AI경영학과
이름
박선영
전공
AI(원격탐사)
TEL
02-970-9778
E-mail
sypark@seoultech.ac.kr
연구실
상상관 406호
교수소개 돌아가기
학력
- 2009년 3월 ~ 2013년 8월 UNIST 도시환경공학부
- 2013년 8월 ~ 2018년 2월 UNIST 도시환경공학부 환경과학공학
주요 경력
- 2019.09-2020.08 한국항공우주연구원 위성활용부 선임연구원
- 2011 Visiting researcher, NASA GSFC, GMAO, Greenbelt, Maryland, USA
주요논문 및 저서
◾ Yeom, J. M., Deo, R. C., Adamowski, J. F., Park, S., & Lee, C. S. (2020). Spatial mapping of short-term solar radiation prediction incorporating geostationary satellite images coupled with deep convolutional LSTM networks for South Korea. Environmental Research Letters.
◾ Park, S., Kang, D., Im, J., & Lee, M. (2020). Recent ENSO influence on East African drought during rainy seasons through the synergistic use of satellite and reanalysis data. ISPRS Journal of Photogrammetry and Remote Sensing, 162, 17-26.
◾ Yeom, J., Park, S., Chae, T., Kim, J., & Lee, C. (2019). Spatial Assessment of Solar Radiation by Machine Learning and Deep Neural Network Models Provided by the COMS MI Geostationary Satellite: A Case Study in South Korea. Sensors, 19(9), 2082.
◾ Park, S., Seo, E., Kang, D., Im, J., & Lee, M. (2018). Prediction of Drought on pantad scale using remote sensing data and MJO Index through Random forest over East Asia. Remote Sensing, 10(11), 447.
◾ Park, S., Im, J., Park, S., & Rhee, J. (2017). Drought monitoring using high resolution soil moisture through multi-sensor satellite data fusion over the Korean peninsula. Agricultural and Forest Meteorology, 237, 257-269.
◾ Park, S., Im, J., Jang, E., & Rhee, J. (2016). Drought assessment and monitoring through blending of multi-sensor indices using machine learning approaches for different climate regions. Agricultural and Forest Meteorology, 216, 157-169.
저널 논문
◼ SCI(E)
[16] Yeom, J. M., Deo, R. C., Adamowski, J. F., Park, S., & Lee, C. S. (2020). Spatial mapping of short-term solar radiation prediction incorporating geostationary satellite images coupled with deep convolutional LSTM networks for South Korea. Environmental Research Letters.
[15] Park, S., Kang, D., Im, J., & Lee, M. (2020). Recent ENSO influence on East African drought during rainy seasons through the synergistic use of satellite and reanalysis data. ISPRS Journal of Photogrammetry and Remote Sensing, 162, 17-26.
[14] Yeom, J., Park, S., Chae, T., Kim, J., & Lee, C. (2019). Spatial Assessment of Solar Radiation by Machine Learning and Deep Neural Network Models Provided by the COMS MI Geostationary Satellite: A Case Study in South Korea. Sensors, 19(9), 2082.
[13] Kim, M., Park, M., Lee, M., Im, J., & Park, S. (2019). Machine Learning Approaches for Detecting Tropical Cyclone Formation Using Satellite Data. Remote Sensing, 11(10), 1195.
[12] Park, S., Seo, E., Kang, D., Im, J., & Lee, M. (2018). Prediction of Drought on pantad scale using remote sensing data and MJO Index through Random forest over East Asia. Remote Sensing, 10(11), 447.
[11] Park, S., Im, J., Park, S., Yoo, C., Han, H., & Rhee, J. (2018). Classification and Mapping of Paddy Rice by Combining Landsat and SAR Time Series Data. Remote Sensing, 10(3), 447.
[10] Yoo, C., Im, J., Park, S., Lindi, J. (2018). Estimation of daily maximum and minimum air temperatures in urban landscapes using MODIS time series satellite data. ISPRS Journal of Photogrammetry and Remote Sensing, 137, 149-162.
[9] Kim, M., Im, J., Park, H., Park, S., Lee, M. I., & Ahn, M. H. (2017). Detection of Tropical Overshooting Cloud Tops Using Himawari-8 Imagery. Remote Sensing, 9(7), 685.
[8] Park, S., Park, S., Im, J., Rhee, J., Shin, J., & Park, J. D. (2017). Downscaling GLDAS Soil Moisture Data in East Asia through Fusion of Multi-Sensors by Optimizing Modified Regression Trees. Water, 9(5), 332.
[7] Park, S., Im, J., Park, S., & Rhee, J. (2017). Drought monitoring using high resolution soil moisture through multi-sensor satellite data fusion over the Korean peninsula. Agricultural and Forest Meteorology, 237, 257-269.
[6] Ke, Y., Im, J., Park, S., & Gong, H. (2017). Spatiotemporal downscaling approaches for monitoring 8-day 30m actual evapotranspiration. ISPRS Journal of Photogrammetry and Remote Sensing, 126, 79-93.
[5] Park, M. S., Kim, M., Lee, M. I., Im, J., & Park, S. (2016). Detection of tropical cyclone genesis via quantitative satellite ocean surface wind pattern and intensity analyses using decision trees. Remote Sensing of Environment, 183, 205-214.
[4] Im, J., Park, S., Rhee, J., Baik, J., & Choi, M. (2016). Downscaling of AMSR-E soil moisture with MODIS products using machine learning approaches. Environmental Earth Sciences, 75(15), 1120.
[3] Ke, Y., Im, J., Park, S., & Gong, H. (2016). Downscaling of MODIS One kilometer evapotranspiration using Landsat-8 data and machine learning approaches. Remote Sensing, 8(3), 215.
[2] Park, S., Im, J., Jang, E., & Rhee, J. (2016). Drought assessment and monitoring through blending of multi-sensor indices using machine learning approaches for different climate regions. Agricultural and Forest Meteorology, 216, 157-169.
[1] Rhee, J., Park, S., & Lu, Z. (2014). Relationship between land cover patterns and surface temperature in urban areas. GIScience & remote sensing, 51(5), 521-536.

◼ Domestic journal
[1] Yoo, C., Park, S., Kim, Y., & Cho, D. (2019). Analysis of Thermal Environment by Urban Expansion using KOMPSAT and Landsat 8: Sejong City. Korean Journal of Remote Sensing, 35(6-4), 1101-1118.
[2] Yoo, C., Im, J., Park, S., & Cho, D. (2017). Thermal Characteristics of Daegu using Land Cover Data and Satellite-derived Surface Temperature Downscaled Based on Machine Learning. Korean Journal of Remote Sensing, 33(6-2), 1101-1118.

◼ Book Chapters
[1] Rhee, J., Im, J., Park, S. 2015. Chapter 16 Regional drought monitoring based on
Multi‐sensor remote sensing. pp. 410-415. In: Remote Sensing of Water Resources,
Disasters, and Urban Studies (Eds. Prasad S. Thenkabail). Taylor and Francis.
November 2015.

◼ Conference Papers
[3] Rhee, J., Im, J., & Park, S. (2016). DROUGHT FORECASTING BASED ON MACHINE LEARNING OF REMOTE SENSING AND LONG-RANGE FORECAST DATA. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 157-158.
[2] Park, S., & Im, J. (2016). CLASSIFICATION OF CROPLANDS THROUGH FUSION OF OPTICAL AND SAR TIME SERIES DATA. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 703-704.
[1] Park, S., Im, J., Park, S., & Rhee, J. (2015, July). AMSR2 soil moisture downscaling using multisensor products through machine learning approach. In Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International (pp. 1984-1987). IEEE.
◾ Estimation of the Hourly Aerosol Optical Depth From GOCI Geostationary Satellite Data: Deep Neural Network, Machine Learning, and Physical Models, IEEE Transactions on Geoscience and Remote Sensing, 2021박선영
◾ Spatial mapping of short-term solar radiation prediction incorporating geostationary satellite images coupled with deep convolutional LSTM networks for South Korea, ENVIRONMENTAL RESEARCH LETTERS, vol.15 No.9, 2020박선영
◾ Recent ENSO influence on East African drought during rainy seasons through the synergistic use of satellite and reanalysis data, ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, vol.162 pp.17~26, 2020박선영
◾ KOMPSAT과 Landsat 8을 이용한 도시확장에 따른 열환경 분석: 세종특별자치시를 중심으로, 대한원격탐사학회지, vol.35 No.6 pp.1403~1415, 2019박선영
◾ Machine Learning Approaches for Detecting Tropical Cyclone Formation Using Satellite Data, REMOTE SENSING, vol.11 No.10, 2019박선영
◾ Spatial Assessment of Solar Radiation by Machine Learning and Deep Neural Network Models Using Data Provided by the COMS MI Geostationary Satellite: A Case Study in South Korea, SENSORS, vol.19 No.9, 2019박선영
◾ Prediction of Drought on Pentad Scale Using Remote Sensing Data and MJO Index through Random Forest over East Asia, REMOTE SENSING, vol.10 No.11, 2018박선영
◾ Classification and Mapping of Paddy Rice by Combining Landsat and SAR Time Series Data, REMOTE SENSING, vol.10 No.3, 2018박선영
◾ Estimation of daily maximum and minimum air temperatures in urban landscapes using MODIS time series satellite data, ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, vol.137 pp.149~162, 2018박선영
◾ 기계학습 기반 상세화를 통한 위성 지표면온도와 환경부 토지피복도를 이용한 열환경 분석: 대구광역시를 중심으로, 대한원격탐사학회지, vol.33 No.6 pp.1101~1118, 2017박선영
◾ Detection of Tropical Overshooting Cloud Tops Using Himawari-8 Imagery, REMOTE SENSING, vol.9 No.7, 2017박선영
◾ Downscaling GLDAS Soil Moisture Data in East Asia through Fusion of Multi-Sensors by Optimizing Modified Regression Trees, WATER, vol.9 No.5, 2017박선영
◾ Drought monitoring using high resolution soil moisture through multi-sensor satellite data fusion over the Korean peninsula, AGRICULTURAL AND FOREST METEOROLOGY, vol.237 pp.257~269, 2017박선영
◾ Spatiotemporal downscaling approaches for monitoring 8-day 30 m actual evapotranspiration, ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, vol.126 pp.79~93, 2017박선영
◾ Detection of tropical cyclone genesis via quantitative satellite ocean surface wind pattern and intensity analyses using decision trees, REMOTE SENSING OF ENVIRONMENT, vol.183 pp.205~214, 2016박선영
◾ Downscaling of AMSR-E soil moisture with MODIS products using machine learning approaches, ENVIRONMENTAL EARTH SCIENCES, vol.75 No.15, 2016박선영
◾ Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches, REMOTE SENSING, vol.8 No.3, 2016박선영
◾ Drought assessment and monitoring through blending of multi-sensor indices using machine learning approaches for different climate regions, AGRICULTURAL AND FOREST METEOROLOGY, vol.216 pp.157~169, 2016박선영
◾ Relationship between land cover patterns and surface temperature in urban areas, GISCIENCE & REMOTE SENSING, vol.51 pp.521~536, 2014박선영
학술대회
◼ 국제학회
[13] Park, S., Kang, D., Yoo, C., Im, J., & Lee, m., East African Drought Monitoring During Rainy seasons, ACRS, Daejeon, Korea, Oct., 2019 (Poster)
[12] Park, S., Seo, E., Kang, D., Im, J., & Lee, m., Prediction of Drought on pantad scale using remote sensing data and MJO Index through Random forest over East Asia, AOGS, Hawaii, USA, Jun, 2018 (Oral)
[11] Park, S., Kang, D., & Im, J., Climate variability and drought over East Africa on time scale of decades, SPIE Remote Sensing, Warsaw, Poland, Sep, 2017 (Oral)
[10] Park, S., Park, S., & Im, J., Downscaling soil moisture over East Asia through fusion of multi sensors by optimizing modified regression trees, European Geosciences Union (EGU) General Assembly 2017, Vienna, Austria, May, 2017 (Oral)
[9] Park, S., & Im, J., Classification of cropland (paddy rice) through fusion of optical and SAR time series data, International Society for Photogrammetry and Remote Sensing (ISPRS), Prague, Czech Republic, Jul., 2016 (Oral)
[8] Park, S., Im, J., & Ke, Y., Mapping 8-day evapotranspiration at 30m spatial resolution by fusion of MODIS and Landsat data and machine learning approach, International Symposium on Remote Sensing (ISRS), Jeju, South Korea, Apr., 2016 (Oral)
[7] Park, S., Im, J., Park, S., & Rhee, J., Drought monitoring using downscaled soil moisture through machine learning approaches over North and South Korea, American Geosciences Union (AGU) Fall Meeting 2015, San Francisco, USA, Dec, 2015 (Oral)
[6] Park, S., Im, J., Baik, J., Choi, M., & Rhee, J., Machine learning approaches for down scaling AMSR-E soil moisture over south Korea, IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2015, Milan, Italy, Jul., 2015 (Poster)
[5] Park, S., Im, J., Park, S., & Rhee, J., AMSR2 Soil moisture downscaling using multisensor products through machine learning approach, IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2015, Milan, Italy, Jul., 2015 (Oral)
[4] Park, S., Im, J., Yoon, H., Jang, E., & Rhee, J., Machine Learning Approaches to Drought Monitoring Using Multi-sensor Indices for Arid and Humid Regions, International Conference on Earth Observation and Social Impact (ICEO&SI) 2014, Miaoli, Taiwan, Jun, 2014 (Poster)
[3] Rhee, J., Im, J., & Park, S., Regional Drought Monitoring Based on Multi-Sensor Remote Sensing, European Geosciences Union (EGU) General Assembly 2014, Vienna, Austria, May, 2014 (Poster)
[2] Park, S., Im, J., Yoon, H., Jang, E., & Rhee, J., Machine Learning Approaches to Drought Monitoring and Assessment through Blending of Multi-sensor Indices for Different Climate Regions, European Geosciences Union (EGU) General Assembly 2014, Vienna, Austria, May, 2014 (Oral)
[1] Park, S., Yoon, H., Jang, E., & Im, J., Estimation of Evapotranspiration in Korea Using MODIS and LANDSAT 8 Imagery with METRIC and SEBAL, International Symposium on Remote Sensing (ISRS), Busan, South Korea, Apr., 2014 (Oral)
◾ 박선영, 염종민, 김은애, 배출량 예측 모니터링 시스템(PEMS) 구축을 위한 머신러닝 기반의 사업장 내 AOD 추정, 지오에이아이데이터학회 추계학술대회, 부산 파라다이스 호텔, 2021박선영
◾ 박선영, 임정호, 기후지수와 위성기반 가뭄지수를 이용한 머신러닝 기반의 단기가뭄 예측, 2021년 지오에이아이데이터학회 추계학술대회, 부산 파라다이스 호텔, 2021박선영
◾ 김보람, 김예지, 박선영, 다중위성 산불 탐지 및 분석: 정지궤도 산불 탐지 및 지역 추출, 항공우주학회 추계학술대회 논문집, 제주 라마다 호텔, 2021박선영
◾ 박선영, 염종민, 강대현, 배출량 예측 모니터링 시스템 구축을 위한 다양한 머신러닝 기법 기반의 대기 AOD 추정, 2021 공동추계학술대회, 제주대학교 아라캠퍼스, 2021박선영
◾ 박선영, 김예지, 김보람, Forest fire detection using multi-satellite remote sensing, BIEN2021, 대전 ICC 및 온라인 하이브리드, 2021박선영
◾ 김예지, 박선영, 이정호, 채태병, 다목적실용위성 3호와 3A호 영상의 산불피해 분석을 위한 지수지도 분석, 한국항공우주학회 2020 추계학술대회 논문집, 제주도 라마다호텔, 2020박선영
◾ 박선영, 유철희, 김예지, 조동진, KOMPSAT과 Landsat 8 영상을 이용한 도시확장에 따른 열 환경 분석, 한국지리정보학회 추계학술대회집, 제주대학교 아라컨벤션, 2020박선영
◾ 박선영, 머신러닝을 활용한 위성영상 활용: 재난재해 분석, 대한원격탐사학회 2020추계학술대회집, 온라인 발표, 2020박선영
저역서
Chapter 16 Regional drought monitoring based on Multi‐sensor remote sensing. pp. 410-415. In: Remote Sensing of Water Resources, Disasters, and Urban Studies (Eds. Prasad S. Thenkabail). Taylor and Francis. November 2015.
연구프로젝트
◾ 위성영상 객체판독 AI 데이터 구축, 2020
◾ 위성정보활용, 한국항공우주연구원, 2018 ~ 2020
◾ 인공지능 기반 우리나라 위성 자료 융합 활용 기술 개발 및 동아시아 환경 모니터링, 한국연구재단, 2017 ~ 2018
◾ 다중 위성자료 융합 모델링을 통한 가뭄 모니터링 시스템 개발 및 활용, 한국연구재단, 2013 ~ 2016
기타(학회활동 등)
[수상]
◾ Student Competition Award, APNN&MAPWiST (Aug. 2014)
◾ Excellent Poster Award, International Conference on Earth Observation and Social Impact (ICEO&SI) (Jun. 2014)
◾ Student Competition Award, KAGIS (Oct. 2013)
◾ Excellent Oral Presentation Award, Korean Association of Geographic Information Studies (KAGIS) (May. 2013)
담당자 : 경영학과(GTM전공)
전화번호 : 02-970-7284
공유하기 :   icon icon icon    
출력하기
copyright(c) SEOUL NATIONAL UNIVERSITY OF SCIENCE AND TECHNOLOGY. All rights resesrved
대학/대학원
공과대학공과대학기계시스템디자인공학과기계·자동차공학과기계공학 프로그램자동차공학 프로그램안전공학과신소재공학과건설시스템공학과건축학부-건축공학전공건축학부-건축학전공건축기계설비공학과정보통신대학정보통신대학전기정보공학과전자IT미디어공학과전자공학 프로그램IT미디어공학프로그램컴퓨터공학과에너지바이오대학에너지바이오대학화공생명공학과환경공학과식품공학과정밀화학과스포츠과학과안경광학과조형대학조형대학디자인학과산업디자인전공시각디자인전공도예학과금속공예디자인학과조형예술학과인문사회대학인문사회대학행정학과영어영문학과문예창작학과기초교육학부어학교육기술경영융합대학기술경영융합대학산업공학과(산업정보시스템전공)산업공학과(ITM전공)MSDE학과경영학과(경영학전공)경영학과(글로벌테크노경영전공)데이터사이언스학과미래융합대학미래융합대학융합공학부(융합기계공학전공)융합공학부(건설환경융합전공)융합사회학부(헬스피트니스전공)융합사회학부(문화예술전공)융합사회학부(영어전공)융합사회학부(벤처경영전공)창의융합대학창의융합대학인공지능응용학과지능형반도체공학과미래에너지융합학과대학원일반대학원산업대학원주택도시대학원철도전문대학원IT 정책전문대학원나노IT디자인융합대학원융합과학대학원