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Shallow lakes (89% of global lakes) face escalating pressures from eutrophication and climate change, yet comprehensive monitoring of chlorophyll-a (Chl-a) spatiotemporal dynamics remains challenging due to high costs and logistical constraints of traditional sampling. Developing transferable satellite-based frameworks is essential for scaling lake management from individual systems to regional assessments, particularly as climate warming intensifies phytoplankton bloom dynamics globally. We developed an integrated remote sensing framework using four decades (1984-2023) of Landsat observations (30 m Chl-a). The framework integrates: machine learning-validated retrieval algorithms, exponential modelling for nutrient-driven spatial patterns, statistical phenological analysis, and zone-specific (littoral vs. pelagic) dynamics quantification. Trend detection employs Mann-Kendall tests with Sen's slope and bootstrap uncertainty estimates. Analysis of Lake Balaton (Central Europe, 596 km², 3.7 m depth) revealed: (1) robust exponential Chl-a decay from the primary nutrient source (k=0.04-0.06 km⁻¹) consistent across four decades and varying trophic conditions; (2) pronounced spatial heterogeneity with littoral zones maintaining 1.3-2.8× higher Chl-a than pelagic zones due to integrated signals from phytoplankton, benthic algae, and macrophytes; (3) climate-driven phenological advancement of 20 days in peak timing and 10 days in growing season onset, coupled with 0.7°C/decade surface warming; (4) 68% algal biomass reduction following nutrient management, demonstrating effective restoration despite concurrent climate pressures. The methodology is currently being extending to Lake Taihu (China, 2,338 km², 1.9 m depth) through international collaboration, testing framework performance across contrasting geographic, climatic, and trophic contexts. We will present comparative results examining the generalizability of spatial decay parameters, littoral-pelagic ratios, phenological response patterns, and climate sensitivity across these systems.The transferable principles enable scaling from intensive single-lake studies to regional assessments, supporting evidence-based management for thousands of shallow lakes globally facing dual pressures of eutrophication and climate change.