| Comparative assessment of various machine learning‐based bias correction methods for numerical weather prediction model forecasts of extreme air temperatures in urban areas D Cho, C Yoo, J Im, DH Cha Earth and Space Science 7 (4), e2019EA000740, 2020 | 194 | 2020 |
| Improvement of spatial interpolation accuracy of daily maximum air temperature in urban areas using a stacking ensemble technique D Cho, C Yoo, J Im, Y Lee, J Lee GIScience & Remote Sensing 57 (5), 633-649, 2020 | 67 | 2020 |
| Improved retrievals of aerosol optical depth and fine mode fraction from GOCI geostationary satellite data using machine learning over East Asia Y Kang, M Kim, E Kang, D Cho, J Im ISPRS Journal of Photogrammetry and Remote Sensing 183, 253-268, 2022 | 63 | 2022 |
| Estimation of all-weather 1 km MODIS land surface temperature for humid summer days C Yoo, J Im, D Cho, N Yokoya, J Xia, B Bechtel Remote Sensing 12 (9), 1398, 2020 | 53 | 2020 |
| Improving local climate zone classification using incomplete building data and Sentinel 2 images based on convolutional neural networks C Yoo, Y Lee, D Cho, J Im, D Han Remote Sensing 12 (21), 3552, 2020 | 50 | 2020 |
| 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 D Cho, C Yoo, B Son, J Im, D Yoon, DH Cha Weather and Climate Extremes 35, 100410, 2022 | 46 | 2022 |
| Spatial downscaling of MODIS land surface temperature: Recent research trends, challenges, and future directions C Yoo, J Im, S Park, D Cho Korean Journal of Remote Sensing 36 (4), 609-626, 2020 | 32 | 2020 |
| All-sky 1 km MODIS land surface temperature reconstruction considering cloud effects based on machine learning D Cho, D Bae, C Yoo, J Im, Y Lee, S Lee Remote Sensing 14 (8), 1815, 2022 | 29 | 2022 |
| Downscaling MODIS nighttime land surface temperatures in urban areas using ASTER thermal data through local linear forest C Yoo, J Im, D Cho, Y Lee, D Bae, P Sismanidis International Journal of Applied Earth Observation and Geoinformation 110 …, 2022 | 28 | 2022 |
| Thermal characteristics of Daegu using land cover data and satellite-derived surface temperature downscaled based on machine learning C Yoo, J Im, S Park, D Cho Korean Journal of Remote Sensing 33 (6_2), 1101-1118, 2017 | 23 | 2017 |
| Multi-task learning based tropical cyclone intensity monitoring and forecasting through fusion of geostationary satellite data and numerical forecasting model output J Lee, C Yoo, J Im, Y Shin, D Cho Korean Journal of Remote Sensing 36 (5_3), 1037-1051, 2020 | 13 | 2020 |
| A hybrid machine learning approach to investigate the changing urban thermal environment by dynamic land cover transformation: a case study of Suwon, Republic of Korea S Lee, C Yoo, J Im, D Cho, Y Lee, D Bae International Journal of Applied Earth Observation and Geoinformation 122 …, 2023 | 12 | 2023 |
| Diurnal urban heat risk assessment using extreme air temperatures and real-time population data in Seoul C Yoo, J Im, Q Weng, D Cho, E Kang, Y Shin Iscience 26 (11), 2023 | 10 | 2023 |
| Generation of daily high-resolution sea surface temperature for the seas around the Korean peninsula using multi-satellite data and artificial intelligence S Jung, M Choo, J Im, D Cho Korean Journal of Remote Sensing 38 (5_2), 707-723, 2022 | 6 | 2022 |
| Analysis of thermal environment by urban expansion using KOMPSAT and Landsat 8: Sejong City C Yoo, S Park, Y Kim, D Cho Korean Journal of Remote Sensing 35 (6_4), 1403-1415, 2019 | 6 | 2019 |
| A new statistical downscaling approach for short‐term forecasting of summer air temperatures through a fusion of deep learning and spatial interpolation D Cho, J Im, S Jung Quarterly Journal of the Royal Meteorological Society 150 (760), 1222-1242, 2024 | 4 | 2024 |
| Development of model output statistics based on the least absolute shrinkage and selection operator regression for forecasting next‐day maximum temperature in South Korea D Yoon, K Kim, DH Cha, MI Lee, J Im, D Cho, KH Min Quarterly Journal of the Royal Meteorological Society 148 (745), 1929-1944, 2022 | 4 | 2022 |
| Comparative Assessment of Linear Regression and Machine Learning for Analyzing the Spatial Distribution of Ground-level NO2 Concentrations: A Case Study for … E Kang, C Yoo, Y Shin, D Cho, J Im Korean Journal of Remote Sensing 37 (6_1), 1739-1756, 2021 | 4 | 2021 |
| Trend analysis of vegetation changes of Korean fir (Abies koreana Wilson) in Hallasan and Jirisan using MODIS imagery M Choo, C Yoo, J Im, D Cho, Y Kang, H Oh, J Lee Korean Journal of Remote Sensing 39 (3), 325-338, 2023 | 3 | 2023 |
| Sensitivity analysis for CAS500-4 atmospheric correction using simulated images and suggestion of the use of geostationary satellite-based atmospheric parameters Y Kang, D Cho, D Han, J Im, J Lim, K Oh, E Kwon Korean Journal of Remote Sensing 37 (5), 1029-1042, 2021 | 3 | 2021 |
Jungho ImUlsan National Institute of Science and TechnologyDirección de correo verificada de unist.ac.kr