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Big Data, originating from the digital breadcrumbs of human activities, let us observe the individual and collective behaviour of people at an unprecedented detail. In this paper we investigate the informative potential of the digital tracking that GPS-enabled devices can offer to academic research and to policy makers, with a specific attention for urban and metropolitan settings. The unstructured nature of the dataset requires a careful consideration and correction of possible biases which could lead to unreliable results. We use the 2011 census commuting matrix as a validation tool for our proposed methodology. GPS data contain information that would not be otherwise available, i.e. non-systematic mobility patterns. The produced estimates are then used to analyse mobility patterns within the Florence Metropolitan Area in a more exhaustive and detailed form.