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“Source–sink” landscape pattern analysis of nonpoint source pollution using remote sensing techniques

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Abstract

Research on the “source–sink” landscape pattern of nonpoint source pollution is of great significance to natural resource management, environmental protection, water quality improvement, nonpoint source pollution prevention and control, and ecological security pattern construction. Remote sensing has proven by many scholars as a practical and effective technique to study landscape patterns and nonpoint source pollution. However, there are still many obstacles to the application of remote sensing technology, such as classification errors, scale effects and the issue, whereby landscape metrics cannot describe the landscape information comprehensively. In view of the characteristics of the macroscale and multi-scale of remote sensing, the analysis of landscape patterns is the basis for the study of the relationship research between patterns and ecological processes, and it is also the key to the study of landscape dynamics and functions. This paper attempts to summarize the representative results and the challenges of remote sensing in the study of the source and sink landscape of the nonpoint source pollution landscape and provide corresponding solutions as a reference for future research.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their constructive comments and suggestions. The study is funded by the Natural Science Foundation of China (Grant No. 61473286) and the National Science & Technology Program of China (grant No. 2017YFB0504201).

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

    X. Zhang, Q. Y. Wu, J. T. Cui & Y. Q. Liu

  2. Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, 830011, Urumqi, Xinjiang, China

    W. S. Wang

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Zhang, X., Wu, Q.Y., Cui, J.T. et al. “Source–sink” landscape pattern analysis of nonpoint source pollution using remote sensing techniques. Int. J. Environ. Sci. Technol. 15, 2253–2268 (2018). https://doi.org/10.1007/s13762-018-1683-1

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