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RESEARCH

Goal 9: Industry, innovation and infrastructure

2023

GOCI-II 대기상한 반사도와 기계학습을 이용한 남한 지역 시간별 에어로졸 광학 두께 산출
양세영;최현영; 임정호
대한원격탐사학회지, 39(5-3), pp.933-948

Direct aerosol optical depth retrievals using MODIS reflectance data and machine learning over East Asia
Kang, Eunjin; Park, Seonyoung; Kim, Miae; Yoo, Cheolhee; Im, Jungho; Song, Chang-Keun
ATMOSPHERIC ENVIRONMENT, v.309, pp.119951

2022

스태킹 앙상블 모델을 이용한 시간별 지상 오존 공간내삽 정확도 향상
김예진; 강은진; 조동진; 이시우; 임정호
한국지리정보학회지, 25(3), pp.74-99.

Geostationary satellite-derived ground-level particulate matter concentrations using real-time machine learning in Northeast Asia
Park, Seohui; Im, Jungho, Kim Jhoon; Kim, Sang-min
ENVIRONMENTAL POLLUTION, v.306, pp.119425

Air Quality Forecasts Improved by Combining Data Assimilation and Machine Learning With Satellite AOD
Lee, Seunghee; Park, Seohui; Lee, Myong-In; Kim, Ganghan; Im, Jungho; Song, Chang-Keun
GEOPHYSICAL RESEARCH LETTERS, v.49, no.1, pp.e2021GL096

Improved retrievals of aerosol optical depth and fine mode fraction from GOCI geostationary satellite data using machine learning over East Asia
Kang, Yoojin; Kim, Miae; Kang, Eunjin; Cho, Dongjin; Im, Jungho

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, v.183, pp.253 - 268

2021

서울 지역 지상 NO2 농도 공간 분포 분석을 위한 회귀 모델 및 기계학습 기법 비교
강은진; 유철희; 신예지; 조동진; 임정호
대한원격탐사학회지, v.37, no.6-1, pp.1739 - 1756

기계학습을 활용한 동아시아 지역의 TROPOMI 기반 SO2 지상농도 추정
최현영; 강유진; 임정호
대한원격탐사학회지, v.37, no.2, pp.275-290

2020

Improving Local Climate Zone Classification Using Incomplete Building Data and Sentinel 2 Images Based on Convolutional Neural Networks
Yoo, Cheolhee; Lee, Yeonsu; Cho, Dongjin; Im, Jungho; Han, Daehyeon
REMOTE SENSING, v.12, no.21, pp.3552

위성 자료와 수치모델 자료를 활용한 스태킹 앙상블 기반 SO2 지상농도 추정
최현영; 강유진; 임정호; 신민소; 박서희; 김상민
대한원격탐사학회지, v.36, no.5, pp.1053-1066

Estimation of spatially continuous daytime particulate matter concentrations under all sky conditions through the synergistic use of satellite-based AOD and numerical models
Park, Seohui; Lee, Junghee; Im, Jungho; Song, Chang-Keun; Choi, Myungje; Kim, Jhoon; Lee, Seungun; Park, Rokjin; Kim, Sang-Min; Yoon, Jongmin; Lee, Dong-Won; Quackenbush, Lindi J.
SCIENCE OF THE TOTAL ENVIRONMENT, v.713, pp.136516

Estimating ground-level particulate matter concentrations using satellite-based data: a review
Shin, Minso; Kang, Yoojin; Park, Seohui; Im, Jungho; Yoo, Cheolhee; Quackenbush, Lindi J.
GISCIENCE & REMOTE SENSING, v.57, no.2, pp.174-189

2019

Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images
Yoo, Cheolhee; Han, Daehyeon; Im, Jungho; Bechtel, Benjamin
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, v.157, pp.155 - 170

Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea
Park, Seohui; Shin, Minso; Im, Jungho; Song, Chang-Keun; Choi, Myungje; Kim, Jhoon; Lee, Seungun; Park, Rokjin; Kim, Jiyoung; Lee, Dong-Won; Kim, Sang-Kyun
ATMOSPHERIC CHEMISTRY AND PHYSICS, v.19, no.2, pp.1097 - 1113

2017

기계학습 기반 상세화를 통한 위성 지표면온도와 환경부 토지피복도를 이용한 열환경 분석: 대구광역시를 중심으로
유철희; 임정호; 박선영; 조동진
대한원격탐사학회지, v.33, no.6-2, pp.1101 - 1118

(The content of this publication has not been approved by the United Nations and does not reflect the views of the United Nations or its officials or Member States.)

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