Spatiotemporal Monitoring of Chlorophyll-a in an Urban Lake Using Sentinel-2, Landsat-8, and In-Situ Data: A Case Study of Chitgar Lake, Tehran

Chlorophyll-a (Chl-a) is a key proxy for phytoplankton biomass and eutrophication in freshwater ecosystems. This study assesses Chl-a dynamics in Chitgar Lake, an artificial urban lake in Tehran, Iran, by integrating long-term in situ monitoring data (2013–2025) with multispectral satellite observations from Sentinel-2 (S2) and Landsat-8 (L8). Field measurements revealed pronounced seasonal variability, with elevated Chl-a concentrations during summer (mean: 2.93 mg/m³; maximum: 3.53 mg/m³ in August) associated with higher water temperatures (up to 30.8°C) and reduced dissolved oxygen levels (8.35 mg/L), reflecting eutrophic conditions. The mean total phosphorus concentration (0.03 mg/L) indicated phosphorus limitation, consistent with widely recognized eutrophication thresholds. Satellite-based Chl-a estimates were derived using multiple algorithms. For Landsat-8, Two-Band, Three-Band, and Complex Algorithms were applied, while Sentinel-2 analyses employed the Maximum Chlorophyll Index (MCI), Chlorophyll Index–Red Edge (CIred), and Floating Algae Index (FAI). Sentinel-2 consistently outperformed Landsat-8, with MCI providing the best performance (RMSE: 1.19 mg/m³; MAE: 0.89 mg/m³; R²: 0.74). Seasonal evaluation identified fall as the most reliable period for Chl-a retrieval using Sentinel-2, while winter showed the lowest errors but limited explanatory power (R²: 0.17–0.25). Landsat-8 exhibited higher overall errors (RMSE ≈ 2.3 mg/m³) but maintained moderate explanatory capability (R² up to 0.73), particularly in summer and fall. Spatial distribution maps demonstrated consistent temporal Chl-a patterns between sensors, although Sentinel-2’s finer spatial resolution and red-edge bands enhanced detection of small-scale variability. Overall, integrating in situ and satellite observations provides a robust framework for urban lake water-quality monitoring, supporting early eutrophication detection and informed ecosystem management.