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Remote sensing-based detailed wetland classification: a review of advances from 2020 to 2025
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DOI：10.3389/frsen.2026.1852249.png)
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Abstract
En 中文
Wetlands play an irreplaceable role in maintaining ecological balance and conserving biodiversity. However; driven by both natural and human factors; vast wetland areas worldwide are being rapidly converted into agricultural or urban land; leading to a sharp decline in their extent and a degradation of their quality. Against this backdrop; remote sensing technology; with its unique advantages in macro-level monitoring and multi-temporal dynamic capture; provides indispensable technical support for the precise identification; classification; and change detection of wetlands; making it an essential tool for wetland monitoring; restoration assessment; conservation planning; and SDG-related evaluation. This review examines recent advances in remote sensing for detailed wetland classification over the past 5 years. It elaborates on commonly used remote sensing data sources; local and international wetland classification standards; diverse classification methods; accuracy evaluation metrics; and prospects. This review provides a comprehensive reference to remote sensing-based wetland classification studies and applications.
Keywords:
deep learning
SDGs
remote sensing
wetlands
detailed classification
Journal
F
IF:
3.7
Papers:
560
Citations:
993
Organization
Cited Papers