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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 Date	Title	Author(s)	Type	View	Altmetrics
2021-08	Satellite-based Drought Forecasting: Research Trends, Challenges, and Future Directions	Son, Bokyung; Im, Jungho; Park, Sumin, et al	ARTICLE	154	Satellite-based Drought Forecasting: Research Trends, Challenges, and Future Directions
2021-04	Estimation of TROPOMI-derived Ground-level SO2 Concentrations Using Machine Learning Over East Asia	Choi, Hyunyoung; Kang, Yoojin; Im, Jungho	ARTICLE	517	Estimation of TROPOMI-derived Ground-level SO2 Concentrations Using Machine Learning Over East Asia
2021-04	Estimation of ground-level PM10 and PM2.5 concentrations using boosting-based machine learning from satellite and numerical weather prediction data	Park, Seohui; Kim, Miae; Im, Jungho	ARTICLE	469	Estimation of ground-level PM10 and PM2.5 concentrations using boosting-based machine learning from satellite and numerical weather prediction data
2021-03	On the use of machine learning based ensemble approaches to improve evapotranspiration estimates from croplands across a wide environmental gradient	Bai, Yun; Zhang, Sha; Bhattarai, Nishan, et al	ARTICLE	277	On the use of machine learning based ensemble approaches to improve evapotranspiration estimates from croplands across a wide environmental gradient
2021-01	A new drought monitoring approach: Vector Projection Analysis (VPA)	Son, Bokyung; Park, Sumin; Im, Jungho, et al	ARTICLE	374	A new drought monitoring approach: Vector Projection Analysis (VPA)
2021-01	Improvement of SMAP sea surface salinity in river-dominated oceans using machine learning approaches	Jang, Eunna; Kim, Young Jun; Im, Jungho, et al	ARTICLE	280	Improvement of SMAP sea surface salinity in river-dominated oceans using machine learning approaches
2020-12	Synergistic use of hyperspectral uv-visible omi and broadband meteorological imager modis data for a merged aerosol product	Go, Sujung; Kim, Jhoon; Park, Sang Seo, et al	ARTICLE	535	Synergistic use of hyperspectral uv-visible omi and broadband meteorological imager modis data for a merged aerosol product
2020-11	Short-Term Forecasting of Satellite-Based Drought Indices Using Their Temporal Patterns and Numerical Model Output	Park, Sumin; Im, Jungho; Han, Daehyeon, et al	ARTICLE	257	Short-Term Forecasting of Satellite-Based Drought Indices Using Their Temporal Patterns and Numerical Model Output
2020-11	Improving Local Climate Zone Classification Using Incomplete Building Data and Sentinel 2 Images Based on Convolutional Neural Networks	Yoo, Cheolhee; Lee, Yeonsu; Cho, Dongjin, et al	ARTICLE	290	Improving Local Climate Zone Classification Using Incomplete Building Data and Sentinel 2 Images Based on Convolutional Neural Networks
2020-11	Developing a New Hourly Forest Fire Risk Index Based on Catboost in South Korea	Kang, Yoojin; Jang, Eunna; Im, Jungho, et al	ARTICLE	355	Developing a New Hourly Forest Fire Risk Index Based on Catboost in South Korea
2020-10	Wildfire Severity Mapping Using Sentinel Satellite Data Based on Machine Learning Approaches	Sim, Seongmun; Kim, Woohyeok; Lee, Jaese, et al	ARTICLE	258	Wildfire Severity Mapping Using Sentinel Satellite Data Based on Machine Learning Approaches
2020-10	Multi-task learning based tropical cyclone intensity monitoring and forecasting through fusion of geostationary satellite data and numerical forecasting model output	Lee, Juhyun; Yoo, Cheolhee; Im, Jungho, et al	ARTICLE	405	Multi-task learning based tropical cyclone intensity monitoring and forecasting through fusion of geostationary satellite data and numerical forecasting model output
2020-10	Prediction of sea surface temperature and detection of ocean heat wave in the South sea of Korea using time-series deep-learning approaches	Jung, Sihun; Kim, Young Jun; Park, Sumin, et al	ARTICLE	283	Prediction of sea surface temperature and detection of ocean heat wave in the South sea of Korea using time-series deep-learning approaches
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, et al	ARTICLE	473	Monitoring Ground-level SO2 Concentrations Based on a Stacking Ensemble Approach Using Satellite Data and Numerical Models
2020-10	Remote sensing-assisted disaster monitoring and risk analysis	Im, Jungho; Sohn, Hong-Gyoo; Kim, Duk-jin, et al	ARTICLE	233	Remote sensing-assisted disaster monitoring and risk analysis
2020-09	Forest and Crop Leaf Area Index Estimation Using Remote Sensing: Research Trends and Future Directions	Xu, Jin; Quackenbush, Lindi J.; Volk, Timothy A., et al	ARTICLE	455	Forest and Crop Leaf Area Index Estimation Using Remote Sensing: Research Trends and Future Directions
2020-08	Spatial Downscaling of MODIS Land Surface Temperature: Recent Research Trends, Challenges, and Future Directions	Yoo, Cheolhee; Im, Jungho; Park, Sumin, et al	ARTICLE	273	Spatial Downscaling of MODIS Land Surface Temperature: Recent Research Trends, Challenges, and Future Directions
2020-07	Improvement of spatial interpolation accuracy of daily maximum air temperature in urban areas using a stacking ensemble technique	Cho, Dongjin; Yoo, Cheolhee; Im, Jungho, et al	ARTICLE	383	Improvement of spatial interpolation accuracy of daily maximum air temperature in urban areas using a stacking ensemble technique
2020-07	Earth observations and geographic information science for sustainable development goals	Im, Jungho	ARTICLE	393	Earth observations and geographic information science for sustainable development goals
2020-06	Object-based landfast sea ice detection over West Antarctica using time series ALOS PALSAR data	Kim, Miae; Kim, Hyun-Cheol; Im, Jungho, et al	ARTICLE	430	Object-based landfast sea ice detection over West Antarctica using time series ALOS PALSAR data

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