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Similar to every process involving quantitative research, the study of migration heavily depends on the data available for analysis. The available movement data limit the type of questions that can be asked, and as a result, certain aspects of human spatial mobility have yet to be examined. The development of information and communication technologies and their widespread adoption offers new datasets, methods and interpretations that make it possible to study social processes at a new level. For example, mobile positioning data can aid in overcoming certain constraints embedded in traditional data sources (such as censuses or questionnaires) for study of the connections between daily mobility and change of residence. This study presents a framework for mapping changes of residence using data from passive mobile positioning and an anchor point model to better understand the limits of these methods and their contribution to understanding long-term mobility. The study concludes that the most important considerations in monitoring change of residence using passive mobile position data include the continuity of the time-series data, the varying structure of the mobile tower network and the diversified nature of human mobility. The fine spatial and temporal granularities of passive mobile positioning data allow us to study human movement at a detailed scale.
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Stored only when both papers are in the corpus — 18 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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