Urban carbon mapping with spatial BigData

Yoshiki Yamagata; Daisuke Murakami; Takahiro Yoshida

doi:10.1016/j.egypro.2017.12.183

Urban carbon mapping with spatial BigData

Yoshiki Yamagata, Daisuke Murakami, Takahiro Yoshida

Research output: Contribution to journal › Conference article › peer-review

9 Citations (Scopus)

Abstract

The objective of this study is mapping carbons utilizing spatial BigData relating buildings and transportations. Regarding buildings, number of storeys, composition of use (e.g., residence and shops), and area of individual buildings are considered. Difference of hourly emission intensity from residence, commercial buildings, firms, and so on, also considered. Regarding transportations, vehicle location by one minutes are considered to capture dynamic fluctuation of transportation behavior. CO₂ emissions from individual buildings and road links in Sumida, Tokyo, Japan, are estimated by 30 minutes by a bottom-up approach. The results are visualized in a 3D manner. The result suggests the usefulness of our carbon mapping approach to detect hot spots, abnormal emissions, and so on, that helps efficient carbon management.

Original language	English
Pages (from-to)	2461-2466
Number of pages	6
Journal	Energy Procedia
Volume	142
DOIs	https://doi.org/10.1016/j.egypro.2017.12.183
Publication status	Published - 2017
Externally published	Yes
Event	9th International Conference on Applied Energy, ICAE 2017 - Cardiff, United Kingdom Duration: 2017 Aug 21 → 2017 Aug 24

Keywords

carbon mapping
individual buildings
LiDAR
micro-geo data
person-trip survey

ASJC Scopus subject areas

Energy(all)

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10.1016/j.egypro.2017.12.183

Cite this

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title = "Urban carbon mapping with spatial BigData",

abstract = "The objective of this study is mapping carbons utilizing spatial BigData relating buildings and transportations. Regarding buildings, number of storeys, composition of use (e.g., residence and shops), and area of individual buildings are considered. Difference of hourly emission intensity from residence, commercial buildings, firms, and so on, also considered. Regarding transportations, vehicle location by one minutes are considered to capture dynamic fluctuation of transportation behavior. CO2 emissions from individual buildings and road links in Sumida, Tokyo, Japan, are estimated by 30 minutes by a bottom-up approach. The results are visualized in a 3D manner. The result suggests the usefulness of our carbon mapping approach to detect hot spots, abnormal emissions, and so on, that helps efficient carbon management.",

keywords = "carbon mapping, individual buildings, LiDAR, micro-geo data, person-trip survey",

author = "Yoshiki Yamagata and Daisuke Murakami and Takahiro Yoshida",

note = "Publisher Copyright: {\textcopyright} 2017 The Authors. Published by Elsevier Ltd.; 9th International Conference on Applied Energy, ICAE 2017 ; Conference date: 21-08-2017 Through 24-08-2017",

year = "2017",

doi = "10.1016/j.egypro.2017.12.183",

language = "English",

volume = "142",

pages = "2461--2466",

journal = "Energy Procedia",

issn = "1876-6102",

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TY - JOUR

T1 - Urban carbon mapping with spatial BigData

AU - Yamagata, Yoshiki

AU - Murakami, Daisuke

AU - Yoshida, Takahiro

PY - 2017

Y1 - 2017

N2 - The objective of this study is mapping carbons utilizing spatial BigData relating buildings and transportations. Regarding buildings, number of storeys, composition of use (e.g., residence and shops), and area of individual buildings are considered. Difference of hourly emission intensity from residence, commercial buildings, firms, and so on, also considered. Regarding transportations, vehicle location by one minutes are considered to capture dynamic fluctuation of transportation behavior. CO2 emissions from individual buildings and road links in Sumida, Tokyo, Japan, are estimated by 30 minutes by a bottom-up approach. The results are visualized in a 3D manner. The result suggests the usefulness of our carbon mapping approach to detect hot spots, abnormal emissions, and so on, that helps efficient carbon management.

AB - The objective of this study is mapping carbons utilizing spatial BigData relating buildings and transportations. Regarding buildings, number of storeys, composition of use (e.g., residence and shops), and area of individual buildings are considered. Difference of hourly emission intensity from residence, commercial buildings, firms, and so on, also considered. Regarding transportations, vehicle location by one minutes are considered to capture dynamic fluctuation of transportation behavior. CO2 emissions from individual buildings and road links in Sumida, Tokyo, Japan, are estimated by 30 minutes by a bottom-up approach. The results are visualized in a 3D manner. The result suggests the usefulness of our carbon mapping approach to detect hot spots, abnormal emissions, and so on, that helps efficient carbon management.

KW - carbon mapping

KW - individual buildings

KW - LiDAR

KW - micro-geo data

KW - person-trip survey

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DO - 10.1016/j.egypro.2017.12.183

M3 - Conference article

AN - SCOPUS:85041491834

SN - 1876-6102

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JO - Energy Procedia

JF - Energy Procedia

T2 - 9th International Conference on Applied Energy, ICAE 2017

Y2 - 21 August 2017 through 24 August 2017

ER -

Urban carbon mapping with spatial BigData

Abstract

Keywords

ASJC Scopus subject areas

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