Comparison of water quality algorithms using satellite optical data for Korea inland water during algal blooms

The number of disasters such as floods and droughts tends to increase the scale and uncertainty of areas according to climate change. Remote sensing technology is an effective method for wide area disaster monitoring. COMS-GOCI captures the hourly images eight times a day around the Korean Peninsula and is suitable for change detection of water resources. Lansat-8 OLI and Sentinel-2 MSI data have high spatial resolution and are easy to analyze the water quality for small water body. Korea has more than 18,000 reservoirs around the country, but observation of water level, volume and quality analysis are limited, and researches were mainly carried out on local water bodies. The research on development of water quality algorithms for sea water is the main focus, and research for inland water is insufficient.

In this study, a simple atmospheric correction of each sensor was applied to analyze water quality of inland water on the Korean Peninsula using COMS GOCI, Lansat-8 OLI, and Sentinel-2 MSI optical data. We reviewed various water quality related level-2 algorithms that have been developed up to now. The data used are satellite images and field data observed during the green algae warning period issued inland on the Korean Peninsula between 2015 and 2017. The products of level-2 are chlorophyll-a concentration, total suspended sediment concentration and visibility were used. We selected candidate algorithms for each product, understood the physical mechanism, and derived the accuracy based on the results applied to the study area. As a result, we selected an algorithm suitable for analysis of inland water quality in the Korean Peninsula.