사진

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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
2023-01Improved Tropical Cyclone Track Simulation over the Western North Pacific using the WRF Model and a Machine Learning MethodKim, Kyoungmin; Yoon, Donghyuck; Cha, Dong-Hyun, et alARTICLE302 Improved Tropical Cyclone Track Simulation over the Western North Pacific using the WRF Model and a Machine Learning Method
2023-01Remote sensing of sea surface salinity: challenges and research directionsKim, Young Jun; Han, Daehyeon; Jang, Eunna, et alARTICLE38 Remote sensing of sea surface salinity: challenges and research directions
2022-12Performance of Drought Indices in Assessing Rice Yield in North Korea and South Korea under the Different Agricultural SystemsPark, Seonyoung; Lee, Jaese; Yeom, Jongmin, et alARTICLE80 Performance of Drought Indices in Assessing Rice Yield in North Korea and South Korea under the Different Agricultural Systems
2022-11A deep learning model using geostationary satellite data for forest fire detection with reduced detection latencyKang, Yoojin; Jang, Eunna; Im, Jungho, et alARTICLE124 A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency
2022-10An Advanced Operational Approach for Tropical Cyclone Center Estimation Using Geostationary-Satellite-Based Water Vapor and Infrared ChannelsShin, Yeji; Lee, Juhyun; Im, Jungho, et alARTICLE106 An Advanced Operational Approach for Tropical Cyclone Center Estimation Using Geostationary-Satellite-Based Water Vapor and Infrared Channels
2022-10Estimation of shrub willow biophysical parameters across time and space from Sentinel-2 and unmanned aerial system (UAS) dataXu, Jin; Quackenbush, Lindi J.; Volk, Timothy A., et alARTICLE150 Estimation of shrub willow biophysical parameters across time and space from Sentinel-2 and unmanned aerial system (UAS) data
2022-10Development of Mid-range Forecast Models of Forest Fire Risk Using Machine LearningPark, Sumin; Son, Bokyung; Im, Jungho, et alARTICLE224 Development of Mid-range Forecast Models of Forest Fire Risk Using Machine Learning
2022-10Estimation of High Resolution Sea Surface Salinity Using Multi Satellite Data and Machine LearningSung, Taejun; Sim, Seongmun; Jang, Eunna, et alARTICLE280 Estimation of High Resolution Sea Surface Salinity Using Multi Satellite Data and Machine Learning
2022-10Forest Burned Area Detection Using Landsat 8/9 and Sentinel-2 A/B Imagery with Various Indices: A Case Study of UljinKim, Byeongcheol; Lee, Kyungil; Park, Seonyoung, et alARTICLE124 Forest Burned Area Detection Using Landsat 8/9 and Sentinel-2 A/B Imagery with Various Indices: A Case Study of Uljin
2022-10Disaster Prediction, Monitoring, and Response Using Remote Sensing and GISKim, Junwoo; Kim, Duk-jin; Sohn, Hong-Gyoo, et alARTICLE186 Disaster Prediction, Monitoring, and Response Using Remote Sensing and GIS
2022-10Generation of Daily High-resolution Sea Surface Temperature for the Seas around the Korean Peninsula Using Multi-satellite Data and Artificial IntelligenceJung, Sihun; Choo, Minki; Im, Jungho, et alARTICLE146 Generation of Daily High-resolution Sea Surface Temperature for the Seas around the Korean Peninsula Using Multi-satellite Data and Artificial Intelligence
2022-09Multi-Platform LiDAR for Non-Destructive Individual Aboveground Biomass Estimation for Changbai Larch (Larix olgensis Henry) Using a Hierarchical Bayesian ApproachWang, Man; Im, Jungho; Zhao, Yinghui, et alARTICLE166 Multi-Platform LiDAR for Non-Destructive Individual Aboveground Biomass Estimation for Changbai Larch (Larix olgensis Henry) Using a Hierarchical Bayesian Approach
2022-09스태킹 앙상블 모델을 이용한 시간별 지상 오존 공간내삽 정확도 향상김예진; 강은진; 조동진, et alARTICLE48 스태킹 앙상블 모델을 이용한 시간별 지상 오존 공간내삽 정확도 향상
2022-09우리나라 연안 대형저서동물 시·공간 군집 특성 분석김영준; 임정호; 조춘옥, et alARTICLE54 우리나라 연안 대형저서동물 시·공간 군집 특성 분석
2022-08Geostationary satellite-derived ground-level particulate matter concentrations using real-time machine learning in Northeast AsiaPark, Seohui; Im, Jungho; Kim, Jhoon, et alARTICLE179 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 alARTICLE271 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 alARTICLE170 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 alARTICLE206 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 alARTICLE263 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 alARTICLE279 Development of model output statistics based on the least absolute shrinkage and selection operator regression for forecasting next-day maximum temperature in South Korea

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