학력
2018. School of Urban and Environmental Engineering UNIST, Korea (PhD)
2013. School of Urban and Environmental Engineering UNIST, Korea (BS)
주요 경력
2020 - present: Assistant Professor, SeoulTech (Seoul National University of Science and Technology), Seoul, Korea
2018 - 2020: Senior Researcher, Korea Aerospace Research Institute (KARI),Korea
2012: Intern (IT department), SIMENS, Seoul, Korea
2011: Visiting researcher, NASA GSFC, GMAO, Greenbelt, Maryland, USA
연구 분야
Remote sensing of Environment
- Disaster monitoring (climate variability and drought, developing drought indices, heat wave, forest fire)
- Environmental monitoring (Air quality monitoring, Others Land related processes such as evapotranspiration, agricultural process)
Machine learning approaches
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.
◾ Environmental Monitoring and Forecasting Using Advanced Remote Sensing Approaches, Korean Journal of Remote Sensing, vol.39 No.5-3 pp.885~890, 2023박선영 학과장
◾ Satellite-Based Cabbage and Radish Yield Prediction Using Deep Learning in Kangwon-do, Korean Journal of Remote Sensing, vol.39 No.3-5 pp.1031~1042, 2023박선영 학과장
◾ Direct aerosol optical depth retrievals using MODIS reflectance data and machine learning over East Asia, Atmospheric Environment, 2023박선영 학과장
◾ Change detection over the Aral Sea using relative radiometric normalization based on deep learning, REMOTE SENSING LETTERS, 2023박선영 학과장
◾ Synergistic use of multi-satellite remote sensing to detect forest fires: A case study in South Korea, REMOTE SENSING LETTERS, vol.14 No.5 pp.491~502, 2023박선영 학과장
◾ Retrieval of hourly PM2.5 using top-of-atmosphere reflectance from geostationary ocean color imagers I and II, ENVIRONMENTAL POLLUTION, vol.323, 2023박선영 학과장
◾ Proposal for a new customization process for a data-based water quality index using a random forest approach, ENVIRONMENTAL POLLUTION, vol.323, 2023박선영 학과장
◾ Evaluating the potential of burn severity mapping and transferability of Copernicus EMS data using Sentinel-2 imagery and machine learning approaches, GISCIENCE & REMOTE SENSING, vol.60 No.1, 2023박선영 학과장
◾ Performance of Drought Indices in Assessing Rice Yield in North Korea and South Korea under the Different Agricultural Systems, REMOTE SENSING, vol.14 No.23, 2022박선영 학과장
◾ Machine Learning-Based Forest Burned Area Detection with Various Input Variables: A Case Study of South Korea, APPLIED SCIENCES-BASEL, vol.12 No.19, 2022박선영 학과장
◾ Forest Burned Area Detection Using Landsat 8/9 and Sentinel-2 A/B Imagery with Various Indices: A Case Study of Uljin, Korean Journal of Remote Sensing, vol.38 No.5-2 pp.765~779, 2022박선영 학과장
◾ Identifying the Impact of Regional Meteorological Parameters on US Crop Yield at Various Spatial Scales Using Remote Sensing Data, REMOTE SENSING, vol.14 No.15, 2022박선영 학과장
◾ 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, vol.60, 2021박선영 학과장
◾ 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 학과장
◾ 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 학과장
◾ KOMPSAT과 Landsat 8을 이용한 도시확장에 따른 열환경 분석: 세종특별자치시를 중심으로, 대한원격탐사학회지, vol.35 No.6 pp.1403~1415, 2019박선영 학과장
◾ 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 학과장
◾ Machine Learning Approaches for Detecting Tropical Cyclone Formation Using Satellite Data, REMOTE SENSING, vol.11 No.10, 2019박선영 학과장
◾ 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 학과장
◾ 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 학과장
◾ Classification and Mapping of Paddy Rice by Combining Landsat and SAR Time Series Data, REMOTE SENSING, vol.10 No.3, 2018박선영 학과장
◾ 기계학습 기반 상세화를 통한 위성 지표면온도와 환경부 토지피복도를 이용한 열환경 분석: 대구광역시를 중심으로, 대한원격탐사학회지, vol.33 No.6 pp.1101~1118, 2017박선영 학과장
◾ Detection of Tropical Overshooting Cloud Tops Using Himawari-8 Imagery, REMOTE SENSING, vol.9 No.7, 2017박선영 학과장
◾ 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 학과장
◾ Downscaling GLDAS Soil Moisture Data in East Asia through Fusion of Multi-Sensors by Optimizing Modified Regression Trees, WATER, vol.9 No.5, 2017박선영 학과장
◾ Spatiotemporal downscaling approaches for monitoring 8-day 30 m actual evapotranspiration, ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, vol.126 pp.79~93, 2017박선영 학과장
◾ 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 학과장
◾ Downscaling of AMSR-E soil moisture with MODIS products using machine learning approaches, ENVIRONMENTAL EARTH SCIENCES, vol.75 No.15, 2016박선영 학과장
◾ Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches, REMOTE SENSING, vol.8 No.3, 2016박선영 학과장
◾ 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 학과장
◾ Relationship between land cover patterns and surface temperature in urban areas, GISCIENCE & REMOTE SENSING, vol.51 pp.521~536, 2014박선영 학과장
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, Sentinel-2 영상을 이용한 동계작물 재배지역 분류, 2023 GEOAI, 그랜드 하얏트 제주, 2023박선영 학과장
◾ 박선영, 임정호, Performance of the Drought Indices in the Different Agricultural Systems, 2023 IAG'i, The University of Electro-Communications (Chofu City, Tokyo), 2023박선영 학과장
◾ 박선영, Performance of the Drought Indices in the Different Agricultural Systems, AOGS 2023, SUNTEC Singapore, 2023박선영 학과장
◾ 이예진, 박헤빈, 박선영, 송낙훈, 이경일, 머신러닝을 활용한 제조 사업장 대기오염 물질 배출량 예측 및 확산 모델링, 2023 전자공학회 춘계학술대회, 롯데호텔 제주, 2023박선영 학과장
◾ 박선영, 이경일, Satellite-based burn severity mapping and evaluating the transferability of Copernicus EMS data using machine learning approaches, EGU23, Austria Center Vienna, 2023박선영 학과장
◾ 박선영, 강유진, 오상호, 이경일, 한유경, 다양한 위성영상을 이용한 머신러닝 기반의 우리나라 산불 피해지역 탐지, 2022년 GEOAI데이터학회 추계학술대회, 그랜드하얏트 제주, 2022박선영 학과장
◾ 박선영, 이경일, 김병철, 박혜빈, 정영민, 송낙훈, 강유진, 김우혁, 원격탐사와 인공지능을 이용한 우리나라 기후환경에 따른 산불 분석, 2022년 대한원격탐사학회 추계학술대회, 부산 벡스코, 2022박선영 학과장
◾ 정영민 이경일, 박선영, Landsat 9 이용한 CNN 기반의 로마 Local Cliamte Zone 매핑, 2022 KAGIS 추계학술대회, 제주대학교 아라캠퍼스, 2022박선영 학과장
◾ 박혜빈, 박선영, 머신러닝을 이용한 위성영상 기반의 우리나라 작물 수확량 예측, 2022 KAGIS 추계학술대회, 제주대학교 아라캠퍼스, 2022박선영 학과장
◾ Seonyoung Park, Yeji Kim, Bo-ram Kim, Youkyung Han, Changhui Lee, Teaheon Kim , DETECTION OF SMALL SCALE FOREST FIRE BASED ON MULTI-SATELLITE REMOTE SENSING USING MACHINE LEARNING APPROACHES, IEEE IGARSS (International Geoscience and Remote Sensing Symposium) 2022, Kuala Lumpur Convention Centre, 2022박선영 학과장
◾ 박선영, 염종민, 김은애, 배출량 예측 모니터링 시스템(PEMS) 구축을 위한 머신러닝 기반의 사업장 내 AOD 추정, 지오에이아이데이터학회 추계학술대회, 부산 파라다이스 호텔, 2021박선영 학과장
◾ 박선영, 임정호, 기후지수와 위성기반 가뭄지수를 이용한 머신러닝 기반의 단기가뭄 예측, 2021년 지오에이아이데이터학회 추계학술대회, 부산 파라다이스 호텔, 2021박선영 학과장
◾ 김보람, 김예지, 박선영, 다중위성 산불 탐지 및 분석: 정지궤도 산불 탐지 및 지역 추출, 항공우주학회 추계학술대회 논문집, 제주 라마다 호텔, 2021박선영 학과장
◾ 박선영, 염종민, 강대현, 배출량 예측 모니터링 시스템 구축을 위한 다양한 머신러닝 기법 기반의 대기 AOD 추정, 2021 공동추계학술대회, 제주대학교 아라캠퍼스, 2021박선영 학과장
◾ 박선영, 김예지, 김보람, Forest fire detection using multi-satellite remote sensing, BIEN2021, 대전 ICC 및 온라인 하이브리드, 2021박선영 학과장
◾ 김예지, 박선영, 이정호, 채태병, 다목적실용위성 3호와 3A호 영상의 산불피해 분석을 위한 지수지도 분석, 한국항공우주학회 2020 추계학술대회 논문집, 제주도 라마다호텔, 2020박선영 학과장
◾ 박선영, 유철희, 김예지, 조동진, KOMPSAT과 Landsat 8 영상을 이용한 도시확장에 따른 열 환경 분석, 한국지리정보학회 추계학술대회집, 제주대학교 아라컨벤션, 2020박선영 학과장
◾ 박선영, 머신러닝을 활용한 위성영상 활용: 재난재해 분석, 대한원격탐사학회 2020추계학술대회집, 온라인 발표, 2020박선영 학과장
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)
Awards
◾ 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)
국방인공지능응용학과
