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Yangwon Lee

6 papers indexed

crossrefWater2026-01-30

A High-Resolution Daily Precipitation Fusion Framework Integrating Radar, Satellite, and NWP Data Using Machine Learning over South Korea

Hyoju Park, Hiroyuki Miyazaki, Menas Kafatos, Seung Hee Kim, Yangwon Lee

Accurate precipitation mapping is essential for effective disaster management; however, individual radar, satellite, and numerical weather prediction products often struggle in the topographically complex terrain of South Korea. This study proposes a high-resolution (~500 m) dail…

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crossrefAtmosphere2025-12-24

Real-Time Production of High-Resolution, Gap-Free, 3-Hourly AOD over South Korea: A Machine Learning Approach Using Model Forecasts, Satellite Products, and Air Quality Data

Seoyeon Kim, Youjeong Youn, Menas Kafatos, Jaejin Kim, Wonsik Choi, Seung Hee Kim, et al.

Aerosol optical depth (AOD) is essential for air quality monitoring and climate research. However, satellite-based retrievals suffer from cloud-related data gaps, and reanalysis products are limited by coarse spatial resolution and substantial production latency. This study devel…

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crossrefApplied Sciences2025-01-22Cited by 17

AI- and Deep Learning-Powered Driver Drowsiness Detection Method Using Facial Analysis

Tahesin Samira Delwar, Mangal Singh, Sayak Mukhopadhyay, Akshay Kumar, Deepak Parashar, Yangwon Lee, et al.

The significant number of road traffic accidents caused by fatigued drivers presents substantial risks to the public’s overall safety. In recent years, there has been a notable convergence of intelligent cameras and artificial intelligence (AI), leading to significant advancement…

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crossrefSensors2024-10-01Cited by 31

The Intersection of Machine Learning and Wireless Sensor Network Security for Cyber-Attack Detection: A Detailed Analysis

Tahesin Samira Delwar, Unal Aras, Sayak Mukhopadhyay, Akshay Kumar, Ujwala Kshirsagar, Yangwon Lee, et al.

This study provides a thorough examination of the important intersection of Wireless Sensor Networks (WSNs) with machine learning (ML) for improving security. WSNs play critical roles in a wide range of applications, but their inherent constraints create unique security challenge…

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crossrefWater2024-09-18Cited by 3

An Automated Machine Learning Approach to the Retrieval of Daily Soil Moisture in South Korea Using Satellite Images, Meteorological Data, and Digital Elevation Model

Nari Kim, Soo-Jin Lee, Eunha Sohn, Mija Kim, Seonkyeong Seong, Seung Hee Kim, et al.

Soil moisture is a critical parameter that significantly impacts the global energy balance, including the hydrologic cycle, land–atmosphere interactions, soil evaporation, and plant growth. Currently, soil moisture is typically measured by installing sensors in the ground or thro…

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crossrefRemote Sensing2023-08-24Cited by 3

Real-Time Retrieval of Daily Soil Moisture Using IMERG and GK2A Satellite Images with NWP and Topographic Data: A Machine Learning Approach for South Korea

Soo-Jin Lee, Eunha Sohn, Mija Kim, Ki-Hong Park, Kyungwon Park, Yangwon Lee

Soil moisture (SM) is an indicator of the moisture status of the land surface, which is useful for monitoring extreme weather events. Representative global SM datasets include the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP), the Global…

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