The study area consisted of the Congo Basin Forest Partnership countries: CAM, CAR, DRC, EQG, GAB, and RoC (fig. S4). To estimate forest loss area within this study region, we used a stratified sampling design, which typically yields better precision compared to simple random and systematic sampling designs (49, 55). Strata were selected to target forest cover loss (fig. S4) with the three strata defined as follows: (i) “Loss,” any pixel that was mapped as forest loss during 2001 to 2014 where forest loss was determined from the global forest loss map [Hansen et al. (14)]; (ii) “Probable loss,” 60-m (two Landsat pixels) buffer around mapped loss; (iii) “No loss,” all other areas outside of mapped loss and the probable loss buffer (including both forested and nonforested areas). The sampling unit was one Landsat pixel (circa 30 m by 30 m); the mean pixel area within the study region in geographic coordinates (latitude/longitude) was 766.13 m2. The variation of mean pixel area among the countries did not exceed 0.2% and was therefore ignored. The total number of sample pixels was 10,000, with 20% of the sample randomly allocated to the “Loss” stratum, 30% to the “Probable loss” stratum, and 50% to the “No loss” stratum. Pixels were allocated to the three sampling strata regardless of country boundaries. Countries were treated as poststrata in the area calculations. The resulting distribution of sample pixels among the countries (poststrata) and three sampling design strata is shown in table S5.

Estimation of area from the sample was performed using indicator functions (56), since this approach works when the sampling strata are different from the map classes and can also be used for the nonbinary (proportional) reference sample labels (in our case, 0, 50, and 100% forest loss). Forest loss area for each reference forest loss type (by disturbance driver, by predisturbance forest type, and by year), reported in table S2, was estimated using the following equationEmbedded Image(1)where Atot is the total study region area, N is the total number of pixels in the study region, H is the number of poststrata (18, see table S5), nh is the sample size (number of sampled pixels) in poststratum h, Nh is the total number of pixels in poststratum h, yu is 1 or 0.5 if pixel u (or its half) is classified as “forest cover loss” in the reference sample interpretation and yu is 0 otherwise, and Embedded Image is the sample mean of the yu values in poststratum h.

To produce forest loss area estimates by disturbance driver, predisturbance forest type, and year, the definition of yu is modified so that 1 or 0.5 is recorded only if the loss area represents the specified disturbance driver, predisturbance forest type, or year targeted by the estimate, and yu = 0 if there is no forest cover loss or the sampled pixel u does not satisfy the definition of the target subset. The SE of the sample-based loss area estimate isEmbedded Image(2)where Embedded Image is the sample variance for poststratum h.

When estimating the relative contribution of each loss driver, forest type, or country to the total area of forest loss, expressed as percentage, both numerator and denominator are estimated from the sample, resulting in a ratio estimator. Other examples for which a ratio estimator is required include the estimates of contribution of each country to the total area of forest loss of each driver, and the estimates of the contribution of each loss driver to the total area of forest loss of each forest type. The combined ratio estimator for stratified random sampling (57) was therefore used to estimate these percentages, reported in ResultsEmbedded Image(3)where yu = 1 or 0.5 if pixel u (or its half) is classified as belonging to a specific driver, forest type, or country in the reference sample interpretation, and yu = 0 otherwise; xu = 1 or 0.5 if pixel u (or its half) is classified as forest cover loss in the reference sample interpretation, and xu = 0 otherwise; Embedded Image is the sample mean of the yu values in poststratum h; and Embedded Image is the sample mean of the xu values in poststratum h.

The SE of the combined ratio estimator isEmbedded Image(4)where Embedded Image is the estimated total area of tree cover loss expressed in pixels, Embedded Image and Embedded Image are the sample variances in poststratum h, and Embedded Image is the sample covariance in poststratum h.

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