Remote Sensing of Non-Intertidal Wetlands: An Overview of Current Status and Future Research Directions
Zhao Y. Samat A. Du P. Luo K. Zhu E. Li W.
June 2026Springer Nature
Journal of Geovisualization and Spatial Analysis
2026#10Issue 1
Wetlands are critical ecosystems that deliver essential services such as water purification, flood regulation, and biodiversity support. Non-intertidal wetlands, in particular, play a key role in maintaining global ecological balance. However, due to their complex structures and dynamic nature, monitoring these ecosystems poses significant challenges. This study offers a comprehensive review of current remote sensing techniques applied to non-intertidal wetlands, with a focus on classification and mapping, vegetation and biodiversity assessment, hydrological monitoring, water quality evaluation, spatiotemporal dynamics, and ecosystem service quantification. We further examine the diverse data sources, analytical models, and technical tools used to monitor these ecosystems. Key challenges identified include limitations in spatial and temporal resolution, ecosystem complexity, and the difficulties of large-scale monitoring. To overcome these barriers, the paper explores promising future directions, including multi-source data integration, the advanced use of hyperspectral satellites, the application of artificial intelligence and machine learning, the coupling of ecological models with socio-economic data, and the development of a global non-intertidal wetland monitoring system. These strategies hold the potential to enhance scientific understanding, support effective conservation efforts, and facilitate sustainable management practices for wetland ecosystems.
Artificial intelligence , Deep learning , Ecosystem service functions , Machine learning , Non-intertidal Wetlands , Remote sensing , Wetland classification and mapping
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State Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China
University of Chinese Academy of Sciences, Beijing, China
China-Kazakhstan Joint Laboratory for Remote Sensing Technology and Application, Al-Farabi Kazakh National University, Almaty, Kazakhstan
School of Geography and Ocean Science, Nanjing University, Nanjing, China
College of Surveying and Geo-Informatics, Tongji University, Shanghai, China
Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
State Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands
University of Chinese Academy of Sciences
China-Kazakhstan Joint Laboratory for Remote Sensing Technology and Application
School of Geography and Ocean Science
College of Surveying and Geo-Informatics
Department of Electrical
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