Yoojin Kang

发表

Estimating ground-level particulate matter concentrations using satellite-based data: a review

Jungho Im, Cheolhee Yoo, Lindi J. Quackenbush, 2020 .

Developing a New Hourly Forest Fire Risk Index Based on Catboost in South Korea

J. Im, C. Kwon, E. Jang, 2020, Applied Sciences.

Estimation of surface-level NO2 and O3 concentrations using TROPOMI data and machine learning over East Asia.

J. Im, Hyun-Jung Choi, Chang-Keun Song, 2021, Environmental pollution.

Detection and Monitoring of Forest Fires Using Himawari-8 Geostationary Satellite Data in South Korea

Jungho Im, Jongmin Yoon, Dong-Won Lee, 2019, Remote. Sens..

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

J. Im, C. Kwon, E. Jang, 2022, GIScience & Remote Sensing.

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

Seonyoung Park, Ju-Hun Im, Yoojin Kang, 2023, Environmental pollution.

Wildfire Severity Mapping Using Sentinel Satellite Data Based on Machine Learning Approaches

J. Im, Yoojin Kang, Sungyong Kim, 2020 .

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

Yoojin Kang, Taejun Sung, Jungho Im, 2023, Remote Sensing of Environment.

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

Yoojin Kang, Jungho Im, 2024, International Journal of Applied Earth Observation and Geoinformation.

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

Yoojin Kang, Taejun Sung, Jungho Im, 2024, IEEE Transactions on Geoscience and Remote Sensing.