Remote Sensing Application in Water Quality of Lake Burdur, Türkiye

Abstract

The advancements in space technology have facilitated water quality (WQ) monitoring of lake conditions at a spatial resolution of 10 m by freely accessible Sentinel-2 images. The main aim of this article was to elucidate the necessity of spatiotemporal WQ monitoring of the shrinking Lake Burdur in Türkiye by examining the relation between field and satellite data with a state-of-the-art machine learning- based regression algorithm. This study focuses on detection of algal blooms and WQ parameters, which are chlorophyll-a (Chl-a) and suspended solids (SS). Furthermore, this study leverages the advantage of geographic position of Lake Burdur, located at the overlap of two Sentinel-2 frames, which enables the acquisition of satellite images at a temporal resolution of 2–3 days. The findings enrich the understanding of the lake's dynamic structure by rapidly monitoring the occurrence of algal blooms. High accuracies were achieved for Chl-a (R-squared: 0.93) and SS (R-squared: 0.94) detection.