The project will develop Coffee Vision, a smart monitoring tool to support the certification of sustainable coffee plots in Vietnam. For the first time the precise location of coffee plots will be identified remotely and, past and present coffee driven deforestation will become radically more visible, and areas of future risk will be identified.
The project leverages satellite imaging and the latest research and developments in Machine Learning (e.g., the use of convolutional neural networks) to identify coffee plots down to smallholder level, including identifying the presence or absence of shade trees and other agroforestry systems. This is overlaid with a detailed history of deforestation to pinpoint coffee driven deforestation and climate projections are used to highlight forests at risk of conversion to coffee in the future.
Coffee Vision will help stop coffee-driven deforestation and thus protect important carbon sinks by reducing the cost and increasing the robustness of third-party certification systems. Noncertified supply chain operators will have an economically viable way to identify suppliers with low risk of deforestation. As costs are reduced, more farmers will be able to participate in higher-value markets for verified coffee beans and more coffee farms will operate in a sustainable way.
Existing standards for shade trees and agroforestry best practice will be remotely monitored and effectively managed for a large climate resilience and carbon sequestration benefit. As climate change alters the growing conditions for coffee, coffee suitability maps based on climate projections will allow intervention prior to deforestation in at-risk areas. Thus, both mitigating and sustainable adaptive measures can be enhanced.