气候变化领域集成服务门户(CCPortal): Combined land-use and street view image model for estimating black carbon concentrations in urban areas

CCPortal

DOI	10.1016/j.atmosenv.2021.118719
	Combined land-use and street view image model for estimating black carbon concentrations in urban areas
	Liu X.; Hadiatullah H.; Zhang X.; Schnelle-Kreis J.; Zhang X.; Lin X.; Cao X.; Zimmermann R.
发表日期	2021
ISSN	1352-2310
卷号	265
英文摘要	In this study, we developed a novel land-use street view image random forest (LUSRF) model to estimate the equivalent black carbon (eBC) concentration based on land-use random forest (LURF) and street view imagery (SVI) models and compared their accuracy and precision in the urban city of Augsburg, Germany. The variables of the LUSRF model were constructed by combining LURF and SVI model variables (i.e., land-use, street scene, and meteorological factors). Stratified cross-validation (CV) was used to validate the model performance. Based on R2 and IA (Index of Agreement), LUSRF has superiority (average-R2: 0.73, average-IA: 0.91) compared to the LURF (average-R2: 0.52, average-IA: 0.81) and SVI model (average-R2: 0.68, average-IA: 0.89) in the urban city of Augsburg during the observed period. The main driving factors of the LUSRF model for BC estimation were different in heating and non-heating periods (i.e., elevation, the proportion of moving cars, and relative humidity for the non-heating period; and elevation, the proportion of building, and relative humidity for the heating period), which improves the estimation accuracy of eBC concentration and its sources. The model verification in other areas (i.e., suburban and small towns) further proved that the model has certain generalizability. Overall, the LUSRF model will provide insight for epidemiological studies in urban areas as a personal exposure assessment. © 2021 Elsevier Ltd
关键词	Black carbon Land-use Random forest Street view images
语种	英语
scopus关键词	Carbon; Decision trees; Heating; Random forests; Augsburg; Black carbon; Carbon concentrations; Heating period; Index of agreements; Random forest modeling; Random forests; Street view image; Urban areas; Urban cities; Land use; black carbon; accuracy assessment; black carbon; concentration (composition); land use; numerical model; satellite imagery; urban area; air pollution; air quality; Article; building; car; comparative study; concentration (parameter); cross validation; environmental temperature; Germany; heating; land street view image random forest model; land use; measurement accuracy; measurement precision; meteorological phenomena; model; random forest; relative humidity; rural area; street view imagery model; suburban area; urban area; wind speed; Augsburg; Bavaria; Germany
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248220
作者单位	Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China; Joint Mass Spectrometry Center, Cooperation Group Comprehensive Molecular Analytics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany; Joint Mass Spectrometry Center, Chair of Analytical Chemistry, University of Rostock, Rostock, 18059, Germany; School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, 300072, China; Biology Department, Faculty of Mathematics and Natural Sciences, Brawijaya University65145, Indonesia; College of Agriculture, Nanjing Agricultural University, Nanjing, 210095, China; School of Mathematical Sciences, South China Normal University, Guangzhou, 510631, China
推荐引用方式 GB/T 7714	Liu X.,Hadiatullah H.,Zhang X.,et al. Combined land-use and street view image model for estimating black carbon concentrations in urban areas[J],2021,265.
APA	Liu X..,Hadiatullah H..,Zhang X..,Schnelle-Kreis J..,Zhang X..,...&Zimmermann R..(2021).Combined land-use and street view image model for estimating black carbon concentrations in urban areas.ATMOSPHERIC ENVIRONMENT,265.
MLA	Liu X.,et al."Combined land-use and street view image model for estimating black carbon concentrations in urban areas".ATMOSPHERIC ENVIRONMENT 265(2021).