Yoojin Kang

Assistant Professor

Kookmin University

South Korea

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Yoojin Kang is an Assistant Professor at Kookmin University in South Korea. Her research primarily focuses on satellite-based environmental monitoring, including aerosol optical depth estimation, wildfire detection, and air quality analysis using machine learning techniques. Recent publications highlight advancements in remote sensing applications for air quality and fire risk assessment, underlining her expertise in geostationary satellite data analysis.

Articles (10)

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2025

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2025

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2024

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2024

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2023

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2023

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2023

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2022

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2022

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2022

Collaborators (3)

Jungho Im

Associate Professor

Korea Advanced Institute of Science and Technology

SOUTH KOREA

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Minki Choo

Institute of Science and Technology

SOUTH KOREA

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Taejun Sung

Institute of Science and Technology

SOUTH KOREA

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Yoojin Kang

Research Interests

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Articles (10)

Enhanced continuous aerosol optical depth (AOD) estimation using geostationary satellite data: focusing on nighttime AOD over East Asia

Bridging temporal gaps: AI-based temporal downscaling of biweekly NH3 to daily scale with spatial transferability

Enhancing Satellite-Based Wildfire Monitoring: Advanced Contextual Model Using Environmental and Structural Information

Mitigating underestimation of fire emissions from the Advanced Himawari Imager: A machine learning and multi-satellite ensemble approach

Retrieval of hourly PM2.5 using top-of-atmosphere reflectance from geostationary ocean color imagers I and II

Trend Analysis of Vegetation Changes of Korean Fir (Abies koreana Wilson) in Hallasan and Jirisan Using MODIS Imagery,MODIS 시계열 위성영상을 이용한 한라산과 지리산 구상나무 식생 변동 추세 분석

Toward an adaptable deep-learning model for satellite-based wildfire monitoring with consideration of environmental conditions

A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency

Development of Mid-range Forecast Models of Forest Fire Risk Using Machine Learning

Improved retrievals of aerosol optical depth and fine mode fraction from GOCI geostationary satellite data using machine learning over East Asia

Collaborators (3)

Jungho Im

Minki Choo

Taejun Sung

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