Monitoring Lake Crab Aquaculture with Dynamic GIS: Spatio-Temporal Analysis Between Aquaculture Extent and Water Quality in Yangcheng Lake, China

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.