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This article discusses the sampling scheme employed by the Six Cities project to ensure that all areas of habitation have a chance of being selected, that we know what that chance is, and that we are able to critically evaluate the sampling strategy after it has been carried out. A weighting strategy that is slightly different from one used only to do research is therefore employed. The article describes a procedure for generating two kinds of random sample points for areas of change and of no change. Finally, a few simple rules for incorporating socioeconomic, demographic, and other relevant information into the sampling frame without introducing bias into the sample are discussed. Key words: sampling strategies; random sampling; sampling bias; local knowledge; Six Cities project; remote sensing; urban areas in Africa

Development of Sampling Procedures Based Upon Satellite Derived Land Cover History for the NSF Digital African Cities Project