Abstract. This study employs a robust remote sensing framework to analyze the spatio-temporal dynamics of cage aquaculture and its effects on water quality in Yangcheng Lake, China. Utilizing time-series Landsat 8 data (2013–2024), we accurately mapped the aquaculture extent by combining spectral water indices for water body delineation with spectral vegetation indices and Gray-Level Co-occurrence Matrix (GLCM)-based texture analysis. This approach achieved high mapping accuracies, with overall accuracies ranging from 95.96% to 98.74% and Kappa coefficients between 0.84 and 0.94, demonstrating the effectiveness of integrating spectral and textural information. Spatio-temporal analysis revealed a significant 40% reduction in aquaculture extent, from 30.41 km2 in 2013 to 17.86 km2 in 2024, directly linked to the Yangcheng Lake Action Plans. Water quality analysis using high-resolution monthly total nitrogen (TN) and total phosphorus (TP) data showed improvement from predominantly Grade IV to Grade III status, with the mean TP concentration exhibited a decrease by approximately 6.2% (from 0.0660 mg/L in 2013 to 0.0619 mg/L in 2023). Notably, a distinct lag between aquaculture reduction and water quality improvements was observed, highlighting the need for a sustained ecosystem recovery period. This research highlights the vital role of dynamic GIS for environmental monitoring and policy evaluation for fostering sustainable aquaculture and protecting lake ecosystems.
Peng et al. (2025) studied this question.