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Im, Jungho (임정호)

Department: Department of Civil, Urban, Earth, and Environmental Engineering(지구환경도시건설공학과)

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
2023-12	Towards accurate individual tree parameters estimation in dense forest: optimized coarse-to-fine algorithms for registering UAV and terrestrial LiDAR data	Zhao, Yuting; Im, Jungho; Zhen, Zhen, et al	ARTICLE	1852	Towards accurate individual tree parameters estimation in dense forest: optimized coarse-to-fine algorithms for registering UAV and terrestrial LiDAR data
2023-12	Precipitation nowcasting using ground radar data and simpler yet better video prediction deep learning	Han, Daehyeon; Choo, Minki; Im, Jungho, et al	ARTICLE	1266	Precipitation nowcasting using ground radar data and simpler yet better video prediction deep learning
2023-12	Combination four different ensemble algorithms with the generalized linear model (GLM) for predicting forest fire susceptibility	Janizadeh, Saeid; Bateni, Sayed M.; Jun, Changhyun, et al	ARTICLE	545	Combination four different ensemble algorithms with the generalized linear model (GLM) for predicting forest fire susceptibility
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	163	Toward an adaptable deep-learning model for satellite-based wildfire monitoring with consideration of environmental conditions
2023-09	Direct aerosol optical depth retrievals using MODIS reflectance data and machine learning over East Asia	Kang, Eunjin; Park, Seonyoung; Kim, Miae, et al	ARTICLE	502	Direct aerosol optical depth retrievals using MODIS reflectance data and machine learning over East Asia
2023-09	Novel Features of Canopy Height Distribution for Aboveground Biomass Estimation Using Machine Learning: A Case Study in Natural Secondary Forests	Ma, Ye; Zhang, Lianjun; Im, Jungho, et al	ARTICLE	282	Novel Features of Canopy Height Distribution for Aboveground Biomass Estimation Using Machine Learning: A Case Study in Natural Secondary Forests
2023-08	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	Lee, Siwoo; Yoo, Cheolhee; Im, Jungho, et al	ARTICLE	190	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
2023-08	Improved Ocean-Fog Monitoring Using Himawari-8 Geostationary Satellite Data Based on Machine Learning With SHAP-Based Model Interpretation	Sim, Seongmun; Im, Jungho	ARTICLE	66	Improved Ocean-Fog Monitoring Using Himawari-8 Geostationary Satellite Data Based on Machine Learning With SHAP-Based Model Interpretation
2023-07	Fine particulate concentrations over East Asia derived from aerosols measured by the advanced Himawari Imager using machine learning	Cho, Yeseul; Kim, Jhoon; Lee, Jeewoo, et al	ARTICLE	192	Fine particulate concentrations over East Asia derived from aerosols measured by the advanced Himawari Imager using machine learning
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, et al	ARTICLE	172	Trend Analysis ofVegetation Changes of Korean Fir (Abies koreana Wilson) in Hallasan and Jirisan Using MODIS Imagery
2023-05	Atmospheric-correction-free red tide quantification algorithm for GOCI based on machine learning combined with a radiative transfer simulation	Kim, Young Jun; Kim, Wonkook; Im, Jungho, et al	ARTICLE	191	Atmospheric-correction-free red tide quantification algorithm for GOCI based on machine learning combined with a radiative transfer simulation
2023-05	Synergistic combination of information from ground observations, geostationary satellite, and air quality modeling towards improved PM2.5 predictability	Yu, Jinhyeok; Song, Chul H.; Lee, Dogyeong, et al	ARTICLE	250	Synergistic combination of information from ground observations, geostationary satellite, and air quality modeling towards improved PM2.5 predictability
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, et al	ARTICLE	230	Retrieval of hourly PM2.5 using top-of-atmosphere reflectance from geostationary ocean color imagers I and II
2023-01	Improved Tropical Cyclone Track Simulation over the Western North Pacific using the WRF Model and a Machine Learning Method	Kim, Kyoungmin; Yoon, Donghyuck; Cha, Dong-Hyun, et al	ARTICLE	507	Improved Tropical Cyclone Track Simulation over the Western North Pacific using the WRF Model and a Machine Learning Method
2023-01	Remote sensing of sea surface salinity: challenges and research directions	Kim, Young Jun; Han, Daehyeon; Jang, Eunna, et al	ARTICLE	348	Remote sensing of sea surface salinity: challenges and research directions
2022-12	Performance of Drought Indices in Assessing Rice Yield in North Korea and South Korea under the Different Agricultural Systems	Park, Seonyoung; Lee, Jaese; Yeom, Jongmin, et al	ARTICLE	119	Performance of Drought Indices in Assessing Rice Yield in North Korea and South Korea under the Different Agricultural Systems
2022-11	A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency	Kang, Yoojin; Jang, Eunna; Im, Jungho, et al	ARTICLE	288	A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency
2022-10	An Advanced Operational Approach for Tropical Cyclone Center Estimation Using Geostationary-Satellite-Based Water Vapor and Infrared Channels	Shin, Yeji; Lee, Juhyun; Im, Jungho, et al	ARTICLE	244	An Advanced Operational Approach for Tropical Cyclone Center Estimation Using Geostationary-Satellite-Based Water Vapor and Infrared Channels
2022-10	Estimation of shrub willow biophysical parameters across time and space from Sentinel-2 and unmanned aerial system (UAS) data	Xu, Jin; Quackenbush, Lindi J.; Volk, Timothy A., et al	ARTICLE	265	Estimation of shrub willow biophysical parameters across time and space from Sentinel-2 and unmanned aerial system (UAS) data
2022-10	Development of Mid-range Forecast Models of Forest Fire Risk Using Machine Learning	Park, Sumin; Son, Bokyung; Im, Jungho, et al	ARTICLE	541	Development of Mid-range Forecast Models of Forest Fire Risk Using Machine Learning

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