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HFLD Research | Technical Report: Predicted Deforestation Rates Statistical Modeling
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HFLD Research | Technical Report: Predicted Deforestation Rates Statistical Modeling

Singapore’s National Climate Change Secretariat (NCCS) commissioned Sylvera to undertake statistical modeling work for predicting deforestation rates for HFLD jurisdictions.

This summary presents the findings and implications of this work.

The number of HFLD jurisdictions has declined over time. Our research shows that the number of jurisdictions meeting HFLD status has decreased over time, and those that have lost their status show accelerating deforestation rates.
The historical average fails to capture forward-looking risk. The classic JREDD baseline approach is unable to capture observed spikes in deforestation and therefore cannot predict elevated risk for jurisdictions where deforestation has not historically been high.
Country-specific and spatially-explicit models are needed for improved accuracy. The variation in performance across models indicates that country-specific approaches may be necessary for more accurately predicting deforestation rates at the individual jurisdiction level.

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Sylvera, in partnership with Singapore's National Climate Change Secretariat (NCCS), has developed a global statistical model for predicting deforestation rates in High Forest Low Deforestation (HFLD) jurisdictions.

This technical paper breaks down the approach and findings in detail.

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