This article explores movement data challenges in urban planning and public health, suggesting ways for improvement.
The increasing availability of movement data and rapid advancements in artificial intelligence have opened new frontiers in movement pattern analysis with implications for a wide range of domains such as urban planning, transportation management, public health, pandemic management, disaster response, and wildlife conservation. The sensitive nature and heterogeneity of novel movement data, however, create technical and methodological challenges around data governance and open movement analytics. This article explores these challenges and identifies key opportunities for the geography discipline to drive analytical advances in human mobility research and open science. In this vision, the geographic perspective is emphasized in future developments of artificial intelligence for movement research for its ability to enrich mobility analyses with spatial and temporal context. Strategies for effective governance of large-scale mobility data are discussed, with special attention to fostering open science and reproducible research practices to ensure transparency and transferability in this rapidly evolving field.
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Dodge et al. (2026) studied this question.
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