Research Professors
LI Lianfa
Source： | Date：2016-10-10 | 【Print】 【Close】
Lianfa Li, Professor of Spatial Statistics, State Key Laboratory of Resources & Environmental Information System, Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences
A11, Datun Road, Beijing 100101, PRC
Telephone Office: +86 10 64888362
Fax: +86 10 64889630
E_mail: lilf@Lreis.ac.cn; lspatial@gmail.com
Male, Ph.D., Appointed as Associate Researcher of State Key Laboratory of Resource and Environmental Information Systems, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences. Won Dean of Chinese Academy of Sciences Scholarship Excellence Award, Wang Kuancheng Work Reward Fund. Conducted advanced visit research work, actively participated in relevant international academic exchange activities, and once served as reviewers of RSE, EST, EI, IEEE Transactions on Industrial Informatics, Earth Information Science, CSIE2009, IJGIS, IJRS, SERRA and Sensors and other domestic and foreign academic journals, international conferences, and reviewers of the National Natural Science Foundation of China. As the person in charge, he presided two national 863 key projects, four National Natural Science Foundation and other projects. Main research areas cover spatiotemporal machine learning, spatiotemporal data mining and knowledge discovery, environmental health.
Peer-reviewed papers：
1) Li, L., Franklin, M., Girguis, M., Lurmann, F., Wu, J., Pavlovic, N., Breton, C., Gilliland, F. & Habre, R., 2020, Spatiotemporal imputation of MAIAC AOD using deep learning with downscaling, Remote Sensing of Environment, 237, 111584.
2) Li, L., 2020, A robust deep learning approach for spatiotemporal estimation of satellite AOD and PM2.5, Remote Sensing, 12(2), 264.
3) Li, L., 2020, Optimal inversion of conversion parameters from satellite AOD to ground aerosol extinction coefficient using automatic differentiation, Remote Sensing, 12(3), 492.
4) Li, L., 2020, Deep residual autoencoder with multiscaling for semantic segmentation of land-use images, Remote Sensing, 2019, 11(18): 0-2142.
5) Li, L., 2019, Geographically weighted machine learning and downscaling for high-resolution spatiotemporal estimations of wind speed, Remote Sensing, 11(11), 1378.
6) Li, L., Girguis, M., Lurmann, F., Wu, J., Urman, R., Rappaport, E., Ritz, B., Franklin, M., Breton, C., Gilliland, F., Habre, R., 2019, Cluster-based bagging of constrained mixed-effects models for high spatiotemporal resolution nitrogen oxides prediction over large regions , Environment International, 2019, 128: 310-323.
7) Girguis, M., Li, L., Lurmann, F., 2019, Exposure measurement error in air pollution studies: A framework for assessing shared, multiplicative measurement error in ensemble learning estimates of nitrogen oxides, Environment International,125, 97-106.
8) Fang, Y., Li, L., (corresponding author), 2019, High-accuracy spatiotemporal estimation of meteorological factors at a high resolution based on machine learning, Geoinformatics (in Chinese), 21, 799-813
9) Li, L., Zhang, J., Meng, X., Fang, Y., Ge, Y., Wang, C., Wu, J., Kan, H., 2018, Estimation of PM2.5 concentrations at a high spatiotemporal resolution using constrained mixed-effect bagging models with MAIAC aerosol optical depth, Remote Sensing of Environment, 217.
10) Li, L., W. Qiu, C. Xu, J. Wang, 2018, A Spatiotemporal Mixed Models to Assessthe Influence of Environmental and Socioeconomic Factors on the Incidence of Hand, Foot and Mouth Disease, BMC Public Health, 18, 274.
11) Masri, S., L. Li, A. Dang, et al. 2018, Source characterization and exposure modeling of gas-phase polycyclic aromatic hydrocarbon (PAH) concentrations in Southern California, Atmos Environ, 177, 175-186.
12) Younan, D., Li, L., Tuvblad, C. et al., 2018, Long-term ambient temperature and externalizing behaviors in adolescents, American Journal of Epidemiology (2018) 187(9) 1931-1941.
13) Younan. D., Tuvblad, C., Franklin M., Lurmann, F., Li, L., et al., 2018, Longitudinal Analysis of Particulate Air Pollutants and Adolescent Delinquent Behavior in Southern California, Journal of Abnormal Child Psychology (2018) 46(6) 1283-1293
14) Li, L., Lurmann, F., Habre, R., Urman, R., Rappaport, E., Ritz, B., Chen, J., Gilliland, F., Wu, J., 2017, Constrained Mixed-Effect Models with Ensemble Learning for Prediction of Nitrogen Oxides Concentrations at High Spatiotemporal Resolution, Environmental Science and Technology, 51(17): 9920-9929.
15) Li, L., A. Wu, I. Cheng, et al., 2017, Spatiotemporal estimation of historical PM2.5 concentrations using PM10, meteorological variables, and spatial effect, Atmos Environ, 166, 182-191.
16) Li, L., J. Zhang & W. Qiu, et al. 2017, An ensemble spatiotemporal model for predicting PM2.5 concentrations, Int. J Environ Res Public Health, 14, 549.
17) Li, L., O. Laurent, & J. Wu, 2016, Spatial variability of the effect of air pollution on term birth weight: evaluating influential factors using Bayesian Hierarchical Models, Environ Health, 15: 14.
18) Laurent, O., Hu, J., Li, L., et al., 2016, A statewide nested case–Control study of preterm birth and air pollution by source and composition: California, 2001–2008, Environmental Health Perspectives, 124(9) 1479-1486
19) Younan, D., Tuvblad, C., Li, L. 2016, Environmental Determinants of Aggression in Adolescents: Role of Urban Neighborhood Greenspace, Journal of the American Academy of Child and Adolescent Psychiatry (2016) 55(7) 591-601.
20) Laurent, O., Hu, L., Li, L., 2016, Low birth weight and air pollution in California: Which sources and components drive the risk? Environment International (2016) 92-93 471-477.
21) Yang, X., Li, L., Wang, J., 2015, Cardiovascular mortality associated with low and high temperatures: determinants of inter-region vulnerability in China, Int J Environ Res Public Health. 2015, 12(6):5918-33.
22) Li, X., Xie, X., Li, L., Li, J., Zhao, H., Wang, H., Zhao, H., Wang, J., 2015, Using robust Bayesian network to estimate the residuals of fluoroquinolone antibiotic in soil. Environ Sci Pol Res. 22(22):17540-9.
23) Yang, X., Li, L., Wang, J., Huang, J., 2015, The Use of Generalized Additive Model in Association of Temperature and Cardiovascular Mortality in Anhui, Geoinformatics (in Chinese), pp 1388-1394, 2015/11.
24) Laurent, O., Hu, J. & Li, L. et al., 2014, Sources and contents of air pollution affecting term low birth weight in Los Angeles County, California, 2001-2008, Environmental Research (2014) 134 488-495.
25) Wang, J., Ge, Y., Li, L., et al. 2014. Spatiotemporal data analysis in geography. Acta Geographica Sinica (in Chinese), 69(9): 1326-1345.
26) Li, L., J. Wu, J.K. Ghosh & B. Ritz, 2013, Estimating spatiotemporal variability of ambient air pollutant concentrations with a hierarchical model, Atmos Environ, 71, 54-63.
27) Li, L., J. Wu, N. Hudda, C. Sioutas, S.A. Fruin & R.J. Delfino, 2013, Modelling the concentrations of on-road air pollutants in southern California, Environmental Science & Technology, 47(16), 9291-9299.
28) Laurent, O., Wu, J. & Li, L. et al, 2013, Green spaces and pregnancy outcomes in Southern California, Health and Place, 24, 190-195.
29) Laurent, O., Wu, J. & Li, L. et al, 2013, Investigating the association between birth weight and complementary air pollution metrics: a cohort study, Environmental Health: A Global Access Science Source, 12(1).
30) Haining, T. Liu, L. Li & C. Jiang, 2013, Design-based spatial sampling: theory and implementation, Environ modell Softw 40, 280-288.
31) Wang, Y., Li, L., A Parallel Bayesian Classifier，Geography and Geo-Information Science (in Chinese), 29(4), pp 47-51, 2013/04/01 04.
32) Li, L., J. Wu, M. Wilhelm & B. Ritz, 2012, Use of generalized additive models and cokriging of spatial residuals to improve land-use regression estimates of nitrogen oxides in southern California, Atmospheric Environment, 55, 220-228.
33) Li, L., J. Wang, H. Leung & S. Zhao, 2012, A Bayesian method to mine spatial data sets to evaluate the vulnerability of human beings to catastrophic risk, Risk Analysis, 32(6), 1072-1092.
34) Li, L., Wang, J. & Wu, J., 2012, A spatial model to predict the incidence of neural tube defects, BMC Public Health (2012) 12(1).
35) Li, L. & Leung, H., 2011, Mining static code metrics for a robust prediction of software defect-proneness, International Symposium on Empirical Software Engineering and Measurement (2011) 207-214.
36) Li, L., J. Wang & H. Leung, 2010, An unsupervised similarity classifier to stratify samples to improve estimation precision, Int J of Remote Sensing, 30(5): 1207-1234.
37) Li, L., & H. Leung, 2011, Mining static code metrics for a robust prediction of software defect-proneness, ACM /IEEE 2011 International Symposium on Empirical Software Engineering and Measurement (http://dl.acm.org/citation.cfm?id=2083427).
38) Lianfa Li, Jinfeng Wang & Hareton Leung, 2010, Assessment of Catastrophic Risk Using Bayesian Network Constructed from Domain Knowledge and Spatial Data , Risk Analysis, 2010, 30(7):1157-75.
39) Lianfa Li, Jinfeng Wang & Hareton Leung, 2010, Using spatial analysis and Bayesian network to model the vulnerability and make insurance pricing of catastrophic risk, International Journal of Geographical Information Science, 24(12): 1759–1784.
40) Lianfa Li, Jinfeng Wang & Chengyi Wang, Typhoon insurance pricing with spatial decision-making support tools, International Journal of Geographical Information Science, 19(3): 363-384
41) Lianfa Li & Jinfeng Wang, 2006, A prototype auto-human support system for spatial analysis, Progress in Natural Science, 16(9): 954-966
42) Lianfa Li, Jinfeng Wang & Jiyuan Liu, 2005, Optimal decision-making model of spatial sampling for survey of China’s land with remotely sensed data, Science in China – Series D, 48(6): 752-764
43) Lianfa Li & Jinfeng Wang, 2004, Integrated spatial sampling modeling of geospatial data, Science in China – Series D, 47(3): 201-208
44) Jinfeng Wang, Lianfa Li & George Christakos, 2009, Sampling and Kriging Spatial Means: Efficiency and Conditions, Sensor, 9(7), 5224-5240
45) Jinfeng Wang & Lianfa Li, Improving tsunami warning systems with remote sensing and geographical information system input, 2008, Risk Analysis, 2008, 28(6): 1653-1668
46) Jinfeng Wang, Jiyuan Liu, Dafang Zhuang, Lianfa Li & Yong Ge, Spatial sampling design for monitoring the area of cultivated land, International Journal of Remote Sensing, 2002, 23(3): 263-284
47) Lianfa Li & Hareton Leung, 2009, Using the number of faults to improve fault-proneness prediction of the probability models, 2009, World Congress on Computer Science and Information Engineering, March 31 - April 2, Los Angeles/Anaheim, USA (IEEE Xplore收錄)
48) Lianfa Li, Jinfeng Wang, Zhidong Cao, et al., 2006, An information-fusion method to regionalize spatial heterogeneity for improving the accuracy of spatial sampling estimation, 53rd Annual North American Meetings of the Regional Science Association International, Toronto, Canada (會(huì)議論文)
49) Jinfeng Wang, Lianfa Li, Zhidong Cao, et al., 2006, A systematic analysis for an intelligent induced spatial sampling (IISS)， 53rd Annual North American Meetings of the Regional Science Association International, Toronto, Canada (會(huì)議論文)
Patent：
1) A system and method of environmental health risk monitoring and warning base on spatial Bayesian network, 2018, Inventors: Lianfa Li et al., published number: CN107767954A
2) A big-data system and method of spatiotemporal mixed-effect exposure evaluation, 2018, Inventors：Lianfa Li et al., published number: CN107798425A
3) A method to improve the processing efficiency of massive spatial data, 2015, Inventor: Lianfa Li et al., Granted No: CN103235974B.
4) A grid-based spatial heterogeneous pattern recognition method and layering method, 2008, Inventors: Lianfa Li et al., granted No: 200810116559.5
5) A dynamic risk and vulnerability prediction method under fine scale, 2008, Inventors: Lianfa Li et al., Granted No： 200810222052.8
Books：
1) Lianfa Li, Jinfeng Wang, 2014. Geospatial Data Mining (in Chinese), Science Press (http://www.sciencep.com/m_single.php?id=34844)
2) Wang, J., Jiang, C., Li, L., Hu, M.，2009，Spatial Sampling and Statistical Inference (in Chinese), Science Press
3) Wang J. et al., 2006, Spatial Analysis (in Chinese), Science Press, in charge of Chapter 1,9 and 28, and noun interpretation and index writing.
Software：
1) Lianfa Li, Yang Wang, Sisi Zhao, Jinfeng Wang, Spatial Statistics and Bayesian Model Parallel Computing System Software (Copyright No: 2014SR077131) , China, 2014/6/12
2) 2008.1-2010：Spatial Data Mining and Decision Support Toolkit (Presider)
3) 2007.1-2008.10：Sandwich spatial sampling and statistical inference software package, one of core members
4) SIMPLE Spatial Analysis, Copyright No: 2005SR05091, the second author.
