Advances, Challenges, and Future Perspectives in Surface Water Quality Monitoring Using Remote Sensing and GIS: A Structured Literature Review
Revue Internationale de Géomatique, (2026), Vol. 35, No. 1, pp. 205-247
Jhoreene Julian a , Jerome Gacu b,c,d
a Department of Civil Engineering, College of Engineering, Central Luzon State University, Science City of Muñoz, Nueva Ecija, Philippines
b Department of Civil Engineering, Romblon State University, Odiongan, Romblon, Philippines
c Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan
d Department of Civil Engineering, College of Engineering, FEU Institute of Technology, P. Paredes St., Sampaloc, Manila, Philippines
Abstract: Surface water quality is a sensitive global environmental issue, as it is important for long-term economic development and environmental sustainability. Due to population growth, urbanization, and the effects of climate change, the degradation of surface water quality cannot be avoided. Therefore, a more accurate, continuous, and operational monitoring of water quality is highly significant. This study aims to systematically review and synthesize existing literature on the technological advancement, challenges, and future directions of Remote Sensing (RS) and Geographic Information System (GIS) techniques in surface water quality monitoring. Following PRISMA guidelines, a structured literature search of published studies was conducted across Science Direct, Web of Science, and Scopus databases between 2012 and 2025. The findings demonstrate that RS data can reliably retrieve key water quality parameters and provide large-scale, repeatable observations across surface water when integrated with GIS-based spatial modeling and in situ validation. This review systematically consolidates RS retrieval methods and GIS-based analytical frameworks, explicitly distinguishing robust retrievals from context-dependent proxy approaches and identifying methodological gaps that constrain operational deployment. The synthesis from the integration of the enhanced RS–GIS results will enable the RS–GIS community to develop a strong, scalable pathway to map spatial heterogeneity and future-ready water quality monitoring systems that support environmental sustainability, resource security across diverse aquatic environments, provide early warning on environmental risks, and inform water governance.