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Global Wetland Datasets: a Review

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Abstract

Accurate wetland datasets are indispensable for generating polices on wetland conservation and appropriate land uses, global climate change studies, and biodiversity conservation. Although increasing numbers of global wetland-related datasets have been established, the extensive disagreements among these datasets are prominent. In particular, estimates of global wetland area range from 0.54 to 21.26 million km2 and the class-specific spatial consistency of wetlands is less than 1%. The different definitions of ‘wetland’ and the intrinsic features of wetlands contribute to this extensive inconsistency. Given the various requirements of wetland-oriented data products, it is important to conduct comprehensive wetland mapping at global scale. The Ramsar wetland definition is recommended and a hierarchical and flexible structure of wetland classification system is preferred for future global wetland datasets. Time-series satellite imagery at 250–1000 m spatial resolution is preferred to characterize wetland dynamics by combination of passive/active SAR data and other ancillary data, such as topography, climate, and soil data. The classification tree method for classification of massive satellite imagery and big-data technology for sample datasets are promising for the enhancement of wetland map product accuracy.

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Acknowledgements

This research was supported by National Natural Science Fund of China (41271423). We also greatly appreciated the professional comments and advice of the anonymous reviewers.

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  1. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China

    Shengjie Hu, Zhenguo Niu & Yanfen Chen

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  1. Shengjie Hu
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Correspondence to Zhenguo Niu.

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Hu, S., Niu, Z. & Chen, Y. Global Wetland Datasets: a Review. Wetlands 37, 807–817 (2017). https://doi.org/10.1007/s13157-017-0927-z

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