Transformations of urban studies and planning in the big/open data era: a review. (1st October 2016)

• Record Type: Journal Article
• Authors: Long, Ying; Liu, Lun
• Is Part Of: International journal of image and data fusion. Volume 7:Number 4(2016)
• Page Start: 295
• Page End: 308
• Publication Date: 2016-10-01
• Subjects: Big data -- open data -- urban planning -- mega-model -- crowdsourcing; Image processing -- Periodicals; Multisensor data fusion -- Periodicals; Multisensor data fusion; Periodicals; 621.36705
• DOI: 10.1080/19479832.2016.1215355
• Languages: English
• ISSNs: 1947-9832

Abstract

ABSTRACT: As the emergence of big/open urban data in recent years, there have been lots of transformations going on in urban study and planning. In this article, we aim to provide a review of the major trends in this round of transformation. The review is started with a brief introduction to the new data environment, which has been made possible by the availability of big data and open data in recent years, as well as a review on the research progress in China, a developing country recently embracing the technology and data boom. It is followed by an analysis on the four major trends in quantitative urban study, supported by typical research cases. The four trends are (1) transformation in spatial scale from high resolution but small coverage or wide coverage but low resolution to wide coverage with high resolution, (2) transformation in temporal scale from static cross-sectional to dynamic consistent, (3) transformation in granularity from land-oriented to human-oriented and (4) transformation in methodology from conventional research group to crowdsourcing. The paper also points out that quantitative urban research is faced with problems like data bias, lack of long-term analysis, lack of linkage to planning practice etc.