Dr. Josh Gray and fellow NC State Department of Forestry and Environmental Resources (FER) faculty member Dr. Erin Sills have been working together to better understand how effective (or not) tropical deforestation mitigation efforts have been. Dr. Sills has been pioneering the application of Synthetic Control Methods (SCM) to understand the effect various policies have had on the rate of deforestation throughout the tropics. SCM is a statistical attempt to deal with the problem of not having “control” units. When it comes to a particular deforestation mitigation policy, we may be able to observe whether more or less forest was removed after enacting the policy, but since we have no control Earth, we can’t be positive that gains/losses were a consequence of the policy or some other factor (e.g., the price of timber changing). SCM works best when there is a long record including substantial observations before and after the treatment (in this case, enacting a particular policy). Satellite remote sensing has been critical in providing such time series, but there are substantial challenges in the tropics. The biggest problems are persistent cloud cover and image spatial resolutions that are too coarse to accurately quantify forest change. Satellite imagers that observe the same area often enough to glimpse the surface on rare cloud-free days have pixels that are too large. Sensors that have the requisite spatial resolution do not see the surface very often (e.g., some pixels in Borneo are only seen 1-2 times a year by Landsat). Dr. Gray has been developing data fusion methods that combine the best of both worlds. These methods create synthetic image time series that are cloud and gap free; providing the foundation for establishing reliable records of forest change that are long enough to use SCM methods to understand the effects of various policies. Gray and Sills have piloted this technique in Borneo where preliminary results indicate that the granting of timber concessions has reduced the rate of deforestation. Read more about that work.