Kang, G., J.-J. Kim, D.-J. Kim, W. Choi and S.-J. Park, 2017: Development of a computational fluid dynamics model with tree drag
parameterizations: Application to pedestrian wind comfort in an urban area. Building and Environment, 124, 209-218 DOI: 10.1016/j.buildenv.2017.08.008.
 C Yoo, J Im, S Park, LJ Quackenbush, 2018: Estimation of daily maximum and minimum air temperatures in urban landscapes using MODIS time series satellite data, ISPRS journal of photogrammetry and remote sensing, 137, Pages 149-162, https://doi.org/10.1016/j.isprsjprs.2018.01.018
 Jin-Ho Yoon, S-Y Simon Wang, Min-Hui Lo, and Wen-Ying Wu, 2018: Concurrent increases in wet and dry extremes projected in Texas and combined effects on groundwater, Environmental Research Letters, 13, Number 5, https://iopscience.iop.org/article/10.1088/1748-9326/aab96b/meta
 Donghyuck Yoon, Dong‐Hyun Cha, Gil Lee, Changyong Park, Myong‐In Lee, Ki‐Hong Min, 2018: Impacts of Synoptic and Local Factors on Heat Wave Events Over Southeastern Region of Korea in 2015, Journal of Geophysical research, https://doi.org/10.1029/2018JD029247
 Nakbin Choi and Myong-In Lee, 2019: Spatial variability and long-term trend in the occurrence frequency of heatwave and tropical night in Korea, Asia-Pacific Journal of Atmospheric Sciences, 55(1), 101-114.
 Kim, M., Park, M. S., Im, J., Park, S., & Lee, M. I., 2019: Machine Learning Approaches for Detecting Tropical Cyclone Formation Using Satellite Data. Remote Sensing, 11(10), 1195.
 Kim, H., Lee, M. I., Cha, D. H., Lim, Y. K., & Putman, W. M., 2019: Improved representation of the diurnal variation of warm season precipitation by an atmospheric general circulation model at a 10 km horizontal resolution. Climate Dynamics, 1-20.
 Choi, N., Kim, K. M., Lim, Y. K., & Lee, M. I. (2019). Decadal changes in the leading patterns of sea level pressure in the Arctic and their impacts on the sea ice variability in boreal summer. The Cryosphere, 13(11), 3007-3021.
 Yoo, C., Han, D., Im, J., & Bechtel, B. (2019). Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images. ISPRS Journal of Photogrammetry and Remote Sensing, 157, 155-170.
 Park, S., Park, H., Im, J., Yoo, C., Rhee, J., Lee, B., & Kwon, C. (2019). Delineation of high resolution climate regions over the Korean Peninsula using machine learning approaches. PloS one, 14(10).
 Choi, N., Lee, M. I., Cha, D. H., Lim, Y. K., & Kim, K. M. (2019). Decadal Changes in the Interannual Variability of Heatwaves in East Asia Caused by Atmospheric Teleconnection Changes. Journal of Climate, (2019)
 Lee, M., Cha, D. H., Moon, J., Park, J., Jin, C. S., & Chan, J. C. (2019). Long‐term trends in tropical cyclone tracks around Korea and Japan in late summer and early fall. Atmospheric Science Letters, 20(11).
 Min, K. H., Chia‐Hui, C., Bae, J. H., & Cha, D. H. (2019). Synoptic characteristics of extreme heat waves over the Korean Peninsula based on ERA Interim reanalysis data. International Journal of Climatology.
 Shin,M., Kang, Y., Park, S., Im, J., Yoo, C., L..Quackenbush. (2019) . Satellite-based estimation of ground-level particulate matter concentrations: A review. GIScience and Remote Sensing
 Cho, D., Yoo, C., Im, J., & Cha, D. H. (2020). Comparative assessment of various machine learning‐based bias correction methods for numerical weather prediction model forecasts of extreme air temperatures in urban areas. Earth and Space Science, 7(4), e2019EA000740.
 Cho, D., Yoo, C., Im, J., Lee, Y., & Lee, J. (2020). Improvement of spatial interpolation accuracy of daily maximum air temperature in urban areas using a stacking ensemble technique. GIScience & Remote Sensing, 57(5), 633-649.
 Park, S., Kang, D., Yoo, C., Im, J., & Lee, M. I. (2020). Recent ENSO influence on East African drought during rainy seasons through the synergistic use of satellite and reanalysis data. ISPRS Journal of Photogrammetry and Remote Sensing, 162, 17-26.
 Kim, M., Kim, H. C., Im, J., Lee, S., & Han, H. (2020). Object-based landfast sea ice detection over West Antarctica using time series ALOS PALSAR data. Remote Sensing of Environment, 242, 111782.
 Park, S., Lee, J., Im, J., Song, C. K., Choi, M., Kim, J., ... & Quackenbush, L. J. (2020). Estimation of spatially continuous daytime particulate matter concentrations under all sky conditions through the synergistic use of satellite-based AOD and numerical models. Science of the Total Environment, 713, 136516.
 Yoo, C., Im, J., Cho, D., Yokoya, N., Xia, J., & Bechtel, B. (2020). Estimation of all-weather 1 km MODIS land surface temperature for humid summer days. Remote Sensing, 12(9), 1398.
 Shin, M., Kang, Y., Park, S., Im, J., Yoo, C., & Quackenbush, L. J. (2020). Estimating ground-level particulate matter concentrations using satellite-based data: A review. GIScience & Remote Sensing, 57(2), 174-189.
 Kim, Y. J., Kim, H. C., Han, D., Lee, S., & Im, J. (2020). Prediction of monthly Arctic sea ice concentrations using satellite and reanalysis data based on convolutional neural networks. The Cryosphere, 14(3), 1083-1104.
 Choi, N., Lee, M. I., Cha, D. H., Lim, Y. K., & Kim, K. M. (2020). Decadal changes in the interannual variability of heat waves in East Asia caused by atmospheric teleconnection changes. Journal of Climate, 33(4), 1505-1522.
 Lee, J. G., Min, K. H., Park, H., Kim, Y., Chung, C. Y., & Chang, E. C. (2020). Improvement of the rapid-development thunderstorm (RDT) algorithm for use with the GK2A satellite. Asia-Pacific Journal of Atmospheric Sciences, 56(2), 307-319.
 Seo, E., Lee, M. I., Schubert, S. D., Koster, R. D., & Kang, H. S. (2020). Investigation of the 2016 Eurasia heat wave as an event of the recent warming. Environmental Research Letters, 15(11), 114018.
 Yoon, D., Cha, D. H., Lee, M. I., Min, K. H., Kim, J., Jun, S. Y., & Choi, Y. (2020). Recent changes in heatwave characteristics over Korea. Climate Dynamics, 55(7), 1685-1696.
 Min, K. H., Chung, C. H., Bae, J. H., & Cha, D. H. (2020). Synoptic characteristics of extreme heatwaves over the Korean Peninsula based on ERA Interim reanalysis data. International Journal of Climatology, 40(6), 3179-3195.
 Wang, J. W., Yang, H. J., & Kim, J. J. (2020). Wind speed estimation in urban areas based on the relationships between background wind speeds and morphological parameters. Journal of Wind Engineering and Industrial Aerodynamics, 205, 104324.
 Kim, D. J., Kang, G., Kim, D. Y., & Kim, J. J. (2020). Characteristics of LDAPS-predicted surface wind speed and temperature at automated weather stations with different surrounding land cover and topography in Korea. Atmosphere, 11(11), 1224.
 Yoo, C., Lee, Y., Cho, D., Im, J., & Han, D. (2020). Improving local climate zone classification using incomplete building data and Sentinel 2 images based on convolutional neural networks. Remote Sensing, 12(21), 3552.
 Son, B., Park, S., Im, J., Park, S., Ke, Y., & Quackenbush, L. J. (2021). A new drought monitoring approach: Vector Projection Analysis (VPA). Remote Sensing of Environment, 252, 112145.
 Park, S. J., Kim, J. J., Choi, W., Kim, E. R., Song, C. K., & Pardyjak, E. R. (2020). Flow characteristics around step-up street canyons with various building aspect ratios. Boundary-Layer Meteorology, 174(3), 411-431.
 Yoon, D., Cha, D. H., Lee, M. I., Min, K. H., Jun, S. Y., & Choi, Y. (2021). Comparison of regional climate model performances for different types of heat waves over South Korea. Journal of Climate, 34(6), 2157-2174.
 Lee, J. W., Min, K. H., & Lim, K. S. S. (2022). Comparing 3DVAR and hybrid radar data assimilation methods for heavy rain forecast. Atmospheric Research, 270, 106062.
 Bae, J. H., & Min, K. H. (2022). Forecast Characteristics of Radar Data Assimilation Based on the Scales of Precipitation Systems. Remote Sensing, 14(3), 605.
 Yoon, D., Kim, K., Cha, D. H., Lee, M. I., Im, J., Cho, D., & Min, K. H. (2022). Development of model output statistics based on the least absolute shrinkage and selection operator regression for forecasting next‐day maximum temperature in South Korea. Quarterly Journal of the Royal Meteorological Society.
 Cho, D., Yoo, C., Son, B., Im, J., Yoon, D., & Cha, D. H. (2022). A novel ensemble learning for post-processing of NWP Model's next-day maximum air temperature forecast in summer using deep learning and statistical approaches. Weather and Climate Extremes, 35, 100410.
 Cho, D., Bae, D., Yoo, C., Im, J., Lee, Y., & Lee, S. (2022). All-Sky 1 km MODIS Land Surface Temperature Reconstruction Considering Cloud Effects Based on Machine Learning. Remote Sensing, 14(8), 1815.
 Yoo, C., Im, J., Cho, D., Lee, Y., Bae, D., & Sismanidis, P. (2022). Downscaling MODIS nighttime land surface temperatures in urban areas using ASTER thermal data through local linear forest. International Journal of Applied Earth Observation and Geoinformation, 110, 102827.
 Lee, J., Park, S., Im, J., Yoo, C., & Seo, E. (2022). Improved soil moisture estimation: Synergistic use of satellite observations and land surface models over CONUS based on machine learning. Journal of Hydrology, 609, 127749.
 유철희, 2017: 폭염, 어떻게 대비할 것인가? 위성과 인공지능의 활용, 한국방재학회, 17(4)
 유철희, 2017: 기계학습 기반 상세화를 통한 위성 지표면온도와 환경부 토지피복도를 이용한 열환경 분석: 대구광역시를 중심으로, Korean Journal of Remote Sensing, Vol.33, No.6-2, 2017
 강정은, 2018: GIS 자료를 활용한 도시 재개발 주변 지역의 일조 환경 분석, Korean Journal of Remote Sensing, Vol.34, No.5, 2018
 Yoo, C., Im, J., Park, S., & Cho, D. (2020). Spatial downscaling of MODIS land surface temperature: Recent research trends, challenges, and future directions. Korean Journal of Remote Sensing, 36(4), 609-626.
 Lee, H. D., Min, K. H., Bae, J. H., & Cha, D. H. (2020). Characteristics and comparison of 2016 and 2018 heat wave in Korea. Atmosphere, 30(1), 1-15.