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A major component of the Joint Research Centre's TREES-II project is the assessment of deforestation rates in moist tropical regions for the period 1992 to 1997 using a statistical sample of fine spatial resolution satellite image pairs. It is widely recognized that spatial stratification can reduce the variance of estimates in spatial sampling designs. However, at the pan-tropical scale little reliable spatial information is available to stratify on the basis of deforestation rates. This paper describes a novel sampling scheme for assessing tropical deforestation rates. Stratification is performed using percentages of forest area (derived from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data) and areas of known deforestation activity (elucidated from expert consultation) estimated for each sampling unit. Sample site selection is performed by using a sample frame based on a tessellation of hexagons on a sphere. This approach allows for a sensor-independent sample from which unbiased estimators and error variance may be computed. The scheme is currently in the implementation phase for the tropical belt, but can be extended to the global scale.
Richards et al. (Sat,) studied this question.