Integrating CyberGIS and Urban Sensing for Reproducible Streaming Analytics

Shaowen Wang, Fangzheng Lyu, Shaohua Wang, Charles E. Catlett, Anand Padmanabhan, Kiumars Soltani

Research output: Chapter in Book/Report/Conference proceedingChapter


Increasingly pervasive location-aware sensors interconnected with rapidly advancing wireless network services are motivating the development of near-real-time urban analytics. This development has revealed both tremendous challenges and opportunities for scientific innovation and discovery. However, state-of-the-art urban discovery and innovation are not well equipped to resolve the challenges of such analytics, which in turn limits new research questions from being asked and answered. Specifically, commonly used urban analytics capabilities are typically designed to handle, process, and analyze static datasets that can be treated as map layers and are consequently ill-equipped in (a) resolving the volume and velocity of urban big data; (b) meeting the computing requirements for processing, analyzing, and visualizing these datasets; and (c) providing concurrent online access to such analytics. To tackle these challenges, we have developed a novel cyberGIS framework that includes computationally reproducible approaches to streaming urban analytics. This framework is based on CyberGIS-Jupyter, through integration of cyberGIS and real-time urban sensing, for achieving capabilities that have previously been unavailable toward helping cities solve challenging urban informatics problems.

Original languageEnglish (US)
Title of host publicationUrban Informatics
EditorsWenzhong Shi, Michael Goodchild, Michael Batty, Mei-Po Kwan, Anshu Zhang
Number of pages19
ISBN (Electronic)978-981-15-8983-6
ISBN (Print)978-981-15-8982-9
StatePublished - 2021

Publication series

NameThe Urban Book Series
ISSN (Print)2365-757X
ISSN (Electronic)2365-7588

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Urban Studies


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