Sunmin Lee

Spatial prediction of flood susceptibility using random-forest and boosted-tree models in Seoul metropolitan city, Korea

Sunmin Lee · Geomatics Natural Hazards and Risk · 2017 · 376 citations · Full text

Flood-susceptibility Maps, Engineering, Geomorphology +17

Landslide susceptibility mapping using random forest and boosted tree models in Pyeong-Chang, Korea

Jeong-Cheol Kim, Sunmin Lee · Geocarto International · 2017 · 285 citations

Rock Slide, Landslides Susceptibility Maps, Engineering +17

Groundwater Potential Mapping Using Remote Sensing and GIS-Based Machine Learning Techniques

Sunmin Lee, Yunjung Hyun, Saro Lee et al. · Remote Sensing · 2020 · 150 citations · Full text

Hydrogeology, Environmental Monitoring, Engineering +14

Novel hybrid models between bivariate statistics, artificial neural networks and boosting algorithms for flood susceptibility assessment

Romulus Costache, Quoc Bao Pham, Mohammadtaghi Avand et al. · Journal of Environmental Management · 2020 · 124 citations

Flash Flood, Novel Hybrid Models, Engineering +11

Comparison of multi-criteria-analytical hierarchy process and machine learning-boosted tree models for regional flood susceptibility mapping: a case study from Slovakia

Matej Vojtek, Jana Vojteková, Romulus Costache et al. · Geomatics Natural Hazards and Risk · 2021 · 96 citations · Full text

Engineering, Flood Control, High Flood Susceptibility +16