Timor-Leste faces growing climate-related challenges that affect crops, food production and public health. Shifting rainfall patterns are increasing climate stress on rain-fed agriculture and contributing to the spread of diseases such as dengue. At the same time, high rural dispersion, exposure to floods and droughts, and limited health system capacity heighten vulnerability. With sparse ground-based monitoring and incomplete administrative data, national authorities and development partners often lack the consistent, spatial evidence needed to anticipate risks, plan effectively, and target interventions.
EO uptake with the World Bank in Timor-Leste
To close this evidence gap, the European Space Agency’s (ESA) Global Development Assistance (GDA) Public Health team collaborated with the World Bank to co-develop a suite of Earth Observation (EO) products tailored to Timor-Leste’s health, agriculture and climate resilience priorities. Delivered by Diginove and BSC as part of the GDA Public Health consortium, the services integrate multi-year satellite data, climate reanalysis and population analytics to show where vulnerabilities are concentrated, how they are evolving, and where investments can reduce long-term risk.
The EO services were designed through close collaboration with specialists across the World Bank’s health, nutrition and disaster resilience teams. Their operational needs shaped each analytic layer so that the outputs can directly support risk assessment and decision-making. As a result, EO tools provide a practical spatial complement to the World Bank’s evidence base, especially in areas where ground data are scarce or inconsistent.
Where the EO services are used: health, agriculture, risk planning
The initiative contributes to the World Bank’s growing climate–health and food security engagements in Timor-Leste and offers a replicable example for the wider East Asia and Pacific region. By providing reliable, spatially explicit datasets, the EO services strengthen risk assessment and help identify priority locations for action, including:
Health system preparedness
Linking dengue case data with rainfall seasonality shows a clear lag between rainfall and case surges, supporting anticipatory early warning and targeted vector control.
Agricultural resilience
Vegetation and moisture indices highlight recurrent dry-season crop stress, helping pinpoint priority areas for irrigation, crop diversification and food security interventions.
Urban and climate risk planning
Land-use change analysis shows expanding urban and cropland areas, including where natural ecosystems are declining, informing flood risk management and nature-based solutions.
Population-based resource allocation
High-resolution population maps identify underserved rural communities, guiding investments in health, education and emergency response.
Together, these elements give decision-makers a consistent, data-driven foundation for climate adaptation and public health strategies.
What the EO services deliver: four analytical layers
Land change hotspots: cities, cropland and ecosystems under pressure
Using multi-year satellite imagery, the team mapped land change in Timor-Leste between 2016 and 2024. The analysis shows expanding urban areas and cropland encroaching on natural grasslands and forests. These patterns indicate increasing pressure on ecosystems and help highlight zones vulnerable to floods and erosion. By pinpointing where land is changing fastest, authorities can plan more targeted interventions for urban resilience, environmental protection and climate-smart development.
Population mapping: locating underserved communities
High-resolution population mapping provides an updated picture of where people live, particularly in rural areas with limited access to essential services. By combining satellite-detected settlements with census and demographic models, the team produced refined population density layers. These maps support more precise identification of underserved communities and better targeting of health, education and emergency services.
Crop and drought signals: monitoring stress with Sentinel-2 indices
Using vegetation and moisture indices derived from Sentinel-2 satellite data, the project tracks crop health and drought stress across the country. While agriculture is largely stable, the analysis reveals recurring dry-season stress in vulnerable regions. This enables seasonal planning and earlier, more targeted food security measures before crises emerge.
Climate–disease links: rainfall patterns and dengue risk
The EO services also connect environmental conditions with public health outcomes. For dengue, rainfall seasonality emerges as a key driver, with a clear lag between rainfall and case surges. This insight supports early-warning approaches and pre-emptive vector control. In addition, the analysis indicates low current risk of malaria reintroduction due to declining cases in neighbouring Indonesia, helping focus attention on the most immediate health priorities.
Making the approach usable: workflows, open tools and scale-up
A core focus is to ensure the EO workflows can be understood, integrated, replicated and scaled within World Bank operations, especially for audiences less familiar with complex spatial analytics. Open-source tools, transparent methods and modular processing chains enable national users and development partners to:
- interpret and validate EO health and agricultural indicators
- integrate them into monitoring or early-warning systems
- replicate and scale the workflows to additional administrative areas or neighbouring countries
- adapt the methods to future World Bank projects and evolving analytical needs
This approach supports long-term usability and helps extend the value of the work beyond a single case study.
From pilot to mainstreaming: feeding into the Climate and Health Vulnerability Assessment
In Timor-Leste, the analytics developed with support from the GDA Public Health activity are directly applied. They feed into the ‘Timor-Leste Climate and Health Vulnerability Assessment’ (CHVA), which is set to be published in the first quarter of 2026. The CHVA combines EO with economic, service delivery and burden of disease analytics to provide a nationwide assessment of how climate change scenarios may affect health outcomes, health systems and growth, linking closely to the World Bank’s jobs agenda. The EO analytics play a key role in identifying spatial risk hotspots and priority areas for targeted policy and investment pathways to strengthen health-system resilience and protect human capital.
Because the approach relies on global open datasets, Copernicus Sentinel missions, ERA5 climate reanalysis and OSM, the same workflows can be applied worldwide at low cost. The Timor-Leste case serves as proof of concept for wider uptake in the region and beyond. Interest has already emerged in applying similar EO-based population analytics to improve health facility geodata quality across low-resource settings, including in Sub-Saharan Africa.
Key takeaways
⭢ ESA and the World Bank co-developed EO services to support climate–health, agriculture and population-based planning in Timor-Leste.
⭢ Multi-year EO analysis highlights key risks, including expanding urban corridors, recurrent dry-season crop stress and a strong rainfall–dengue transmission relationship.
⭢ Updated population density maps strengthen vulnerability assessments and help improve service planning in rural areas.
⭢ Open-source, globally available datasets enable replicability across Southeast Asia, the Pacific and Africa.
⭢ EO tools strengthen transparency, data-driven decision-making and climate–health preparedness where ground observation data are limited.
