Research on Inversion Technology of Empirical Models for Water Chlorophyll Concentration Based on Sentinel-2 Images

Abstract. To address the limitations of traditional fixed-point sampling for monitoring water chlorophyll concentration and improve the inversion accuracy of complex inland waters, this study took the Naoli River Nature Reserve as the research area and conducted research based on Sentinel-2 images and measured chlorophyll point data. First, the study performed combined calculations on multispectral bands to generate multiple derived bands, and selected "B4+B5+B6" as the optimal band combination through the coefficient of determination (R²). Then, using this combination as input, various empirical models were constructed and evaluated using multiple indicators. The results showed that the univariate cubic function model had the highest R² and the smallest multiple error indicators, which was significantly better than other models, and successfully realized the spatial inversion of chlorophyll concentration in the study area. This study reveals the complex nonlinear relationship between chlorophyll and band combinations, provides a high-precision inversion technical scheme for water chlorophyll, offers data support for algal bloom early warning and water quality fluctuation tracking, and provides scientific references for the optimization of river basin management measures and ecological protection decisions.