사진

  • ResearcherID
  • ORCiD
  • Scopus
  • Google Citations

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, 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.
This table browses all dspace content
Issue DateTitleAuthor(s)TypeViewAltmetrics
2020-04Comparative Assessment of Various Machine Learning-Based Bias Correction Methods for Numerical Weather Prediction Model Forecasts of Extreme Air Temperatures in Urban AreasCho, Dongjin; Yoo, Cheolhee; Im, Jungho, et alARTICLE170 Comparative Assessment of Various Machine Learning-Based Bias Correction Methods for Numerical Weather Prediction Model Forecasts of Extreme Air Temperatures in Urban Areas
2020-04Different Spectral Domain Transformation for Land Cover Classification Using Convolutional Neural Networks with Multi-Temporal Satellite ImageryLee, Junghee; Han, Daehyeon; Shin, Minso, et alARTICLE164 Different Spectral Domain Transformation for Land Cover Classification Using Convolutional Neural Networks with Multi-Temporal Satellite Imagery
2020-03Prediction of monthly Arctic sea ice concentrations using satellite and reanalysis data based on convolutional neural networksKim, Young Jun; Kim, Hyun-Cheol; Han, Daehyeon, et alARTICLE221 Prediction of monthly Arctic sea ice concentrations using satellite and reanalysis data based on convolutional neural networks
2020-02Estimating ground-level particulate matter concentrations using satellite-based data: a reviewShin, Minso; Kang, Yoojin; Park, Seohui, et alARTICLE248 Estimating ground-level particulate matter concentrations using satellite-based data: a review
2020-01Tropical Cyclone Intensity Estimation Using Multi-Dimensional Convolutional Neural Networks from Geostationary Satellite DataLee, Juhyun; Im, Jungho; Cha, Dong-Hyun, et alARTICLE238 Tropical Cyclone Intensity Estimation Using Multi-Dimensional Convolutional Neural Networks from Geostationary Satellite Data
2019-12기상 예보 및 위성 자료를 이용한 우리나라 산불위험지수의 시공간적 고도화강유진; 박수민; 장은나, et alARTICLE237 기상 예보 및 위성 자료를 이용한 우리나라 산불위험지수의 시공간적 고도화
2019-12산불발생위험 추정을 위한 위성기반 가뭄지수 개발박수민; 손보경; 임정호, et alARTICLE150 산불발생위험 추정을 위한 위성기반 가뭄지수 개발
2019-11Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat imagesYoo, Cheolhee; Han, Daehyeon; Im, Jungho, et alARTICLE248 Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images
2019-11Comparison of Five Spatio-Temporal Satellite Image Fusion Models over Landscapes with Various Spatial Heterogeneity and Temporal VariationLiu, Maolin; Ke, Yinghai; Yin, Qi, et alARTICLE153 Comparison of Five Spatio-Temporal Satellite Image Fusion Models over Landscapes with Various Spatial Heterogeneity and Temporal Variation
2019-10Delineation of high resolution climate regions over the Korean Peninsula using machine learning approachesPark, Sumin; Park, Haemi; Im, Jungho, et alARTICLE238 Delineation of high resolution climate regions over the Korean Peninsula using machine learning approaches
2019-08Retrieval of total precipitable water from Himawari-8 AHI data: A comparison of random forest, extreme gradient boosting, and deep neural networkLee, Yeonjin; Han, Daehyeon; Ahn, Myoung-Hwan, et alARTICLE237 Retrieval of total precipitable water from Himawari-8 AHI data: A comparison of random forest, extreme gradient boosting, and deep neural network
2019-08Airborne Lidar Sampling Strategies to Enhance Forest Aboveground Biomass Estimation from Landsat ImageryLi, Siqi; Quackenbush, Lindi J.; Im, JunghoARTICLE276 Airborne Lidar Sampling Strategies to Enhance Forest Aboveground Biomass Estimation from Landsat Imagery
2019-07Zooplankton and micronekton respond to climate fluctuations in the Amundsen Sea polynya, AntarcticaLa, Hyoung Sul; Park, Keyhong; Wahlin, Anna, et alARTICLE298 Zooplankton and micronekton respond to climate fluctuations in the Amundsen Sea polynya, Antarctica
2019-06Improvement of satellite-based estimation of gross primary production through optimization of meteorological parameters and high resolution land cover information at regional scale over East AsiaPark, Haemi; Im, Jungho; Kim, MiaeARTICLE358 Improvement of satellite-based estimation of gross primary production through optimization of meteorological parameters and high resolution land cover information at regional scale over East Asia
2019-06A novel framework of detecting convective initiation combining automated sampling, machine learning, and repeated model tuning from geostationary satellite dataHan, Daehyeon; Lee, Juhyun; Im, Jungho, et alARTICLE386 A novel framework of detecting convective initiation combining automated sampling, machine learning, and repeated model tuning from geostationary satellite data
2019-05Machine learning approaches for detecting tropical cyclone formation using satellite dataKim, Minsang; Park, Myung-Sook; Im, Jungho, et alARTICLE395 Machine learning approaches for detecting tropical cyclone formation using satellite data
2019-02Detection and monitoring of forest fires using Himawari-8 geostationary satellite data in South KoreaJang, Eunna; Kang, Yoojin; Im, Jungho, et alARTICLE345 Detection and monitoring of forest fires using Himawari-8 geostationary satellite data in South Korea
2019-01Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South KoreaPark, Seohui; Shin, Minso; Im, Jungho, et alARTICLE531 Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea
2018-12Convolutional Neural Network-Based Land Cover Classification Using 2-D Spectral Reflectance Curve Graphs With Multitemporal Satellite ImageryKim, Miae; Lee, Junghee; Han, Daehyun, et alARTICLE460 Convolutional Neural Network-Based Land Cover Classification Using 2-D Spectral Reflectance Curve Graphs With Multitemporal Satellite Imagery
2018-12기계학습 기반의 IABP 부이 자료와 AMSR2 위성영상을 이용한 여름철 북극 대기 온도 추정한대현; 김영준; 임정호, et alARTICLE461 기계학습 기반의 IABP 부이 자료와 AMSR2 위성영상을 이용한 여름철 북극 대기 온도 추정

MENU