이우균 교수
Woo‐Kyun Lee
고려대학교 환경생태공학부 · 환경과학
연구실 소개
이우균 교수의 연구실은 원격 감지, 지리정보시스템(GIS), 그리고 머신러닝 기반 기술을 활용해 산림 생태계, 도시 환경 변화, 대기 오염 등에 대한 공간적 분석을 수행하고 있습니다. 주요 연구 방향은 산림 자원 관리와 기후 변화 대응을 위한 고해상도 LiDAR 및 히퍼스펙트럼 데이터 분석, 도시화와 자연 자원 감소의 상호작용, 그리고 대기질 오염의 공간적 추세와 원인 규명에 초점이 맞춰져 있습니다. 특히 한국과 아시아 지역의 산림 질병, 산불 위험, 도시 성장에 기여하는 사회환경적 요인을 통합적으로 분석하는 데 기여하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15For 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
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
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
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
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
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
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
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
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
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
대표 연구 분야
이우균 교수의 연구를 Nubint에서 더 깊이 살펴보세요
이 연구실의 논문을 앱에서 열어 AI와 함께 읽고, 핵심을 요약하고, 내 글에 인용하세요.