World's Best Scientists 2026 revealed!
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Earth Science
Korea
2026

D-Index & Metrics

Earth Science

D-Index
97
Citations
29079
World Ranking
166
National Ranking
1

Research.com Recognitions

  • 2026 - Research.com Earth Science in Korea Leader Award
  • 2025 - Research.com Earth Science in Korea Leader Award
  • 2022 - Research.com Earth Science in Korea Leader Award

Overview

Saro Lee is affiliated with the Korea Institute of Geoscience and Mineral Resources in South Korea. Their research focuses primarily on environmental science, with a particular emphasis on global and planetary change, management, monitoring, policy, and law, as well as environmental engineering and water science and technology. The body of work covers key themes such as flood risk assessment and management, landslides and related hazards, hydrology and watershed management studies, groundwater and watershed analysis, hydrology and drought analysis, soil erosion and sediment transport, and geochemistry and geologic mapping.

The scientist has published extensively in several academic venues. The most frequent publication venues include:

  • Remote Sensing
  • GEO DATA
  • Geoscience Frontiers
  • Journal of Hydrology
  • Geocarto International

Leading papers authored or co-authored by Saro Lee span topics in natural hazard modeling and hydrology. Recent papers include:

  • "Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran," published in 2020 in Geoscience Frontiers
  • "Spatial prediction of groundwater potential mapping based on convolutional neural network (CNN) and support vector regression (SVR)," published in 2020 in Journal of Hydrology
  • "Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran," published in 2020 in Journal of Hydrology
  • "Urban flood modeling using deep-learning approaches in Seoul, South Korea," published in 2021 in Journal of Hydrology
  • "Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer," published in 2020 in Geoscience Frontiers

Frequent collaborators featured in the research network include:

  • Fatemeh Rezaie
  • Mahdi Panahi
  • Alireza Arabameri
  • Sayed M. Bateni
  • Omid Rahmati

The primary research fields and subfields demonstrate a focus on environmental and atmospheric dynamics, particularly how they relate to water resources and geological hazards. Saro Lee's work integrates advanced computational methods including deep learning, convolutional neural networks, and optimization algorithms to address challenges in landslide susceptibility, flood hazard mapping, and groundwater potential assessment at both national and urban scales.

Best Publications

  • Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models

    Saro Lee;Biswajeet Pradhan

  • Statistical analysis of landslide susceptibility at Yongin, Korea

    Saro Lee;Kyungduck Min

  • Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling

    Biswajeet Pradhan;Saro Lee

  • Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data

    S. Lee

  • Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models

    Biswajeet Pradhan;Saro Lee

  • Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

    Saro Lee;Joo Hyung Ryu;Joong Sun Won;Hyuck Jin Park

  • Probabilistic landslide susceptibility and factor effect analysis

    S Lee;Jasmi Abdul Talib

  • Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models

    Saro Lee;Touch Sambath

  • Regional landslide susceptibility analysis using back-propagation neural network model at Cameron Highland, Malaysia

    Biswajeet Pradhan;Saro Lee

  • GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea

    Hyun-Joo Oh;Yong-Sung Kim;Jong-Kuk Choi;Eungyu Park

  • Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia

    Saro Lee;Biswajeet Pradhan

  • Application of an evidential belief function model in landslide susceptibility mapping

    Omar F. Althuwaynee;Biswajeet Pradhan;Saro Lee

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

    Sunmin Lee;Jeong-Cheol Kim;Hyung-Sup Jung;Moung Jin Lee

  • Application of probabilistic-based frequency ratio model in groundwater potential mapping using remote sensing data and GIS

    Mohamad Abd Manap;Haleh Nampak;Biswajeet Pradhan;Saro Lee

  • Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

    Phuong Thao Thi Ngo;Mahdi Panahi;Khabat Khosravi;Omid Ghorbanzadeh

  • Combining landslide susceptibility maps obtained from frequency ratio, logistic regression, and artificial neural network models using ASTER images and GIS

    Jaewon Choi;Hyun-Joo Oh;Hong-Jin Lee;Changwook Lee

  • Flood susceptibility mapping using integrated bivariate and multivariate statistical models

    Mahyat Shafapour Tehrany;Moung Jin Lee;Biswajeet Pradhan;Mustafa Neamah Jebur

  • Spatial prediction of groundwater potential mapping based on convolutional neural network (CNN) and support vector regression (SVR)

    Mahdi Panahi;Nitheshnirmal Sadhasivam;Hamid Reza Pourghasemi;Fatemeh Rezaie

  • Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment

    Maher Ibrahim Sameen;Biswajeet Pradhan;Biswajeet Pradhan;Saro Lee

  • Landslide susceptibility analysis using GIS and artificial neural network

    Saro Lee;Joo Hyung Ryu;Kyungduck Min;Joong Sun Won

  • Application and verification of fuzzy algebraic operators to landslide susceptibility mapping

    Saro Lee

  • Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea

    Saro Lee;Joo-Hyung Ryu;Ii-Soo Kim

  • Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea

    S. Lee;J. Choi;K. Min

Frequent Co-Authors

Biswajeet Pradhan
Biswajeet Pradhan University of Technology Sydney
Joong-Sun Won
Joong-Sun Won Yonsei University
Dieu Tien Bui
Dieu Tien Bui University of South-Eastern Norway
Himan Shahabi
Himan Shahabi University of Kurdistan
Ataollah Shirzadi
Ataollah Shirzadi University of Kurdistan
Baharin Bin Ahmad
Baharin Bin Ahmad University of Technology Malaysia
Hamid Reza Pourghasemi
Hamid Reza Pourghasemi Shiraz University
Omid Rahmati
Omid Rahmati Agricultural Research Education And Extention Organization
Assefa M. Melesse
Assefa M. Melesse Florida International University
Saskia Keesstra
Saskia Keesstra Wageningen University & Research

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