Seasonal urban carbon emission estimation using spatial micro Big Data

Yoshiki Yamagata, Takahiro Yoshida, Daisuke Murakami, Tomoko Matsui, Yuki Akiyama

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


The objective of this study is to map direct and indirect seasonal urban carbon emissions using spatial micro Big Data, regarding building and transportation energy-use activities in Sumida, Tokyo. Building emissions were estimated by considering the number of stories, composition of use (e.g., residence and retail), and other factors associated with individual buildings. Transportation emissions were estimated through dynamic transportation behaviour modelling, which was obtained using person-trip surveys. Spatial seasonal emissions were evaluated and visualized using three-dimensional (3D) mapping. The results suggest the usefulness of spatial micro Big Data for seasonal urban carbon emission mapping; a process which combines both the building and transportation sectors for the first time with 3D mapping, to detect emission hot spots and to support community-level carbon management in the future.

Original languageEnglish
Article number4472
JournalSustainability (Switzerland)
Issue number12
Publication statusPublished - 2018 Nov 28
Externally publishedYes


  • Carbon mapping
  • Individual buildings
  • Micro geodata
  • Mobile GPS data
  • Person-trip survey
  • Urban sustainability

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Environmental Science (miscellaneous)
  • Energy Engineering and Power Technology
  • Management, Monitoring, Policy and Law


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