The application of custom classiﬁcation techniques and posterior probability modeling (PPM) using Worldview-2 multispectral imagery to archaeological ﬁeld survey is presented in this paper. Research is focused on the identiﬁcation of Neolithic felsite stone tool workshops in the North Mavine region of the Shetland Islands in Northern Scotland. Sample data from known workshops surveyed using differential GPS are used alongside known non-sites to train a linear discriminant analysis (LDA) classiﬁer based on a combination of datasets including Worldview-2 bands, band difference ratios (BDR) and topographical derivatives. Principal components analysis is further used to test and reduce dimensionality caused by redundant datasets. Probability models were generated by LDA using principal components and tested with sites identiﬁed through geological ﬁeld survey. Testing shows the prospective ability of this technique and signiﬁcance between 0.05 and 0.01, and gain statistics between 0.90 and 0.94, higher than those obtained using maximum likelihood and random forest classiﬁers. Results suggest that this approach is best suited to relatively homogenous site types, and performs better with correlated data sources. Finally, by combining posterior probability models and least-cost analysis, a survey least-cost efﬁcacy model is generated showing the utility of such approaches to archaeological ﬁeld survey.