A new Monte Carlo simulation tool for designing an archaeological landscape sampling strategy

This article describes in detail how the Dig It, Design It (DIDI) simulation tool operates to design a subsurface landscape sampling strategy and predict its likely effectiveness. The purpose of the DIDI model is to help archaeologists develop statistically sound subsurface sampling programs that maximise the number of sites found while minimising the number of sampling units used. It has been unusual for archaeological test-pitting programs to be theoretically tested or statistically justified by simulation prior to implementation. Previous research by Kintigh (1988) and Krakker et al. (1983) established the statistical principles underlying the subsurface sampling of a rectangular survey area, and Kintigh pioneered the use of Monte Carlo simulations to test the effectiveness of these sampling strategies. DIDI provides an updated version of this simulation approach that has three key benefits over the original version: 1. It allows the user to model a larger range of possible archaeological conditions by providing an additional density distribution function (see below), and making the clustering parameter available with all distribution functions; 2. DIDI gives the user the option of filling the previously unavoidable gaps around the edges of the survey area with additional, suitably placed test-units, thereby increasing the detection rate of a sampling strategy; and 3. It is free to download and use and is compatible with modern operating systems.