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Spatiotemporal imputation of MAIAC AOD using deep learning with downscaling 期刊论文
REMOTE SENSING OF ENVIRONMENT, 2020, 卷号: 237, 页码: 17
Authors:  Li, Lianfa;  Franklin, Meredith;  Girguis, Mariam;  Lurmann, Frederick;  Wu, Jun;  Pavlovic, Nathan;  Breton, Carrie;  Gilliland, Frank;  Habre, Rima
Favorite  |  View/Download:5/0  |  Submit date:2020/05/19
Aerosol Optical Depth  MAIAC  MERRA-2 GMI Replay Simulation  Deep learning  Downscaling  Missingness imputation  Air quality  
Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation 期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 3, 页码: 20
Authors:  Li, Lianfa
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parameter inversion  aerosol optical depth  PBLH  ground-based AOD  PM2  5  automatic differentiation  
A Robust Deep Learning Approach for Spatiotemporal Estimation of Satellite AOD and PM2.5 期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 2, 页码: 27
Authors:  Li, Lianfa
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PM2.5  satellite AOD  deep learning  autoencoder  residual network  exposure estimation  high spatiotemporal resolution  
Deep Residual Autoencoder with Multiscaling for Semantic Segmentation of Land-Use Images 期刊论文
REMOTE SENSING, 2019, 卷号: 11, 期号: 18, 页码: 24
Authors:  Li, Lianfa
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residual learning  autoencoder  multiscale  atrous spatial pyramid pooling  semantic segmentation  remotely sensed land-use images  
Cluster-based bagging of constrained mixed-effects models for high spatiotemporal resolution nitrogen oxides prediction over large regions 期刊论文
ENVIRONMENT INTERNATIONAL, 2019, 卷号: 128, 页码: 310-323
Authors:  Li, Lianfa;  Girguis, Mariam;  Lurmann, Frederick;  Wu, Jun;  Urman, Robert;  Rappaport, Edward;  Ritz, Beate;  Franklin, Meredith;  Breton, Carrie;  Gilliland, Frank;  Habre, Rima
Favorite  |  View/Download:18/0  |  Submit date:2019/09/24
Air pollution  Nitrogen oxides  Spatiotemporal variability  Generalization  Machine learning  Cluster methods  
基于机器学习的高精度高分辨率气象因子时空估计 期刊论文
地球信息科学学报, 2019, 卷号: 21, 期号: 6, 页码: 799
Authors:  方颖;  李连发
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Estimation of PM2.5 concentrations at a high spatiotemporal resolution using constrained mixed-effect bagging models with MAIAC aerosol optical depth 期刊论文
REMOTE SENSING OF ENVIRONMENT, 2018, 卷号: 217, 页码: 573-586
Authors:  Li, Lianfa;  Zhang, Jiehao;  Meng, Xia;  Fang, Ying;  Ge, Yong;  Wang, Jinfeng;  Wang, Chengyi;  Wu, Jun;  Kan, Haidong
Favorite  |  View/Download:21/0  |  Submit date:2019/05/23
PM2.5  MAIAC AOD  High spatiotemporal resolution  Temporal variation  AOD-PM2.5 associations  Spatial effects  Missingness  Machine learning  
Source characterization and exposure modeling of gas-phase polycyclic aromatic hydrocarbon (PAH) concentrations in Southern California 期刊论文
ATMOSPHERIC ENVIRONMENT, 2018, 卷号: 177, 页码: 175-186
Authors:  Masri, Shahir;  Li, Lianfa;  Dang, Andy;  Chung, Judith H.;  Chen, Jiu-Chivan;  Fan, Zhi-Hua (Tina);  Wu, Jun
Favorite  |  View/Download:19/0  |  Submit date:2019/05/30
Air pollution  Polycyclic aromatic hydrocarbon  Source  Land-use regression  Spatial model  Thiessen polygons  
A spatiotemporal mixed model to assess the influence of environmental and socioeconomic factors on the incidence of hand, foot and mouth disease 期刊论文
BMC PUBLIC HEALTH, 2018, 卷号: 18, 页码: 12
Authors:  Li, Lianfa;  Qiu, Wenyang;  Xu, Chengdong;  Wang, Jinfeng
Favorite  |  View/Download:11/0  |  Submit date:2019/05/30
Spatiotemporal mixed model  Spatial effect  Non-linear effect  Hand-foot-mouth disease  Spatiotemporal scanning statistics  
Spatiotemporal estimation of historical PM2.5 concentrations using PM10, meteorological variables, and spatial effect 期刊论文
ATMOSPHERIC ENVIRONMENT, 2017, 卷号: 166, 页码: 182-191
Authors:  Li, Lianfa;  Wu, Anna H.;  Cheng, Iona;  Chen, Jiu-Chivan;  Wu, Jun
Favorite  |  View/Download:5/0  |  Submit date:2019/09/25
Particulate matter  PM2.5  Historical concentration  Spatiotemporal model