Terrain analysis has been a powerful tool for predicting soil properties.  This study was conducted to determine optimal grid resolution for predicting multiple soil properties in a low relief landscape. Multiple primary and secondary terrain attributes were created from a high accuracy Digital Elevation Model (DEM).  Regression was then used to determine the grid resolution at which specific attributes best predict soil properties.  The variance explained by the model ranged from 23% to 70% by changing the grid resolution alone.  Prediction of some properties was not affected by grid resolution.  The statistical significance of terrain attributes varied at different grid resolutions.  Relief is an important contributor to processes that modify the landscape and must be considered when attempting to model those changes.