Authors
Hui Ye, Yan-Yan Li, Xin-Xin Wang, Ying Liu, Yu-Han Zheng, Xi Zhang, Hong-Yang Chen, Yong-Chao Liu, Ming Nie, Bo Li
Published in
Ying yong sheng tai xue bao = The journal of applied ecology. Volume 37. Issue 9. Pages 2929-2944. Sep 18, 2026.
Abstract
Wetlands are critical ecosystems that support hydrological and climate regulation, biodiversity conservation, and ecological security. However, under the combined pressures of climate change and human activities, global wetlands are increasingly facing severe area loss, functional degradation, and habitat fragmentation. With the advantages including long-term time-series records, broad spatial coverage, and multi-source observations, remote sensing big data provide essential technical support for identifying wetland degradation, monitoring dynamic changes, tracking restoration processes, and enabling risk early warning. We systematically reviewed the current applications, technical approaches, assessment frameworks, and future development directions of remote sensing big data in wetland monitoring. First, we sorted out the characteristics of remote sensing big data sources and their applicability in wetland monitoring. Second, we comparatively analyzed recent advances in wetland information extraction techniques based on spectral features, temporal characteristics, machine learning, deep learning, and multi-source data fusion. Third, from the perspectives of hydrological processes, vegetation function, landscape structure, and temporal stability, we constructed a remote sensing-based assessment framework for monitoring wetland degradation and restoration, and explored its applications in degradation diagnosis, restoration trajectory tracking, effectiveness evaluation, and instability early warning. Finally, we identified key challenges in current applications, including difficulties in integrating massive heterogeneous datasets, limitations in spatiotemporal resolution, the complexity of wetland surface conditions, and insufficient ecological interpretation. Accordingly, we proposed future development pathways involving multi-source sensor synergy, model construction for complex scenarios, multi-factor environmental assessment, and innovation in governance models. This review would provide theoretical references and technical guidance for whole-process monitoring of wetland degradation and restoration, evaluation of ecological conservation and restoration, and intelligent wetland governance.
PMID:
42864085
Bibliographic data and abstract were imported from PubMed on 13 Oct 2026.
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