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Im, Jungho (임정호)

Department
Department of Urban and Environmental Engineering(도시환경공학과)
Website
http://iris.unist.ac.kr/
Lab
Intelligent Remote sensing and geospatial Information Science Lab. (환경원격탐사/인공지능 연구실)
Research Keywords
환경원격탐사, 인공지능, 공간모델링, 재난모니터링, 재난예측, Remote sensing, Geospatial modeling, Disaster monitoring and management, artificial intelligence
Research Interests
The IRIS lab utilizes remote sensing, GIS modeling, and artificial intelligence techniques to broaden and deepen our understanding of the Earth science under climate variability/change, and leverages this knowledge to better manage and control critical functions related to terrestrial, coastal, and polar ecosystems, natural and man-made disasters, water resources, and carbon sequestration.
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Issue DateTitleAuthor(s)TypeViewAltmetrics
2022-08Geostationary satellite-derived ground-level particulate matter concentrations using real-time machine learning in Northeast AsiaPark, Seohui; Im, Jungho; Kim, Jhoon, et alARTICLE25 Geostationary satellite-derived ground-level particulate matter concentrations using real-time machine learning in Northeast Asia
2022-06Improved soil moisture estimation: Synergistic use of satellite observations and land surface models over CONUS based on machine learningLee, Jaese; Park, Sumin; Im, Jungho, et alARTICLE124 Improved soil moisture estimation: Synergistic use of satellite observations and land surface models over CONUS based on machine learning
2022-06Downscaling MODIS nighttime land surface temperatures in urban areas using ASTER thermal data through local linear forestYoo, Cheolhee; Im, Jungho; Cho, Dongjin, et alARTICLE16 Downscaling MODIS nighttime land surface temperatures in urban areas using ASTER thermal data through local linear forest
2022-05Global sea surface salinity via the synergistic use of SMAP satellite and HYCOM data based on machine learningJang, Eunna; Kim, Young Jun; Im, Jungho, et alARTICLE98 Global sea surface salinity via the synergistic use of SMAP satellite and HYCOM data based on machine learning
2022-04All-Sky 1 km MODIS Land Surface Temperature Reconstruction Considering Cloud Effects Based on Machine LearningCho, Dongjin; Bae, Dukwon; Yoo, Cheolhee, et alARTICLE106 All-Sky 1 km MODIS Land Surface Temperature Reconstruction Considering Cloud Effects Based on Machine Learning
2022-04Development of model output statistics based on the least absolute shrinkage and selection operator regression for forecasting next-day maximum temperature in South KoreaYoon, Donghyuck; Kim, Kyoungmin; Cha, Dong-Hyun, et alARTICLE86 Development of model output statistics based on the least absolute shrinkage and selection operator regression for forecasting next-day maximum temperature in South Korea
2022-03A novel ensemble learning for post-processing of NWP Model's next-day maximum air temperature forecast in summer using deep learning and statistical approachesCho, Dongjin; Yoo, Cheolhee; Son, Bokyung, et alARTICLE61 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
2022-02High-Resolution Seamless Daily Sea Surface Temperature Based on Satellite Data Fusion and Machine Learning over Kuroshio ExtensionJung, Sihun; Yoo, Cheolhee; Im, JunghoARTICLE106 High-Resolution Seamless Daily Sea Surface Temperature Based on Satellite Data Fusion and Machine Learning over Kuroshio Extension
2022-01Air Quality Forecasts Improved by Combining Data Assimilation and Machine Learning With Satellite AODLee, Seunghee; Park, Seohui; Lee, Myong-In, et alARTICLE143 Air Quality Forecasts Improved by Combining Data Assimilation and Machine Learning With Satellite AOD
2022-01A Novel Tropical Cyclone Size Estimation Model Based on a Convolutional Neural Network Using Geostationary Satellite ImageryBaek, You-Hyun; Moon, Il-Ju; Im, Jungho, et alARTICLE101 A Novel Tropical Cyclone Size Estimation Model Based on a Convolutional Neural Network Using Geostationary Satellite Imagery
2022-01Improved retrievals of aerosol optical depth and fine mode fraction from GOCI geostationary satellite data using machine learning over East AsiaKang, Yoojin; Kim, Miae; Kang, Eunjin, et alARTICLE79 Improved retrievals of aerosol optical depth and fine mode fraction from GOCI geostationary satellite data using machine learning over East Asia
2021-12Rainfall intensity estimation using geostationary satellite data based on machine learning: A case study in the korean peninsula in summerShin, Yeji; Han, Daehyeon; Im, JunghoARTICLE237 Rainfall intensity estimation using geostationary satellite data based on machine learning: A case study in the korean peninsula in summer
2021-12Comparative Assessment of Linear Regression and Machine Learning for Analyzing the Spatial Distribution of Ground-level NO2 Concentrations: A Case Study for Seoul, KoreaKang, Eunjin; Yoo, Cheolhee; Shin, Yeji, et alARTICLE260 Comparative Assessment of Linear Regression and Machine Learning for Analyzing the Spatial Distribution of Ground-level NO2 Concentrations: A Case Study for Seoul, Korea
2021-12Estimation of Leaf Area Index Based on Machine Learning/PROSAIL Using Optical Satellite ImageryLee, Jaese; Kang, Yoojin; Son, Bokyung, et alARTICLE163 Estimation of Leaf Area Index Based on Machine Learning/PROSAIL Using Optical Satellite Imagery
2021-11Estimation of surface-level NO2 and O-3 concentrations using TROPOMI data and machine learning over East AsiaKang, Yoojin; Choi, Hyunyoung; Im, Jungho, et alARTICLE108 Estimation of surface-level NO2 and O-3 concentrations using TROPOMI data and machine learning over East Asia
2021-10Detection of Forest Fire Damage from Sentinel-1 SAR Data through the Synergistic Use of Principal Component Analysis and K-means Clustering [Sentinel-1 SAR K-means Clustering]Lee, Jaese; Kim, Woohyeok; Im, Jungho, et alARTICLE190 Detection of Forest Fire Damage from Sentinel-1 SAR Data through the Synergistic Use of Principal Component Analysis and K-means Clustering [Sentinel-1 SAR K-means Clustering]
2021-10Detection of arctic summer melt ponds using icesat-2 altimetry dataHan, Daehyeon; Kim, Young Jun; Jung, Sihun, et alARTICLE139 Detection of arctic summer melt ponds using icesat-2 altimetry data
2021-10Spatial downscaling of ocean colour-climate change initiative (OC-CCI) Forel-Ule Index using GOCI satellite image and machine learning techniqueSung, Taejun; Kim, Young Jun; Choi, Hyunyoung, et alARTICLE137 Spatial downscaling of ocean colour-climate change initiative (OC-CCI) Forel-Ule Index using GOCI satellite image and machine learning technique
2021-10One year of GOCI-II launch present and futureChoi, Jong-kuk; Park, Myung-sook; Han, Kyung-soo, et alARTICLE94 One year of GOCI-II launch present and future
2021-10Sensitivity analysis for CAS500-4 atmospheric correction using simulated images and suggestion of the use of geostationary satellite-based atmospheric parametersKang, Yoojin; Cho, Dongjin; Han, Daehyeon, et alARTICLE98 Sensitivity analysis for CAS500-4 atmospheric correction using simulated images and suggestion of the use of geostationary satellite-based atmospheric parameters

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