Abstract
Three sampling designs — simple random, stratified random, and systematic sampling — are compared on the basis of precision of estimated loss of intact humid tropical forest area in the Brazilian Legal Amazon from 2000 to 2005. MODIS-derived deforestation is used to partition the study area into strata to intensify sampling within forest clearing hotspots. The precision of the estimator of deforestation area for each design is calculated from a population of wall-to-wall PRODES deforestation data available for the study area. Both systematic and stratified sampling yield smaller standard errors than simple random sampling, and the stratified design has smaller standard errors than the systematic design at each sample size evaluated. The results of this case study demonstrate the utility of a stratified design based on MODIS-derived deforestation data to improve precision of the estimated loss of intact forest area as estimated from sampling Landsat imagery.