Skip to main content

Woo‐Kyun Lee

Korea University · 環境科学

研究室紹介

Professor Woo-Kyun Lee's research lab specializes in environmental remote sensing, with a focus on applying advanced geospatial technologies—such as LiDAR, hyperspectral imaging, and GIS—to address pressing ecological and environmental challenges. The lab investigates forest ecology, land use and land cover change, air quality dynamics, and forest fire risk, often integrating socio-environmental factors to improve predictive modeling and sustainability planning. Their work spans from individual tree-level analysis in coniferous and deciduous forests to global-scale assessments of PM2.5 pollution and local agroforestry practices in vulnerable regions.

remote sensingforest ecologyland use changeair qualityhyperspectral analysis

Research Overview

Papers
501
Total Citations
5,572
Papers (5y)
95
Primary Field
環境科学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
95total
2022
2023
2024
2025
2026
Citations per year (5y)
389total
20222023202420252026

Selected Papers

15
1
Article|252 citations·2007
Detection of individual trees and estimation of tree height using LiDAR data
Doo-Ahn Kwak, Woo‐Kyun Lee, Jun‐Hak Lee, Greg S. Biging, Peng Gong
SJR Q2Journal of Forest Research

For estimation of tree parameters at the single-tree level using light detection and ranging (LiDAR), detection and delineation of individual trees is an important starting point. This paper presents an approach for delineating individual trees and estimating tree heights using LiDAR in coniferous (Pinus koraiensis, Larix leptolepis) and deciduous (Quercus spp.) forests in South Korea. To detect tree tops, the extended maxima transformation of morphological image-analysis methods was applied to

Environmental EngineeringEnvironmental Science
2
Article|246 citations·2020
Understanding global PM2.5 concentrations and their drivers in recent decades (1998–2016)
Chul-Hee Lim, Jieun Ryu, Yuyoung Choi, Seong Woo Jeon, Woo‐Kyun Lee
SJR Q1Environment InternationalOA

The threat of fine particulate matter (PM2.5) is increasing globally. Tackling this issue requires an accurate understanding of its trends and drivers. In this study, global risk regions of PM2.5 concentrations during 1998-2016 were spatiotemporally derived. Time series analysis was conducted in the spatial relationship between PM2.5 and three socio-environmental drivers: population, urban ratio, and vegetation greenness that can cause changes in the concentration of PM2.5. "High Risk" areas wer

Health, Toxicology and MutagenesisEnvironmental Science
3
Article|204 citations·2020
Land Use and Land Cover Change Detection and Prediction in the Kathmandu District of Nepal Using Remote Sensing and GIS
Sonam Wangyel Wang, Belay Manjur Gebru, Munkhnasan Lamchin, Rijan Bhakta Kayastha, Woo‐Kyun Lee
SJR Q1SustainabilityOA

Understanding land use and land cover changes has become a necessity in managing and monitoring natural resources and development especially urban planning. Remote sensing and geographical information systems are proven tools for assessing land use and land cover changes that help planners to advance sustainability. Our study used remote sensing and geographical information system to detect and predict land use and land cover changes in one of the world’s most vulnerable and rapidly growing city

Global and Planetary ChangeEnvironmental Science
4
Article|185 citations·2015
Assessment of land cover change and desertification using remote sensing technology in a local region of Mongolia
Munkhnasan Lamchin, Jong-Yeol Lee, Woo‐Kyun Lee, Eun Jung Lee, Moonil Kim, Chul-Hee Lim, Hyun-Ah Choi, So Ra Kim
SJR Q1Advances in Space Research
Management, Monitoring, Policy and LawEnvironmental Science
5
Article|178 citations·2018
Long-term trend and correlation between vegetation greenness and climate variables in Asia based on satellite data
Munkhnasan Lamchin, Woo‐Kyun Lee, Seong Woo Jeon, Sonam Wangyel Wang, Chul Hee Lim, Cholho Song, Minjun Sung
SJR Q1The Science of The Total Environment
EcologyEnvironmental Science
6
Article|142 citations·2019
Multi-Temporal Analysis of Forest Fire Probability Using Socio-Economic and Environmental Variables
Sea Jin Kim, Chul-Hee Lim, Gang Sun Kim, Jongyeol Lee, Tobias Geiger, Omid Rahmati, Yowhan Son, Woo‐Kyun Lee
SJR Q1Remote SensingOA

As most of the forest fires in South Korea are related to human activity, socio-economic factors are critical in estimating their probability. To estimate and analyze how human activity is influencing forest fire probability, this study considered not only environmental factors such as precipitation, elevation, topographic wetness index, and forest type, but also socio-economic factors such as population density and distance from urban area. The machine learning Maximum Entropy (Maxent) and Rand

Global and Planetary ChangeEnvironmental Science
7
Article|96 citations·2018
Hyperspectral Analysis of Pine Wilt Disease to Determine an Optimal Detection Index
So Ra Kim, Woo‐Kyun Lee, Chul-Hee Lim, Moonil Kim, M. Kafatos, Seung-Ho Lee, Sung-Soon Lee
SJR Q1ForestsOA

Bursaphelenchus xylophilus, the pine wood nematode (PWN) which causes pine wilt disease, is currently a serious problem in East Asia, including in Japan, Korea, and China. This paper investigates the hyperspectral analysis of pine wilt disease to determine the optimal detection indices for measuring changes in the spectral reflectance characteristics and leaf reflectance in the Pinus thunbergii (black pine) forest on Geoje Island, South Korea. In the present study, we collected the leaf reflecta

EcologyEnvironmental Science
8
Article|93 citations·2019
Socio-Ecological Niche and Factors Affecting Agroforestry Practice Adoption in Different Agroecologies of Southern Tigray, Ethiopia
Belay Manjur Gebru, Sonam Wangyel Wang, Sea Jin Kim, Woo‐Kyun Lee
SJR Q1SustainabilityOA

This study was carried out in the southern zone of Tigray to identify and characterize traditional common agroforestry practices and understand the existing knowledge of farm households on the management of trees under different agroforestry in different agroecologies. We conducted reconnaissance and diagnostic surveys by systematically and randomly selecting 147 farming households in the three agroecologies of the study area. A logit regression model was employed to determine how these factors

Plant ScienceAgricultural and Biological Sciences
9
Article|82 citations·2011
Estimating Crown Variables of Individual Trees Using Airborne and Terrestrial Laser Scanners
Sung-Eun Jung, Doo-Ahn Kwak, Taejin Park, Woo‐Kyun Lee, Seongjin Yoo
SJR Q1Remote SensingOA

In this study, individual tree height (TH), crown base height (CBH), crown area (CA) and crown volume (CV), which were considered as essential parameters for individual stem volume and biomass estimation, were estimated by both an airborne laser scanner (ALS) and a terrestrial laser scanner (TLS). These ALS- and TLS-derived tree parameters were compared because TLS has been introduced as an instrument to measure objects more precisely. ALS-estimated TH was extracted from the highest value within

Environmental EngineeringEnvironmental Science
10
Article|82 citations·2002
Modeling stem profiles for Pinus densiflora in Korea
Woo‐Kyun Lee, Jeong-Ho Seo, Young-Mo Son, Kyeong-Hak Lee, Klaus von Gadow
SJR Q1Forest Ecology and Management
Nature and Landscape ConservationEnvironmental Science
11
Article|62 citations·2011
Forest Cover Classification by Optimal Segmentation of High Resolution Satellite Imagery
So Ra Kim, Woo‐Kyun Lee, Doo-Ahn Kwak, Greg S. Biging, Peng Gong, Jun‐Hak Lee, Hyun-Kook Cho
SJR Q1SensorsOA

This study investigated whether high-resolution satellite imagery is suitable for preparing a detailed digital forest cover map that discriminates forest cover at the tree species level. First, we tried to find an optimal process for segmenting the high-resolution images using a region-growing method with the scale, color and shape factors in Definiens(®) Professional 5.0. The image was classified by a traditional, pixel-based, maximum likelihood classification approach using the spectral inform

Environmental EngineeringEnvironmental Science
12
Article|60 citations·2004
DBH growth model for Pinus densiflora and Quercus variabilis mixed forests in central Korea
Woo Kyun Lee, Klaus von Gadow, D. J. Chung, Jong-Lak Lee, Man Yong Shin
SJR Q1Ecological Modelling
Nature and Landscape ConservationEnvironmental Science
13
Article|58 citations·2017
Effect of National-Scale Afforestation on Forest Water Supply and Soil Loss in South Korea, 1971–2010
Gang Sun Kim, Chul-Hee Lim, Sea Jin Kim, Jongyeol Lee, Yowhan Son, Woo‐Kyun Lee
SJR Q1SustainabilityOA

Afforestation of forests in South Korea may provide an example of the benefit of afforestation on precipitation storage and erosion control. In this study, we presented the effects of afforestation on water supply and soil loss prevention. A spatio-temporal simulation of forest water yield and soil loss was performed from 1971–2010 using InVEST water yield and SWAT models. A forest stock change map was produced by combining land cover data and National Forest Inventory data. The forest water yie

Water Science and TechnologyEnvironmental Science
14
Article|58 citations·2010
Estimating stem volume and biomass of Pinus koraiensis using LiDAR data
Doo-Ahn Kwak, Woo‐Kyun Lee, Hyun-Kook Cho, Seung-Ho Lee, Yowhan Son, M. Kafatos, So Ra Kim
SJR Q2Journal of Plant Research
Environmental EngineeringEnvironmental Science
15
Article|56 citations·2020
Understanding global spatio-temporal trends and the relationship between vegetation greenness and climate factors by land cover during 1982–2014
Munkhnasan Lamchin, Sonam Wangyel Wang, Chul-Hee Lim, Altansukh Ochir, Pavel Ukrainskiy, Belay Manjur Gebru, Yuyoung Choi, Seong Woo Jeon, Woo‐Kyun Lee
SJR Q1Global Ecology and ConservationOA

Analysis of the correlation between vegetation greenness and climate variable trends is important in the study of vegetation greenness. Our study used Normalized Difference Vegetation Index-3rd generation data from the Advanced Very High-Resolution Radiometer - Global Inventory Modeling and Mapping Studies (AVHRR-GIMMS NDVI3g), land cover data from the Climate Change Initiative (CCI-LC), and climate data from the Climatic Research Unit global time series (CRU TS) of climate variables (temperatur

EcologyEnvironmental Science

Research Areas

Global and Planetary ChangeAerospace EngineeringPlant ScienceEnvironmental EngineeringNature and Landscape ConservationEcology

Woo‐Kyun Leeの研究をNubintでさらに深く

この研究室の論文をアプリで開き、AIと共に読み、要約し、引用しましょう。