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Table of Contents
Welcome to the GIS Lab in IESA UNG
The GIS Lab is Dr. Huidae Cho's research group in IESA. Our research focuses around the broad applications of Geographic Information Systems (GIS) and computational methods to geospatial analysis, modeling, and engineering. We use this wiki site to share project information and document our research for internal collaboration. Most of pages related to ongoing projects will be hidden from the public, but we will disseminate research findings and outcomes once the project is completed. Find the conferences where you can meet us.
Please also check these 2021 academic opportunities.
Current projects
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- Funded by the Georgia Forestry Commission
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- A special topic in GIS for spring 2020
- Idea proposed by Huidae Cho and partially implemented by Tyler Henderson
- Ongoing collaboration project with Dr. Tien Yee from Kennesaw State University
Projects on hold
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- Idea proposed by Huidae Cho, but put on hold because of a lack of budget
Past projects
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- Funded by the Georgia Forestry Commission
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- A special topic in GIS for spring 2020
- Idea proposed and implemented by Owen Smith
Software
- r.accumulate: An efficient flow accumulation addon for GRASS GIS
- CanoClass: An open-source Python module for canopy classification using scikit-learn
- CanoPy: A Python module for canopy classification using Feature Analyst
- GRASS GIS for MS Windows
Manuscripts in preparation
- Owen Smith, Huidae Cho. An Open-Source Canopy Classification System Using Machine-Learning Techniques Within a Python Framework. Environmental Modelling & Software. SCIE, 2019 Impact Factor 4.807.
- Huidae Cho, Owen Smith. Quantifying Decade Canopy Change for the State of Georgia Utilizing NAIP Imagery from 2009–2019. Forestry. SCIE, 2019 Impact Factor 2.293 (too low, maybe a remote sensing journal?).
Manuscripts under review
- Aboalhasan Fathabadi, Huidae Cho, Seyed Morteza Seyedian, Bahram Choubin. Comparison of Bayesian Model Averaging and GLUE Weighting Methods for Uncertainty Estimation in Hydrologic Modeling. Journal of Hydrology. SCIE, 2019 Impact Factor 4.500.
Recent publications
- Huidae Cho, September 2020. A Recursive Algorithm for Calculating the Longest Flow Path and Its Iterative Implementation. Environmental Modelling & Software 131, 104774. 10.1016/j.envsoft.2020.104774. SCIE, 2019 Impact Factor 4.807, Author's Version.
- Huidae Cho, Jeongha Park, Dongkyun Kim, March 2019. Evaluation of Four GLUE Likelihood Measures and Behavior of Large Parameter Samples in ISPSO-GLUE for TOPMODEL. Water 11 (3), 447. doi:10.3390/w11030447. SCIE, 2019 Impact Factor 2.544.
- Huidae Cho, Tien M. Yee, Joonghyeok Heo, October 2018. Automated Floodway Determination Using Particle Swarm Optimization. Water 10 (10), 1420. doi:10.3390/w10101420. SCIE, 2019 Impact Factor 2.544.
- Dongkyun Kim, Huidae Cho, Christian Onof, Minha Choi, May 2017. Let-It-Rain: A Web Application for Stochastic Point Rainfall Generation at Ungaged Basins and Its Applicability in Runoff and Flood Modeling. Stochastic Environmental Research and Risk Assessment 31 (4), 1023-1043. doi:10.1007/s00477-016-1234-6. SCI, 2019 Impact Factor 2.351.
- Huidae Cho, Emma Bones, August 2016. Quantification of Uncertainties in the 100-year Flow at an Ungaged Site Near a Gaged Station and Its Application in Georgia. Journal of Hydrology 539, 640-647. doi:10.1016/j.jhydrol.2016.05.070. SCI, 2019 Impact Factor 4.500, Author's Version.
Other resources
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