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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, 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
2016-12Intercomparison of Terrestrial Carbon Fluxes and Carbon Use Efficiency Simulated by CMIP5 Earth System ModelsKim, Dongmin; Lee, Myong-In; Jeong, Su-Jong, et alARTICLE424 Intercomparison of Terrestrial Carbon Fluxes and Carbon Use Efficiency Simulated by CMIP5 Earth System Models
2016-09Detection of tropical cyclone genesis via quantitative satellite ocean surface wind pattern and intensity analyses using decision treesPark, Myung-Sook; Kim, Minsang; Lee, Myong-In, et alARTICLE567 Detection of tropical cyclone genesis via quantitative satellite ocean surface wind pattern and intensity analyses using decision trees
2016-09Arctic Sea Ice Thickness Estimation from CryoSat-2 Satellite Data Using Machine Learning-Based Lead DetectionLee, Sanggyun; Im, Jungho; Kim, Jinwoo, et alARTICLE484 Arctic Sea Ice Thickness Estimation from CryoSat-2 Satellite Data Using Machine Learning-Based Lead Detection
2016-08Downscaling of AMSR-E soil moisture with MODIS products using machine learning approachesIm, Jungho; Park, Seonyoung; Rhee, Jinyoung, et alARTICLE625 Downscaling of AMSR-E soil moisture with MODIS products using machine learning approaches
2016-07Evaluating five remote sensing based single-source surface energy balance models for estimating daily evapotranspiration in a humid subtropical climateBhattarai, Nishan; Shaw, Stephen B.; Quackenbush, Lindi J., et alARTICLE786 Evaluating five remote sensing based single-source surface energy balance models for estimating daily evapotranspiration in a humid subtropical climate
2016-06GOCI 위성영상과 기계학습을 이용한 한반도 연안 수질평가지수 추정Jang, Eunna; Im, Jungho; Ha, Sunghyun, et alARTICLE795 GOCI 위성영상과 기계학습을 이용한 한반도 연안 수질평가지수 추정
2016-05An improved tree crown delineation method based on live crown ratios from airborne LiDAR dataFang, Fang; Im, Jungho; Lee, Junghee, et alARTICLE705 An improved tree crown delineation method based on live crown ratios from airborne LiDAR data
2016-03Downscaling of MODIS One kilometer evapotranspiration using Landsat-8 data and machine learning approachesKe, Yinghai; Im, Jungho; Park, Seonyoung, et alARTICLE455 Downscaling of MODIS One kilometer evapotranspiration using Landsat-8 data and machine learning approaches
2016-02Spatial and diurnal variations of storm heights in the East Asia summer monsoon: storm height regimes and large-scale diurnal modulationPark, Myung-Sook; Lee, Myong-In; Kim, Hyerim, et alARTICLE766 Spatial and diurnal variations of storm heights in the East Asia summer monsoon: storm height regimes and large-scale diurnal modulation
2016-02Chlorophyll-a concentration estimation using three difference bio-optical algorithms, including a correction for the low-concentration range: the case of the Yiam reservoir, KoreaPyo, JongCheol; Ha, SeongHyeon; Yakov A. Pachepsky, et alARTICLE670 Chlorophyll-a concentration estimation using three difference bio-optical algorithms, including a correction for the low-concentration range: the case of the Yiam reservoir, Korea
2016-01Drought assessment and monitoring through blending of multi-sensor indices using machine learning approaches for different climate regionsPark, Seonyoung; Im, Jungho; Jang, Eunna, et alARTICLE767 Drought assessment and monitoring through blending of multi-sensor indices using machine learning approaches for different climate regions
2016-01Retrieval of Melt Ponds on Arctic Multiyear Sea Ice in Summer from TerraSAR-X Dual-Polarization Data Using Machine Learning Approaches: A Case Study in the Chukchi Sea with Mid-Incidence Angle DataHan, Hyangsun; Kim, Miae; Sim, Seongmun, et alARTICLE697 Retrieval of Melt Ponds on Arctic Multiyear Sea Ice in Summer from TerraSAR-X Dual-Polarization Data Using Machine Learning Approaches: A Case Study in the Chukchi Sea with Mid-Incidence Angle Data
2015-12A novel transferable individual tree crown delineation model based on Fishing Net Dragging and boundary classificationLiu, Tao; Im, Jungho; Quackenbush, Lindi J.ARTICLE771 A novel transferable individual tree crown delineation model based on Fishing Net Dragging and boundary classification
2015-12A Novel Bias Correction Method for Soil Moisture and Ocean Salinity (SMOS) Soil Moisture: Retrieval EnsemblesLee, Ju Hyoung; Im, JunghoARTICLE545 A Novel Bias Correction Method for Soil Moisture and Ocean Salinity (SMOS) Soil Moisture: Retrieval Ensembles
2015-12Change Analysis of Aboveground Forest Carbon Stocks According to the Land Cover Change Using Multi-Temporal Landsat TM Images and Machine Learning AlgorithmsLee, Jung-Hee; Im, Jungho; Kim, Kyoung-Min, et alARTICLE478 Change Analysis of Aboveground Forest Carbon Stocks According to the Land Cover Change Using Multi-Temporal Landsat TM Images and Machine Learning Algorithms
2015-07Detection of Convective Initiation Using Meteorological Imager Onboard Communication, Ocean, and Meteorological Based on Machine Learning ApproachesHan, Hyangsun; Lee, Sanggyun; Im, Jungho, et alARTICLE797 Detection of Convective Initiation Using Meteorological Imager Onboard Communication, Ocean, and Meteorological Based on Machine Learning Approaches
2015-07Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observationsKe, Yinghai; Im, Jungho; Lee, Junghee, et alARTICLE640 Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations
2015-03Landfast sea ice monitoring using multisensor fusion in the AntarcticKim, Miae; Im, Jungho; Han, Hyangsun, et alARTICLE836 Landfast sea ice monitoring using multisensor fusion in the Antarctic
2014-10Building type classification using spatial and landscape attributes derived from LiDAR remote sensing dataLu, Zhenyu; Im, Jungho; Rhee, Jinyoung, et alARTICLE869 Building type classification using spatial and landscape attributes derived from LiDAR remote sensing data
2014-09The MODIS ice surface temperature product as an indicator of sea ice minimum over the Arctic OceanKang, Daehyun; Im, Jungho; Lee, Myong-In, et alARTICLE776 The MODIS ice surface temperature product as an indicator of sea ice minimum over the Arctic Ocean

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