2022-11 | A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency | Kang, Yoojin; Jang, Eunna; Im, Jungho; Kwon, Chungeun | ARTICLE | 295 |
2019-02 | Detection and monitoring of forest fires using Himawari-8 geostationary satellite data in South Korea | Jang, Eunna; Kang, Yoojin; Im, Jungho; Lee, Dong-Won; Yoon, Jongmin; Kim, Sang-Kyun | ARTICLE | 806 |
2020-11 | Developing a New Hourly Forest Fire Risk Index Based on Catboost in South Korea | Kang, Yoojin; Jang, Eunna; Im, Jungho; Kwon, Chungeun; Kim, Sungyong | ARTICLE | 517 |
2022-10 | Development of Mid-range Forecast Models of Forest Fire Risk Using Machine Learning | Park, Sumin; Son, Bokyung; Im, Jungho; Kang, Yoojin; Kwon, Chungeun; Kim, Sungyong | ARTICLE | 546 |
2020-02 | Estimating ground-level particulate matter concentrations using satellite-based data: a review | Shin, Minso; Kang, Yoojin; Park, Seohui; Im, Jungho; Yoo, Cheolhee; Quackenbush, Lindi J. | ARTICLE | 758 |
2021-12 | Estimation of Leaf Area Index Based on Machine Learning/PROSAIL Using Optical Satellite Imagery | Lee, Jaese; Kang, Yoojin; Son, Bokyung; Im, Jungho; Jang, Keunchang | ARTICLE | 509 |
2021-11 | Estimation of surface-level NO2 and O-3 concentrations using TROPOMI data and machine learning over East Asia | Kang, Yoojin; Choi, Hyunyoung; Im, Jungho; Park, Seohui; Shin, Minso; Song, Chang-Keun; Kim, Sangmin | ARTICLE | 368 |
2021-04 | Estimation of TROPOMI-derived Ground-level SO2 Concentrations Using Machine Learning Over East Asia | Choi, Hyunyoung; Kang, Yoojin; Im, Jungho | ARTICLE | 715 |
2018-04-12 | Forest fire detection and monitoring in South Korea using geostationary meteorological satellite data | Jang, Eunna; Im, Jungho; Kang, Yoojin | CONFERENCE | 332 |
2022-01 | Improved retrievals of aerosol optical depth and fine mode fraction from GOCI geostationary satellite data using machine learning over East Asia | Kang, Yoojin; Kim, Miae; Kang, Eunjin; Cho, Dongjin; Im, Jungho | ARTICLE | 399 |
2018-12-11 | Machine learning apporaches to wildfire detection using geostationary satellite data | Kang, Yoojin; Im, Jungho; Jang, Kunna | CONFERENCE | 332 |
2018-05-11 | Machine learning apporaches to wildfire detection using geostationary satellite data | Kang, Yoojin; Jang, Kunna; Im, Jungho | CONFERENCE | 378 |
2023-02 | Machine learning-based wildfire monitoring and characterization using geostationary satellite data | Im, Jungho; Kang, Yoojin | Doctoral thesis | 698 |
2020-10 | Monitoring Ground-level SO2 Concentrations Based on a Stacking Ensemble Approach Using Satellite Data and Numerical Models | Choi, Hyunyoung; Kang, Yoojin; Im, Jungho; Park, Seohui; Shin, Minso; Kim, Sang-Min | ARTICLE | 649 |
2018-05-11 | Monitoring of overshooting tops over East Asia using Himawari-8 data and machine learning approaches? | Lee, Juhyun; Kim, Miae; Im, Jungho; Kang, Yoojin | CONFERENCE | 323 |
2023-04 | Retrieval of hourly PM2.5 using top-of-atmosphere reflectance from geostationary ocean color imagers I and II | Choi, Hyunyoung; Park, Seonyoung; Kang, Yoojin; Im, Jungho; Song, Sanghyeon | ARTICLE | 236 |
2021-10 | Sensitivity analysis for CAS500-4 atmospheric correction using simulated images and suggestion of the use of geostationary satellite-based atmospheric parameters | Kang, Yoojin; Cho, Dongjin; Han, Daehyeon; Im, Jungho; Lim, Joongbi; Oh, Kum-hui; Kwon, Eonhye | ARTICLE | 413 |
2023-12 | Toward an adaptable deep-learning model for satellite-based wildfire monitoring with consideration of environmental conditions | Kang, Yoojin; Sung, Taejun; Im, Jungho | ARTICLE | 179 |
2023-06 | Trend Analysis ofVegetation Changes of Korean Fir (Abies koreana Wilson) in Hallasan and Jirisan Using MODIS Imagery | Choo, Minki; Yo, Cheolhee; Im, Jungho; Cho, Dongjin; Kang, Yoojin; Oh, Hyunkyung; Lee, Jongsung | ARTICLE | 181 |
2020-10 | Wildfire Severity Mapping Using Sentinel Satellite Data Based on Machine Learning Approaches | Sim, Seongmun; Kim, Woohyeok; Lee, Jaese; Kang, Yoojin; Im, Jungho; Kwon, Chunguen; Kim, Sungyong | ARTICLE | 431 |