For implementing entities managing climate adaptation projects across large and varied geographies, monitoring what is actually changing on the ground is one of the most persistent operational challenges. Climate funds expect results, and those results need to be evidenced consistently, independently and at scale. Earth Observation (EO) can provide that evidence, but its value depends entirely on how well the support is designed around the realities of project implementation.
The ESA GDA Climate Adaptation and Finance (CA&F) consortium is working with the Sahara and Sahel Observatory (OSS) to co-design an EO demonstrator for RICOWAS, an Adaptation Fund-financed project working with around 125,000 farmers across 13 countries to scale climate-resilient rice production in West Africa. This story follows that collaboration and what it is beginning to reveal about the integration of EO into climate finance more broadly.
Monitoring adaptation outcomes across 13 countries
Across West Africa and the Sahel, smallholder farmers are absorbing the front-line shocks of a changing climate. Rice production systems are shifting under unpredictable rainfall and rising temperatures, and the pressure on already fragile food systems is growing. RICOWAS responds to this by promoting the System of Rice Intensification (SRI), a set of agronomic practices designed to increase rice productivity, reduce water and seed consumption, and improve the sustainability of production systems across 13 West African countries. Effective monitoring and evaluation is one of the most persistent challenges in projects operating at this scale and across this diversity of contexts. Without consistent evidence that rice yields are genuinely improving, that environmental co-benefits are being realised, and that expansion into fragile habitats is not creating new risks, it is hard to demonstrate results to funders, hard to course-correct, and hard to make the case for the next round of climate finance. EO can help close that gap, by providing consistent, objective, repeatable data over time and at scale. The question for the ESA GDA CA&F activity is how to make that support genuinely useful: sized to real implementation timelines, anchored in the data partners already hold and fit for the operational team doing monitoring and reporting on the ground.
Identifying where EO can add value to a live project
OSS has, since 1992, supported African member states in managing natural resources under increasingly difficult climate conditions. Accredited to both the Adaptation Fund and the Green Climate Fund, it implements multi-country adaptation projects across some of the continent’s most climate-vulnerable landscapes, making it well placed to test how EO support can be integrated into projects already in motion.
Working with Environment Systems and Argans under the ESA GDA CA&F activity, OSS identified RICOWAS as the focus for an EO demonstrator. The planned approach centres on progressing towards a blended method, bringing geolocated ground data and open-source satellite imagery together to strengthen monitoring and evaluation. Time series of Sentinel-1 and Sentinel-2 data will be used to map rice areas to enable future assessment of productivity differences between SRI and conventional plots, with additional datasets covering climate vulnerability, land cover, and conservation status to identify any unintended consequences, such as encroachment into protected natural areas. Mapped outputs and workflows for a demonstration area are planned, together with guidance on technical considerations for OSS to develop a dashboard around what operational and programme management teams actually need.
Defining the scope of that support has proved more complex than anticipated, for two reasons. The first is the diversity of rice production systems across the RICOWAS footprint. The project spans five bioclimatic regions, from mangrove rice systems in the tropical forest environments of Senegal, Guinea, and Sierra Leone, to large-scale irrigated systems in the Sahel, to rainfed
lowland and upland systems across the Sudanian zone, to specialty systems such as deep-water and recession rice along the Niger River. Mapping rice productivity meaningfully across that range requires a different approach in each context.
The second is a data problem common to projects of this kind. National partners often collect ground data on rice production (such as planting dates and yield records) but the locations are not precisely geolocated. This means the data cannot be directly linked to satellite imagery. Without that anchor, EO indices cannot be attributed to specific fields or farming practices. Establishing what geo-referenced information national partners can actually provide has therefore been a central part of the work to date and has shaped a shift toward mapping outputs for a demonstration area rather than a full-scale analysis across all 13 countries.
Bringing national partners into the collaboration
In April 2026, OSS and the ESA GDA CA&F consortium held a webinar for around 40 participants, including RICOWAS National Executing Entities from across West Africa and representatives from ESA. Rather than presenting a finalised approach, the session was structured as a working consultation: explaining why systematic monitoring and evaluation matters for in-country actors, presenting the EO methods under consideration, and surfacing the data gaps and practical constraints that will shape what is deliverable.
The consultation confirmed a pattern familiar from projects of this kind: monitoring data exists, but is largely held in spreadsheets and has not been geolocated. To begin bridging that gap, a bespoke data collection form has been developed to help national partners transition locally held records into a spatial dataset, capturing field locations, project zone boundaries, and associated agronomic information in a format that can be linked to satellite imagery. National Entities have responded, and whilst ground data was not available in time to support the ESA rice mapping demonstrator, OSS are now receiving good quality geolocated data within their RICOWAS project zones. Mapping rice without ground verification involves creating training and validation points for a range of land cover types (and if possible differing crops) from visual interpretation of open source data such as Sentinel satellite and derived products such as ESA’s WorldCover
What this engagement is beginning to reveal about integrating EO into climate finance
The demonstrator will focus on showing what an EO-supported monitoring and evaluation system would comprise in practice: the data dependencies, the mapped outputs, and the role of a blended ground and satellite-based approach. Rather than attempting to cover all 13 countries, the initial work will go deep in a particular area and rice growing context, with transferability to other rice systems representing a substantial piece of future work given the diversity of production systems across the region.
Central to that system is how data is collected, shared, and made accessible throughout the project lifetime. Dashboards and data platforms make EO more useful not simply by visualising outputs, but because they encourage the early, standardised gathering of project data. That data supports EO analysis by providing vertification, and helps ensure that satellite-derived products map meaningful elements at the right scale, whether individual fields, irrigated units, or project zones. Operational teams can explore their own ground data and EO outputs for their locality, while programme managers can work with results at scale, identify anomalies, and make adaptive decisions during the project rather than drawing lessons only at its end.
The longer-term value for OSS lies less in the localised data outputs the demonstrator produces than in what it leaves behind: a range of outputs and workflows that show how EO can be built into monitoring and evaluation from the outset. The aim is to equip OSS to plan EO-integrated M&E when applying for funding for further work, whether on rice or other crop-focused adaptation projects, so that the approach becomes a repeatable foundation for future bids.
