground surveys: Traditional field-based data collection is too slow and expensive to keep pace with rapid urban change across large areas.
- Invisible mobility patterns: Informal transit, night-time movement, and population distribution are largely absent from official statistics.
- Climate exposure without a baseline: Roads and transport networks in climate-vulnerable regions lack condition and exposure data, making it hard to prioritise resilience investments.
How EO can help
Satellite imagery and derived data products can fill these gaps at a fraction of the cost of ground surveys:
- Road network mapping: High-resolution optical and SAR imagery can generate up-to-date road inventories, including informal tracks not in official datasets.
- Urban growth tracking: Sentinel-2 time-series captures where and how fast cities are expanding, helping planners anticipate future transport demand.
- Travel-time estimation: Satellite-derived road network data feeds into transport models for demand analysis and accessibility planning.
- Population and mobility analysis: Night-time light data (e.g. VIIRS) and satellite-derived population density layers reveal where people live and how they move, particularly in areas with limited census coverage.
- Infrastructure risk assessment: EO-based flood mapping and land-surface monitoring supports climate risk analysis for road networks in exposed corridors.
Key examples
1- Transport modelling in Dhaka, Bangladesh
An ESA-funded project used satellite EO to build a macroscopic transport demand model for Dhaka, covering 161 traffic analysis zones. EO-derived land use and population data were integrated with the model to map where trips are generated and where they are likely to go. The outputs supported the ADB’s Revised Strategic Transport Plan update for one of the world’s most congested urban environments.
Figure: Dhaka Land Use/Land Cover (© GISAT, EO4SD-Urban) and Population Density (© DLR, GDA Urban)
2- Road mapping and urban growth tracking in Lubango, Angola
In Lubango, EO supported an ESA-World Bank collaboration to produce a road network inventory, travel-time estimates from key locations such as markets and schools, and urban growth mapping using Sentinel-2 imagery from 2016 to 2024. The work filled data gaps for transport and land use planning in a city where conventional surveys were not feasible. Outputs fed into the World Bank’s Angola Urban Sustainable Mobility Project.
Figure: Main road network detection 2024, Lubango
3- Urban Mobility Plan for Chisinau, Moldova
An ESA project contributed EO and data analysis to support Chisinau’s Urban Mobility Plan. EO-derived night-time population distribution was combined with telecom mobility data from Orange Moldova to map how people move across the city. The analysis identified public transport accessibility gaps that were not visible in official transport statistics.
Figure: Night-time population density estimates shown as heatmap for the year 2018 over a part of Chișinău municipality. Credits: GeoVille/SIRS for ESA/UNDP.
4- Urban master plan assessment in Tanzanian cities
EO mapping was used across seven Tanzanian cities to support a World Bank urban planning study. Satellite-derived products covered land use, transport infrastructure, informal settlements, urban extent, and population distribution. A comparison against existing master plans found a 35-45% gap between planned and actual land use, giving planners a factual basis for updating infrastructure strategies.
Figure: Satellite-based land use mapping supporting the assessment of the effectiveness of urban master plans. Left: Existing 1985 master plan of Arusha, Tanzania; Centre: land use classification for 2015 produced in the EO4SD-Urban project; Right: the diversion of the actual land use form the proposed land use.
Further resources
Related ESA-funded projects:
