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	Estimating annual average daily traffic and transport emissions for a national road network: A bottom-up methodology for both nationally-aggregated and spatially-disaggregated results
	Miao Fu; J. Andrew Kelly; J. Peter Clinch
刊名	Journal of Transport Geography
	2017
卷号	Vol.58页码:186-195
关键词	Transport Traffic Road network Emissions Neural network GIS
ISSN号	0966-6923
URL标识	查看原文
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/1923366
专题	广东外语外贸大学（超星）
作者单位	1.EnvEcon, NexusUCD, Block 9, Belfield Office Park, Belfield, Dublin 4, Ireland 2.Collaborative Innovation Center for 21st-Century Maritime Silk Road Studies, Guangdong University of Foreign Studies, Guangzhou, China 3.UCD Planning and Environmental Policy and UCD Earth Institute, University College Dublin, Belfield, Dublin 4, Ireland 4.a UCD Planning and Environmental Policy, University College Dublin, Belfield, Dublin 4, Ireland
推荐引用方式 GB/T 7714	Miao Fu,J. Andrew Kelly,J. Peter Clinch. Estimating annual average daily traffic and transport emissions for a national road network: A bottom-up methodology for both nationally-aggregated and spatially-disaggregated results[J]. Journal of Transport Geography,2017,Vol.58:186-195.
APA	Miao Fu,J. Andrew Kelly,&J. Peter Clinch.(2017).Estimating annual average daily traffic and transport emissions for a national road network: A bottom-up methodology for both nationally-aggregated and spatially-disaggregated results.Journal of Transport Geography,Vol.58,186-195.
MLA	Miao Fu,et al."Estimating annual average daily traffic and transport emissions for a national road network: A bottom-up methodology for both nationally-aggregated and spatially-disaggregated results".Journal of Transport Geography Vol.58(2017):186-195.

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