In today’s gradually connected world of virtual, perceived, and real spaces, data-driven urban computing and analytics have become increasingly essential for the understanding of coupled human and socioeconomic dynamics. The complexities of such systems and their connectivity at various spatial, temporal, and semantic scales have posed daunting challenges to urban researchers. Due to the rapid progress of information and communications technology, the emergence of big data available from various sources has presented significant opportunities for urban studies. Rigorous analysis of such data depicting complex socioeconomic events is likely to open up a rich context for advancing urban sciences and policy interventions. Interdisciplinary approaches combining with rich spatial data are urgently needed to ignite transformative geospatial innovation and discovery for enabling effective and timely solutions to challenging problems. This book chapter highlights the challenges and opportunities of a synthesized urban science based on ever-increasing amounts of large-scale diverse data and computing power.
CITATION STYLE
Ye, X., Li, W., & Huang, Q. (2018). A Synthesized Urban Science in the Context of Big Data and Cyberinfrastructure. In Advances in Geographic Information Science (pp. 435–448). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-51929-6_22
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