Advancing Predictive Modeling in Archaeology - Supplementary Data

The data provided here(Yaworsky_etal_2020_sdmdata.csv) accompany a set of archaeological predictive models created for the Grand Staircase-Escalante National Monument, Utah. The full dataset is comprised of 11,814 observations (1,619 presence points and 10,195 absence points), and ten predictor variables. Column 1 is a unique ID. Column 2 is a binary identifier of whether an observation represents an archaeological site/presence point (1) or pseudo absence point (0). The remaining columns represent environmental predictor values at presence and absence points extracted from spatial raster data. These include a decomposed east-west aspect (3), growing degree days (4), a decomposed north-south aspect (5), net primary productivity (6), mean annual temperature (7), slope (8), cost-distance to springs (9), cost-distance to streams (10), cost-distance to wetlands (11), and wastershed size (12). Detailed information about these data and how they were generated can be found in the Supplementary Information (S.I.) of the published paper. The S.I. is a markdown document (.html) that walks through the analysis covered in the published paper. The primary findings can be replicated using the data provided here.