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Machine learning models for wetland habitat vulnerability in mature Ganges delta

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Abstract

The present study attempts to measure wetland habitat vulnerability (WHV) in the Indian part of mature Ganges delta. Predictive algorithms belonging to bivariate statistics and machine learning (ML) algorithms were applied for fulfilling the data mining and generating the models. Results show that 60% of the wetland areas are covered by moderate to very high WHV, out of which > 300 km2 belong to very high WHV followed by a high vulnerability in almost 150 km2. This areal coverage increases by 10–15% from phase II to phase III. On the other hand, a relatively safe situation is confined to < 200 km2. The receiver operating characteristic curve, root-mean-square error, and correlation coefficient are used to assess the accuracy of these models and categorization of habitat vulnerability. Ensemble modeling is done using the individual models having a greater accuracy level in order to increase accuracy. A field-based model of the same is prepared by gathering information directly from the field which also exhibits similar results with the algorithm-based models. Analysis of residuals in standard regression strongly supports the relevance of the selected parameters and multi-parametric models.

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Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgments

For this study, the authors would like to convey their gratitude to USGS for providing Landsat imageries. They are also thankful to Swapan Talukdar, Susanta Mahato, Sk Ziaul, Pankaj Singha, and Rajesh Sarda for their assistance during field survey and software handling.

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  1. Department of Geography, University of Gour Banga, Malda, India

    Swades Pal & Sandipta Debanshi

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Both the authors contributed to the study conception and design. Conceptualization; methodology designing; supervision; editing; and reviewing were performed by Swades Pal. Data curation; investigation; formal analysis; validation; and writing of original draft were performed by Sandipta Debanshi. Both the authors read and approved the final manuscript.

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Pal, S., Debanshi, S. Machine learning models for wetland habitat vulnerability in mature Ganges delta. Environ Sci Pollut Res 28, 19121–19146 (2021). https://doi.org/10.1007/s11356-020-11413-8

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