1. A method for characterizing in-ground rock types from measurement-while-drilling data in a mining environment, comprising: drilling holes at a plurality of selected locations within a region of interest; collecting measurements-while-drilling; determining from the collected measurements an array of characteristic measures indicative of rock hardness at various drilling depths in the drill hole locations; applying the array of characteristic measures to a Gaussian process with a selected covariance function to generate a Gaussian process model with optimized hyperparameters; sampling the Gaussian process model by performing Gaussian process regression at a selected spatial resolution within the region of interest; and applying boundary detection to rock hardness output data obtained from the sampling of the Gaussian process model to identify the distribution of at least one cluster of rock type within the region of interest.