BS, 1999, Korea University; MS, 2001, Korea University; PhD in Environmental Science, Policy, and Management, 2010, University of California, Berkeley
Junhak Lee specializes in the intersection of environmental data science, remote sensing, and ecological modeling. He teaches Environmental Data Visualization, GIS for Landscape Architecture, 3D Mapping with LiDAR, and Sensing the Environment, an introductory course on distributed environmental sensors. His expertise lies in leveraging geospatial data analytics and remote sensing technologies to analyze and measure landscape features and performance.
Dr. Lee’s research focuses on the integration of spatially explicit data to model carbon and water cycles across natural and urban landscapes. He is particularly interested in applying remote sensing technologies to ecological assessments and quantifying landscape performance. His work bridges the gap between cutting-edge environmental data analytics and actionable insights for sustainable ecosystem management.
Research Interests
Dynamic Urban Flood Modeling: Development of physically-based models leveraging high-performance computing (HPC) to analyze urban flood dynamics.
Remote Sensing and Ecosystem Modeling: Integration of aerial imagery and LiDAR for urban and forest ecosystem assessments, including eco-physical 3D data extraction and machine learning applications for feature analysis.
Wildfire Monitoring: Use of high-resolution imagery and LiDAR-derived 3D data for monitoring wildfire fuel and risk assessment.
Geospatial Analysis for Environmental Justice: Advanced spatial modeling of climate change impacts on urban infrastructure, participatory GIS, environmental monitoring networks, and analyses of extreme weather events (wildfires and urban flooding).
Publications
Lee, J.-H., S. Lee, Kim, B. Choi, H., S., Noh, S., Process-based urban inundation mapping via downscaling of coarse-resolution water height and high-resolution terrain data (Work in Progress)
Lee, J.-H., Jung, S., Ko, Y., Fisher. J. B., Lee, S., Noh, S., Exploring Spatial and Social Inequities in Flood Exposure: A Dynamic Inundation Modeling Approach Across Varied Magnitude, Nature sustainability (Work in Progress)
Lee, J.-H., S. Lee, Kim, B. Choi, H., S., Noh, S., Evaluating the effects of spatial resolution on urban pluvial flood modeling, Hydrological Processes; Special Issue: "Pluvial Flooding: maturing process understanding from data scarcity into data abundance" (Revised and re-submitted)
Elderbrock, E., Ponette-González, A. G., Rindy, J. E., Lee, J. -H., Weathers, K. C., & Ko, Y. 2023. Modeling Black Carbon Removal by City Trees: Implications for Urban Forest Planning. Urban Forestry & Urban Greening, 128013.
Naik, N. S., Elzeyadi, I., Minson, C. T., & Lee, J. -H. 2023. Significance of dynamic over static solar screens on thermal perception in perimeter offices under different sky conditions. Building and Environment, 234, 110153.
Ponette-González, A., Chen, D., Elderbrock, E., Rindy, J., Barrett, T., Luce, B., Lee, J.-H., Ko, Y., Weathers, K., 2022, Urban edge trees: urban form and meteorology drive elemental carbon deposition to canopies and soils, Environmental Pollution, 314 (120197)
Naik, N., Elzeyadi, I., Minson, C., Lee, J.-H., Thermal pleasure inside solar screened spaces: an experimental study to explore alliesthesia in architecture, Building Research & Information 49(7), 795-812
Noh, S., Lee, J.-H., Lee, S., Seo, D.J., 2019. Retrospective Dynamic Inundation Mapping of Hurricane Harvey Flooding in the Houston Metropolitan Area Using High-Resolution Modeling and High-Performance Computing. Water. 11(3): 597-614
Noh, S., Lee, J.-H., Lee, S., Seo D.J., Kawaike, K. 2018. Hyper-resolution 1D-2D urban flood modelling using LiDAR data and hybrid parallelization. Environmental Modelling and Software 103:131-145
Lee, J.-H., Biging. G.S., Gong, P., Fisher J.B., 2016, An Individual Tree-Based Automatic Registration of Aerial Images to Airborne LiDAR Data. Photogrammetric Engineering and Remote Sensing 82(9): 699-710.
Lee, J.-H., Ko, Y, McPherson, 2016. The feasibility of remotely sensed data to estimate urban tree dimensions and biomass, Urban Forestry and Urban Greening 16: 208-220.
Ko, Y., Lee, J.-H., McPherson, E.G., Roman, L.A. 2015. Long-term monitoring of Sacramento Shade program trees: tree survival, growth and energy-saving performance. Landscape and Urban Planning 143:183–191.
Ko, Y., Lee, J.-H., McPherson, E.G., Roman, L.A. 2015. Factors affecting long-term mortality for residential shade trees: Evidence from Sacramento, CA, Urban Forestry and Urban Greening 14: 500–507.
Lee, J.-H., Biging. G.S., Radke, J.D., Fisher, J.B. 2013. An improved topographic map from airborne LiDAR: Application in a forested hillside. International Journal of Remote Sensing, 334(20): 7293-7311
Kim, S.R., Lee, W.K., Kwak, D.A., Biging, G.S., Gong P., Lee, J.-H., Cho H.K., 2011. Forest Cover Classification by Optimal Segmentation of High Resolution Satellite Imagery. Sensors, 11(2):1943-1958.
Bigham, J.M., Rice, T.M., Pande, S., Lee, J.-H., Park, S.H., Gutierrez, N., Ragland, D.R., 2009. Geocoding police collision report data from California: a comprehensive approach, International Journal of Health Geographics, 8:72
Kwak, D.A., Lee, W.K., Lee, J.-H., Biging, G.S., Gong, P., 2007. Detection of individual trees and estimation of tree height using LiDARdata. Journal of Forest Research, 12(6):425-434.
