Payments for Ecosystem Services (PES) schemes have recently become an important tool in environmental governance. In a typical scheme, landowners (PES sellers) receive payments to manage ecosystems and the services that they provide in a beneficial way. Payments are usually made by governments or by interested private sector stakeholders (PES buyers). A prominent example of PES are carbon sequestration payments, which incentivize forest owners to keep forests intact to store the sequestrated CO2 (e.g. the UN REDD program). Another example are wildlife conservation incentive payments, which reward landowners for maintaining biodiversity. In locations where the rule of law is not upheld and the banking infrastructure is poor, PES schemes can corrupt and the payments sometimes fail to reach the addressees. The efficiency and effectiveness of such programs is then undermined and they cannot reach their full potential.
The value of the cryptocurrency Ether will maintain its current stability and the Ethereum blockchain will therefore be maintained.
The application programming interfaces (APIs) that we use will persist.
Potential end users are willing to use the product.
The added value of our solution lies in jointly addressing two big barriers of PES in developing countries: First, the efficiency of such PES schemes is undermined by inadequate payment channels that are either subject to high transaction costs or corruption. Second, the effectiveness of PES schemes is undermined because it is expensive to adequately monitor environmental performance. We improve PES efficiency by using Ethereum smart-contracts as payment channels. Ethereum smart-contracts are tamper-proof and will execute the contract code in any circumstance. This allows for the direct and incorruptible transfer of funds from e.g. an ecosystem services buyer in the global North to a recipient in the global South. We also improve PES effectiveness by integrating remote sensing algorithms into our application. This allows for automating the monitoring, thereby making payments conditional upon achieving predefined environmental targets on the ground.
We have already developed a proof-of-concept of an Ethereum smart contract that interacts with remote sensing algorithms on the Google Earth Engine Python API. We now want to build a prototype that is tailored to our example use case, the wildlife corridors in rural Namibia. Therefore, we need to refine the back end, including the actual smart-contract as well as the remote sensing algorithms. Finally, we want to build a front end for convenient interaction.