Our Study Featured on NASA Landsat Science: Advancing Water Quality Monitoring

March 26, 2025

To learn more about their groundbreaking study, please visit this link for further details: NASA Landsat Science

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We are proud to announce that the research presented by Seongjun Lee (Master's Course) in our lab, at AGU 2024, titled "Development of Chlorophyll-ɑ Prediction Model for Inland Reservoirs Using Satellite and Land Surface Model: Applying Deep Learning Approach" (Corresponding Author: Hyunglok Kim), has been featured on NASA Landsat Science.

This study was conducted by combining the high-resolution optical satellite data Harmonized Landsat and Sentinel-2 and ERA5 Land reanalysis data with deep learning approach to monitor chlorophyll-a, a representative water quality indicator in rivers and lakes in Korea. 

This study provided insight to effectively predict water quality by utilizing satellite and surface data in unmeasured areas due to the absence of water quality observatories. This breakthrough not only highlights the diversity of Landsat images, but also demonstrates the potential of remote sensing to support sustainable water management in response to the climate crisis.

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