Jun Hak Lee

Instructor
Courtesy Research Associate
Landscape Architecture
Research Interests:
Spatial data analysis, Remote sensing, LiDAR, Distributed environmental sensors, Environmental data visualization
Phone: 541-346-2687
Office: 232 Pacific Hall
Website:
BS, 1999, Korea University; MS, 2001, Korea University; PhD in Environmental Science, Policy, and Management, 2010, University of California, Berkeley
 
Junhak Lee teaches Environmental Data Visualization, 3D Mapping with LiDAR, Sensing the Environment (introduction to distributed environmental sensors). He is interested in measuring landscape features using GIS and remote sensing and modeling carbon and water cycle using spatially explicit data. His research interests include the use of spatially explicit data to model carbon and water cycling in natural and built environments and the use of remote sensing technologies in ecological assessments and measurements of landscape performance.
 
Research Interests
Carbon, energy, and water cycles modeling
  • Estimating biomass and carbon sequestration by urban and natural ecosystems under climate change
  • The impact of urban vegetation on water cycles for sustainability
  • Evapotranspiration modeling using FLUXNET and remote sensing to understand global water cycles
Remote sensing for ecological assessments
  • Urban and forest ecosystem modeling by integrating aerial imagery and LiDAR
  • Integrating multi-source remotely sensed data for evapotranspiration modeling 
  • Extracting individual tree level forest eco-physical information from airborne LiDAR
  • Object-oriented urban and natural features extraction by using high spatial resolution aerial imagery and airborne LiDAR
Geographic Information Science & Big Data Analysis
  • Advanced spatial modeling with geographic effect; Impact of climate change on urban infrastructure (Vulnerability assessment of urban transportation infrastructure due to climate change)
  • Environmental indicator & public participatory GIS
  • Urban-scale wireless sensor network for environmental monitoring and modeling
 
Publications
 
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.