基于GEE平台水质监测应用的研究进展OA

The increasingly severe global water environment crisis has underscored the critical importance of water quality monitoring in environmental management.Traditional monito-ring methods are constrained by high costs and low efficiency,posing significant challenges to large-scale application.The integration of remote sensing technology with the Google Earth Engine(GEE)platform provides an innovative and efficient approach to water quality monitoring.GEE integrates multi-source remote sensing datasets-such as Landsat,Senti-nel and MODIS-with powerful cloud-based computational capabilities,enabling the spati-otemporal inversion of key water quality parameters including chlorophyll-a,total nitro-gen,and total phosphorus.The platform supports real-time processing of petabyte-scale remote sensing data,greatly improving the feasibility of long-term and large-scale water quality assessment.However,current studies indicate that GEE-based monitoring still faces challenges such as insufficient high-resolution imagery coverage,limited regional a-daptability of retrieval algorithms,and the scarcity of in-situ calibration data,all of which constrain its accuracy and applicability in remote regions.Future research should focus on enhancing access to high-resolution datasets,developing more adaptive retrieval models,and strengthening the integration of multi-source data and machine learning techniques.As the global market for real-time water quality monitoring continues to expand,the GEE platform will play a pivotal role in shifting water quality management from reactive treat-ment to proactive early warning and decision-making,providing essential technological sup-port for water environment governance.