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Suitability mapping of global wetland areas and validation with remotely sensed data

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  • Special Topic: Remote Sensing and Global Change
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Abstract

With increasing urbanization and agricultural expansion, large tracts of wetlands have been either disturbed or converted to other uses. To protect wetlands, accurate distribution maps are needed. However, because of the dramatic diversity of wetlands and difficulties in field work, wetland mapping on a large spatial scale is very difficult to do. Until recently there were only a few high resolution global wetland distribution datasets developed for wetland protection and restoration. In this paper, we used hydrologic and climatic variables in combination with Compound Topographic Index (CTI) data in modeling the average annual water table depth at 30 arc-second grids over the continental areas of the world except for Antarctica. The water table depth data were modeled without considering influences of anthropogenic activities. We adopted a relationship between potential wetland distribution and water table depth to develop the global wetland suitability distribution dataset. The modeling results showed that the total area of global wetland reached 3.316×107 km2. Remote-sensing-based validation based on a compilation of wetland areas from multiple sources indicates that the overall accuracy of our product is 83.7%. This result can be used as the basis for mapping the actual global wetland distribution. Because the modeling process did not account for the impact of anthropogenic water management such as irrigation and reservoir construction over suitable wetland areas, our result represents the upper bound of wetland areas when compared with some other global wetland datasets. Our method requires relatively fewer datasets and has a higher accuracy than a recently developed global wetland dataset.

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Correspondence to Peng Gong.

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Zhu, P., Gong, P. Suitability mapping of global wetland areas and validation with remotely sensed data. Sci. China Earth Sci. 57, 2283–2292 (2014). https://doi.org/10.1007/s11430-014-4925-1

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  • DOI: https://doi.org/10.1007/s11430-014-4925-1

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