Seasonal urban carbon emission estimation using spatial micro Big Data

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

研究成果: Article査読

9 被引用数 (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.

ジャーナルSustainability (Switzerland)
出版ステータスPublished - 2018 11月 28

ASJC Scopus subject areas

  • 地理、計画および開発
  • 再生可能エネルギー、持続可能性、環境
  • 環境科学(その他)
  • エネルギー工学および電力技術
  • 管理、モニタリング、政策と法律


「Seasonal urban carbon emission estimation using spatial micro Big Data」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。