Publications

• Pu, Q., & Yoo, E. H. (2022). A gap-filling hybrid approach for hourly PM2.5 prediction at high spatial resolution from multi-sourced AOD data. Environmental Pollution, 120419.
• Jiang, X., Eum, Y., & Yoo, E. H. (2022). The impact of fire-specific PM2.5 calibration on health effect analyses. Science of The Total Environment, 159548.
• Zhu K., Kawyn M.N., Kordas K., Mu. L, Yoo E-H, Seibert R. Smith L.E. (2022). Assessing exposure to household air pollution in children under five: A scoping review, Environmental Pollution, 119917.
• Eum, Y. & Yoo, E. H. (2022) Imputation of Missing Time-Activity Data with Long-term Gaps: A multi-scale residual CNN-LSTM Network Model, Computers, Environment and Urban Systems.
• Yoo, E. H., Roberts, J. E., Eum, Y., Li, X., Chu L., Wang P., & Chen, K. (2022) Short-term exposure to air pollution and mental disorders: A case-crossover study in New York City, Environmental Research: Health.
  
• Yoo, E. H., Roberts, J. E. (2022) Static home-based versus dynamic mobility-based assessments of exposure to urban green space, Urban Forestry & Urban Greening, 70 April 2022, 127528.
• Eum, Y. & Yoo, E. H. (2022) Using GPS-enabled Mobile Phones to Evaluate the Associations between Human Mobility Changes and the Onset of Influenza Illness. Spatial and Spatio-temporal Epidemiology, 40, 100458.
  

  2021

• Zaidi, S.M.A., Chandola, V, and Yoo, E.H. (2021) DST-Predict: Predicting individual mobility patterns from mobile phone GPS data, IEEE Access.
• Yoo, E. H., Roberts, J. E., Eum, Y., Li, X., & Konty, K. (2021). Exposure to urban green space may both promote and harm mental health in socially vulnerable neighborhoods: A neighborhood-scale analysis in New York City. Environmental Research, 112292.
• Yoo, E. H., Palermo, T., & Maluka, S. (2021). Geostatistical linkage of national demographic and health survey data: a case study of Tanzania. Population Health Metrics, 19(1), 1-14. 
• Yoo, E. H., Eum, Y., Roberts, J. E., Gao, Q., & Chen, K. (2021). Association between extreme temperatures and emergency room visits related to mental disorders: A multi-region time-series study in New York, USA. Science of The Total Environment, 148246.
• Yoo, E. H., Eum, Y., Gao, Q., & Chen, K. (2021). Effect of extreme temperatures on daily emergency room visits for mental disorders. Environmental Science and Pollution Research, 1-14.
• Yoo, E. H., Pu, Q., Eum, Y., & Jiang, X. (2021). The Impact of Individual Mobility on Long-Term Exposure to Ambient PM2.5: Assessing Effect Modification by Travel Patterns and Spatial Variability of PM2.5. International Journal of Environmental Research and Public Health, 18(4), 2194.
• Pu, Q., & Yoo, E. H. (2021). Ground PM2.5 prediction using imputed MAIAC AOD with uncertainty quantification. Environmental Pollution, 274, 116574.

2020

• Yoo, E. H., Zammit-Mangion, A., & Chipeta, M. G. (2020). Adaptive spatial sampling design for environmental field prediction using low-cost sensing technologies. Atmospheric Environment, 221(11), 117091.
• Yoo, E. H., Roberts, J. E., Eum, Y., & Shi, Y. (2020). Quality of hybrid location data drawn from GPS‐enabled mobile phones: Does it matter?. Transactions in GIS, 24(2), 462-482.
• Pu, Q., & Yoo, E. H. (2020). Spatio-temporal modeling of PM2.5 concentrations with missing data problem: a case study in Beijing, China. International Journal of Geographical Information Science, 34(3), 423-447.
• Jiang, X., & Yoo, E. H. (2020). Evaluating the effect of domain size of the community multiscale air quality (CMAQ) model on regional PM 2.5 simulations. In Geospatial Technologies for Urban Health (Chap 4. pp. 53-72). Springer, Cham.
• Pu, Q., Yoo, E. H., Rothstein, D. H., Cairo, S., & Malemo, L. (2020). Improving the spatial accessibility of healthcare in North Kivu, Democratic Republic of Congo. Applied Geography, 121, 102262.

2019

• Yoo, E. H. (2019). How short is long enough? Modeling temporal aspects of human mobility behavior using mobile phone data. Annals of the American Association of Geographers, 109(5), 1415-1432.
• Jiang, X., & Yoo, E. H. (2019). Modeling wildland fire-specific PM2.5 concentrations for uncertainty-aware health impact assessments. Environmental Science & Technology, 53(20), 11828-11839.
• Eum, Y., Yoo, E. H., & Bowen, E. (2019). Socioeconomic determinants of pediatric asthma emergency department visits under regional economic development in western New York. Social Science & Medicine, 222, 133-144.
• Yoo, E. H., Eum, Y., Roberts, J. E. (2019). Implications of incomplete GPS-enabled mobile phone data on human mobility studies, AGILE 2019.
• Kerry, R., Yoo, E. H., & Ingram, B. (2019). Spatial analysis of drug poisoning deaths in the American West: A comparison study using profile regression to adjust for collinearity and spatial correlation. Drug and Alcohol Dependence, 204, 107598.
• Weaver, A. M., Gurley, E. S., Crabtree-Ide, C., Salje, H., Yoo, E. H., Mu, L., … & Ram, P. K. (2019). Air pollution dispersion from biomass stoves to neighboring homes in Mirpur, Dhaka, Bangladesh. BMC Public Health, 19(1), 1-12.

2018

• Yoo, E. H., Brown, P., & Eum, Y. (2018). Ambient air quality and Spatio-temporal patterns of cardiovascular emergency department visits. International Journal of Health Geographics, 17(1), 1-16.
• Yoo, E. H., Kerry, R., Ingram, B., Ortiz, B., & Scully, B. (2018). Defining and characterizing aflatoxin contamination risk areas for corn in Georgia, USA: Adjusting for collinearity and spatial correlation. Spatial Statistics, 28, 84-104.
• Jiang, X., & Yoo, E. H. (2018). The importance of spatial resolutions of community multiscale air quality (CMAQ) models on health impact assessment. Science of the Total Environment, 627, 1528-1543.
• Yoo, E. H. (2018). Geostatistical Approach to Spatial Data Transformation.
• Martin, S. J., Funch, R. R., Hanson, P. R., & Yoo, E. H. (2018). A vast 4,000-year-old spatial pattern of termite mounds. Current Biology, 28(22), R1292-R1293.
• Lim, H., Yoo, E. H., & Park, M. (2018). Warehouse rental market segmentation using spatial profile regression. Journal of Transport Geography, 73, 64-74.
• Stanley, K., Yoo, E. H., Paul, T., & Bell, S. (2018). How many days are enough?: capturing routine human mobility. International Journal of Geographical Information Science, 32(7), 1485-1504.
• Mennis, J., & Yoo, E. H. (2018). Geographic information science and the analysis of place and health. Transactions in GIS, 22(3), 842-854.
• Dodson, Z. M., Yoo, E. H., Martin-Gill, C., & Roth, R. (2018). Spatial methods to enhance public health surveillance and resource deployment in the opioid epidemic. American Journal of Public Health, 108(9), 1191-1196.

2017

• Shekhar, S., Yoo, E. H., Ahmed, S. A., Haining, R., & Kadannolly, S. (2017). Analysing malaria incidence at the small area level for developing a spatial decision support system: a case study in Kalaburagi, Karnataka, India. Spatial and Spatio-temporal Epidemiology, 20, 9-25.
• Yoo, E. H. (2017) Geostatistics, In: T. J. Cova and M.-H. Tsou (Eds) Comprehensive Geographic Information Systems: GIS Principles and Technical Designs of GIS (Chap 18), Elsevier.

2016

• Yoo, E. H., Chen, D., Diao, C., & Russell, C. (2016). The effects of weather and environmental factors on West Nile virus mosquito abundance in greater Toronto area. Earth Interactions, 20(3), 1-22.
• Yoo, E. H., & Eum, Y. S. (2016). Using GPS-enabled mobile phones to characterize individuals’ activity patterns for epidemiology applications. In International Conference on GIScience Short Paper Proceedings (Vol. 1, No. 1).
• Glasgow, M. L., Rudra, C. B., Yoo, E. H., Demirbas, M., Merriman, J., Nayak, P., … & Mu, L. (2016). Using smartphones to collect time-activity data for long-term personal-level air pollution exposure assessment. Journal of Exposure Science & Environmental Epidemiology, 26(4), 356-364.

2015 

• Yoo, E. H., Rudra, C., Glasgow, M., & Mu, L. (2015). Geospatial estimation of individual exposure to air pollutants: Moving from static monitoring to activity-based dynamic exposure assessment. Annals of the Association of American Geographers, 105(5), 915-926.
• Yoo, E. H., Chen, D., & Russel, C. (2015). West Nile virus mosquito abundance modeling using nonstationary spatiotemporal geostatistics. Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases, 263.
• Yoo, E. H., Lee, C. R., & Park, K. H. (2015). Valuing commercial spaces in multistory buildings using a three-level mixed-effects modeling approach. International Regional Science Review, 38(4), 413-436.
• Zhuang, Y., Lin, F., Yoo, E. H., & Xu, W. (2015, June). Airsense: A portable context-sensing device for personal air quality monitoring. In Proceedings of the 2015 Workshop on Pervasive Wireless Healthcare (pp. 17-22).

2014 and Earlier

• Yoo, E. H. (2014). Site-specific prediction of West Nile virus mosquito abundance in Greater Toronto Area using generalized linear mixed models. International Journal of Geographical Information Science, 28(2), 296-313.
• Cao, G., Yoo, E. H., & Wang, S. (2014). A statistical framework of data fusion for spatial prediction of categorical variables. Stochastic Environmental Research and Risk Assessment, 28(7), 1785-1799.
• Yoo, E. H. (2013). Exploring space-time models for West Nile virus mosquito abundance data. Applied Geography, 45, 203-210.
• Yoo, E. H., Hoagland, B. W., Cao, G., & Fagin, T. (2013). Spatial distribution of trees and landscapes of the past: a mixed spatially correlated multinomial logit model approach for the analysis of the public land survey data. Geographical Analysis, 45(4), 419-440.
• Spielman, S. E., Yoo, E. H., & Linkletter, C. (2013). Neighborhood contexts, health, and behavior: understanding the role of scale and residential sorting. Environment and Planning B: Planning and Design, 40(3), 489-506.
• Powell, R. L., Yoo, E. H., & Still, C. J. (2012). Vegetation and soil carbon‐13 isoscapes for South America: integrating remote sensing and ecosystem isotope measurements. Ecosphere, 3(11), 1-25.
• Patterson, K. L., & Yoo, E. H. (2012). Trapped in poor places? An assessment of the residential spatial patterns of housing choice voucher holders in 2004 and 2008. Journal of Social Service Research, 38(5), 637-655.
• Yoo, E. H., & Trgovac, A. B. (2011). Scale effects in uncertainty modeling of presettlement vegetation distribution. International Journal of Geographical Information Science, 25(3), 405-421.
• Yoo, E. H., Kyriakidis, P. C., & Tobler, W. (2010). Reconstructing
  Population Density Surfaces from Areal Data: A Comparison of Tobler’s
  Pycnophylactic Interpolation Method and Area‐to‐Point Kriging. Geographical Analysis, 42(1), 78-98.
• Yoo, E. H., & Kyriakidis, P. C. (2009). Area-to-point Kriging in spatial hedonic pricing models. Journal of Geographical Systems, 11(4), 381-406.
• Spielman, S. E., & Yoo, E. H. (2009). The spatial dimensions of neighborhood effects. Social Science & Medicine, 68(6), 1098-1105.
• Yoo, E. H., & Kyriakidis, P. C. (2008). Area‐to‐Point Prediction Under Boundary Conditions. Geographical Analysis, 40(4), 355-379.
• Yoo, E. H., Kyriakidis, P. C., & Tobler, W. (2010). Reconstructing
  Population Density Surfaces from Areal Data: A Comparison of Tobler’s
  Pycnophylactic Interpolation Method and Area‐to‐Point Kriging. Geographical Analysis, 42(1), 78-98.
• Yoo, E. H., Wang, Y. C., & Trgovac, A. (2008). Spatial uncertainty assessment in the reconstruction of presettlement forest patterns in Western NY, USA. In Proceedings
  of the 8th International Symposium on Spatial Accuracy Assessment in
  Natural Resources and Environmental Sciences: Shanghai, China, June
  25-27, 2008 (Vol. 1, p. 278). 
• Yoo, E. H., & Kyriakidis, P. C. (2006). Area-to-point kriging with inequality-type data. Journal of geographical systems, 8(4), 357-390.
• Kyriakidis, P. C., & Yoo, E. H. (2005). Geostatistical prediction and simulation of point values from areal data. Geographical Analysis, 37(2), 124-151.