Woo-Kyun Lee

Orcid: 0000-0002-2188-359X

According to our database1, Woo-Kyun Lee authored at least 13 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Application of the domain adaptation method using a phenological classification framework for the land-cover classification of North Korea.
Ecol. Informatics, 2024

Towards Global Crop Maps with Transfer Learning.
Proceedings of the IGARSS 2024, 2024

2023
Modeling Historical and Future Forest Fires in South Korea: The FLAM Optimization Approach.
Remote. Sens., March, 2023

2022
Towards Global Crop Maps with Transfer Learning.
CoRR, 2022

2021
Phenological Classification Using Deep Learning and the Sentinel-2 Satellite to Identify Priority Afforestation Sites in North Korea.
Remote. Sens., 2021

Evaluation and Comparison of Satellite-Derived Estimates of Rainfall in the Diverse Climate and Terrain of Central and Northeastern Ethiopia.
Remote. Sens., 2021

2020
Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea.
IEEE Trans. Geosci. Remote. Sens., 2020

2019
Multi-Temporal Analysis of Forest Fire Probability Using Socio-Economic and Environmental Variables.
Remote. Sens., 2019

Hydrological Response of Dry Afromontane Forest to Changes in Land Use and Land Cover in Northern Ethiopia.
Remote. Sens., 2019

2012
Estimating the spatial pattern of human-caused forest fires using a generalized linear mixed model with spatial autocorrelation in South Korea.
Int. J. Geogr. Inf. Sci., 2012

Estimation of PAIe using airborne LiDAR data in South Korea.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012

2011
Forest Cover Classification by Optimal Segmentation of High Resolution Satellite Imagery.
Sensors, 2011

Estimating Crown Variables of Individual Trees Using Airborne and Terrestrial Laser Scanners.
Remote. Sens., 2011


  Loading...