Author(s): Wei Jiang; Fanping Kong; Xiaohui Ding; Gan Luo; Zhiguo Pang

Linked Author(s):

Keywords: Water quality monitoring; Remote sensing; Google Earth Engine; Sentinel-2

Abstract: Accurate determination of spatiotemporal distribution characteristics of water quality parameters holds pivotal importance in monitoring water environments and aquatic ecosystems. This study is centered on the rivers and lakes within Jiujiang city, aiming to address the increasing need for more efficient, comprehensive, and continuous water quality remote sensing monitoring. Leveraging the Google Earth Engine (GEE) cloud platform and Sentinel-2 satellite data, three crucial water quality parameters -- Total Nitrogen (TN), Total Phosphorus (TP), and Chlorophyll-a (Chla) concentration -- are chosen for investigation. Through amalgamating field water quality sampling data, statistical regression models were formulated to enable remote sensing monitoring of water quality parameters. This advancement significantly enhances the efficiency of routine water quality monitoring and assessment, offering a scientific basis for decision-making in water environmental management.

DOI: https://doi.org/10.3850/iahr-hic2483430201-52

Year: 2024