Giha Lee

2.3k total citations · 1 hit paper
82 papers, 1.6k citations indexed

About

Giha Lee is a scholar working on Water Science and Technology, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Giha Lee has authored 82 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Water Science and Technology, 41 papers in Global and Planetary Change and 24 papers in Environmental Engineering. Recurrent topics in Giha Lee's work include Hydrology and Watershed Management Studies (45 papers), Flood Risk Assessment and Management (33 papers) and Soil erosion and sediment transport (19 papers). Giha Lee is often cited by papers focused on Hydrology and Watershed Management Studies (45 papers), Flood Risk Assessment and Management (33 papers) and Soil erosion and sediment transport (19 papers). Giha Lee collaborates with scholars based in South Korea, Vietnam and Japan. Giha Lee's co-authors include Xuan-Hien Le, Sungho Jung, Hyunuk An, Duc Hai Nguyen, Kwansue Jung, Minseok Kim, Massimiliano Alvioli, Giang V. Nguyen, Yeonsu Kim and Sophal Try and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and Journal of Hydrology.

In The Last Decade

Giha Lee

74 papers receiving 1.6k citations

Hit Papers

Application of Long Short-Term Memory (LSTM) Neural Netwo... 2019 2026 2021 2023 2019 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Giha Lee South Korea 17 748 637 594 376 337 82 1.6k
Changhyun Jun South Korea 23 761 1.0× 507 0.8× 562 0.9× 314 0.8× 150 0.4× 143 1.8k
Mehdi Vafakhah Iran 24 1.0k 1.4× 899 1.4× 864 1.5× 241 0.6× 314 0.9× 112 1.9k
Vahid Moosavi Iran 20 690 0.9× 477 0.7× 799 1.3× 268 0.7× 242 0.7× 61 1.5k
Viet‐Ha Nhu Vietnam 25 968 1.3× 348 0.5× 436 0.7× 292 0.8× 872 2.6× 35 2.1k
Abhirup Dikshit Australia 26 1.3k 1.7× 301 0.5× 376 0.6× 439 1.2× 878 2.6× 38 2.0k
Ataollah Shirzadi Iran 22 1.5k 1.9× 404 0.6× 520 0.9× 386 1.0× 1.1k 3.3× 31 2.3k
Xiaoshen Xie China 10 1.2k 1.6× 369 0.6× 420 0.7× 331 0.9× 1.1k 3.4× 19 2.0k
Pham Viet Hoa Vietnam 16 814 1.1× 383 0.6× 403 0.7× 220 0.6× 281 0.8× 29 1.3k
Aiding Kornejady Iran 15 1.4k 1.9× 491 0.8× 508 0.9× 357 0.9× 1.0k 3.0× 19 2.1k
Somayeh Panahi Iran 11 816 1.1× 405 0.6× 356 0.6× 165 0.4× 378 1.1× 16 1.2k

Countries citing papers authored by Giha Lee

Since Specialization
Citations

This map shows the geographic impact of Giha Lee's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Giha Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giha Lee more than expected).

Fields of papers citing papers by Giha Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Giha Lee. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Giha Lee. The network helps show where Giha Lee may publish in the future.

Co-authorship network of co-authors of Giha Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Giha Lee. A scholar is included among the top collaborators of Giha Lee based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Giha Lee. Giha Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Le, Xuan-Hien, Đoàn Văn Bình, & Giha Lee. (2025). Performance and uncertainty analysis in deep learning frameworks for streamflow forecasting via Monte Carlo dropout technique. Journal of Hydrology Regional Studies. 61. 102668–102668.
2.
Nguyen, Giang V., et al.. (2025). Rapid Urban Flood Detection Using PlanetScope Imagery and Thresholding Methods. Water. 17(7). 1005–1005.
3.
Lee, Giha, et al.. (2025). Optimizing Stacked Ensemble Machine Learning Models for Accurate Wildfire Severity Mapping. Remote Sensing. 17(5). 854–854. 7 indexed citations
4.
Lee, Giha, et al.. (2025). Investigating the Relationship Between Topographic Variables and Wildfire Burn Severity. SHILAP Revista de lepidopterología. 5(3). 47–47. 1 indexed citations
5.
Le, Xuan-Hien, et al.. (2024). Benchmarking the performance and uncertainty of machine learning models in estimating scour depth at sluice outlets. Journal of Hydroinformatics. 26(7). 1572–1588. 11 indexed citations
6.
Lee, Giha, et al.. (2024). Underutilized Feature Extraction Methods for Burn Severity Mapping: A Comprehensive Evaluation. Remote Sensing. 16(22). 4339–4339. 2 indexed citations
7.
Lee, Giha, Duc Hai Nguyen, & Xuan-Hien Le. (2023). A Novel Framework for Correcting Satellite-Based Precipitation Products for Watersheds with Discontinuous Observed Data, Case Study in Mekong River Basin. Remote Sensing. 15(3). 630–630. 9 indexed citations
8.
Le, Xuan-Hien, et al.. (2022). Evaluation of Numerous Kinetic Energy-Rainfall Intensity Equations Using Disdrometer Data. Remote Sensing. 15(1). 156–156. 4 indexed citations
9.
Le, Xuan-Hien, et al.. (2021). Investigating Behavior of Six Methods for Sediment Transport Capacity Estimation of Spatial-Temporal Soil Erosion. Water. 13(21). 3054–3054. 4 indexed citations
10.
Le, Xuan-Hien, et al.. (2021). Comparison of Deep Learning Techniques for River Streamflow Forecasting. IEEE Access. 9. 71805–71820. 116 indexed citations
11.
Kim, Seong-Won, et al.. (2020). Assessment of Soil Erosion and Sedimentation in Cheoncheon Basin Considering Hourly Rainfall. 21(4). 5–17. 1 indexed citations
12.
Lee, Giha, et al.. (2019). Estimation of Landslide Risk based on Infinity Flow Direction. Journal of the Korean geoenvironmental society. 20(2). 5–18. 2 indexed citations
13.
Try, Sophal, et al.. (2018). Delineation of flood-prone areas using geomorphological approach in the Mekong River Basin. Quaternary International. 503. 79–86. 12 indexed citations
14.
Kim, Yeonsu, et al.. (2018). Hydrological assessment of basin development scenarios: Impacts on the Tonle Sap Lake in Cambodia. Quaternary International. 503. 115–127. 14 indexed citations
15.
An, Hyunuk, et al.. (2018). Estimation of the area of sediment deposition by debris flow using a physical-based modeling approach. Quaternary International. 503. 59–69. 14 indexed citations
16.
Lee, Giha, et al.. (2018). Large Scale Rainfall-runoff Analysis Using SWAT Model: Case Study: Mekong River Basin. Journal of The Korean Society of Agricultural Engineers. 60(1). 47–57. 1 indexed citations
17.
Lee, Giha, et al.. (2017). Comparing the performance of TRIGRS and TiVaSS in spatial and temporal prediction of rainfall-induced shallow landslides. Environmental Earth Sciences. 76(8). 36 indexed citations
18.
Yang, Jae-E., et al.. (2017). Development and Application of a Physics-based Soil Erosion Model. Journal of Soil and Groundwater Environment. 22(6). 66–73. 1 indexed citations
19.
Kim, Jae-Young, et al.. (2013). Analysis on Flood Control Effect of Siphon Spillway by Reservoir Routing. Journal of the Korean geoenvironmental society. 14(11). 55–63.
20.
Kim, Yeon‐Su, Chang‐Lae Jang, Giha Lee, & Kwansue Jung. (2010). Investigation of Flow Characteristics of Sharply Curved Channels by Using CCHE2D Model. 10(5). 125–133. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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