Use Case Description
Results-Based Climate Finance (RBCF) disburses funds not for activities (e.g. buying seedlings) but for verified outcomes (e.g. tons of carbon sequestered or hectares of forest preserved). Earth Observation (EO) supports this mechanism by providing the independent, objective, and scalable data needed to prove these outcomes were, in fact, achieved.
The first step in this is baseline setting. Whereas in the past baselines were established through manual surveys and rough estimates, an EO-supported approach draws on decades of archival imagery to establish a “business-as-usual” baseline, ensuring that payments reflect true additionality. During the monitoring phase, EO has supplanted traditional, expensive, and error-prone field surveys in favour of continuous, inexpensive, and reliable monitoring with high revisit times. In the verification phase, algorithms instantly process the relevant imagery and can verify payment triggers, drastically reducing transaction costs and time-to-payment.
Establishing these systems in developing countries, however, requires extensive technical support. A first step for national-level applications may involve establishing systems so countries can claim payments autonomously, e.g. in the case of REDD+ by being able to generate UN-compliant deforestation reports using EO data. At the level of individual climate-affected economic actors, parametric or index-based insurance is the most mature kind of RBCF, where the data flow from satellite to algorithm to verification and eventually the payment trigger is automated to a very high degree. When a satellite-derived index crosses a specific threshold, or an extreme natural hazard event (flood, drought, cyclone, earthquake) is verified through EO data, the holder of a smart, often blockchain-based contract receives the payment. In this context, the “result” is resilience to climate-induced hardships or other force majeure events. Leveraging the possibilities EO offers thus helps ensure that climate finance is used effectively to meet global climate mitigation and adaptation targets.
