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The Applicability of Remote Sensing Models of Soil Salinization Based on Feature Space

Author

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  • Jing Liu

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830000, China
    Key Laboratory of Grassland Restoration and Environmental Information, Urumqi 830000, China
    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Li Zhang

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830000, China
    Key Laboratory of Grassland Restoration and Environmental Information, Urumqi 830000, China)

  • Tong Dong

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830000, China
    Key Laboratory of Grassland Restoration and Environmental Information, Urumqi 830000, China)

  • Juanle Wang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Yanmin Fan

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830000, China
    Key Laboratory of Grassland Restoration and Environmental Information, Urumqi 830000, China)

  • Hongqi Wu

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830000, China
    Key Laboratory of Grassland Restoration and Environmental Information, Urumqi 830000, China)

  • Qinglong Geng

    (Institute of Soil and Fertilizer and Agricultural Water Conservation, Xinjiang Academy of Agricultural Sciences, Urumqi 830000, China)

  • Qiangjun Yang

    (China Geo-Engineering Corporation, Beijing 100101, China)

  • Zhibin Zhang

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830000, China
    Key Laboratory of Grassland Restoration and Environmental Information, Urumqi 830000, China)

Abstract

Soil salinization is a major challenge for the sustainable use of land resources. An optimal remote sensing inversion model could monitor regional soil salinity across diverse geographical areas. In this study, the feature space method was used to study the applicability of the inversion model for typical salt-affected soils in China (Yanqi Basin (arid area) and Kenli County (coastal area)), and to obtain soil salinity grade distribution maps. The salinity index (SI) surface albedo (Albedo)model was the most accurate in both arid and coastal regions with overall accuracy reaching 93.3% and 88.8%, respectively. The sensitivity factors for the inversion of salinity in both regions were the same, indicating that the SI-Albedo model is applicable for monitoring salinity in arid and coastal areas of China. We combined Landsat 8 Operational Land Imager image data and field data to obtain the distribution pattern of soil salinity using the SI-Albedo model and proposed corresponding countermeasures for soil salinity in the Yanqi Basin and Kenli County according to the degree of salinity. This study on soil salinity in arid and coastal areas of China will provide a useful reference for future research on soil salinity both in China and globally.

Suggested Citation

  • Jing Liu & Li Zhang & Tong Dong & Juanle Wang & Yanmin Fan & Hongqi Wu & Qinglong Geng & Qiangjun Yang & Zhibin Zhang, 2021. "The Applicability of Remote Sensing Models of Soil Salinization Based on Feature Space," Sustainability, MDPI, vol. 13(24), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:24:p:13711-:d:700587
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    Citations

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    Cited by:

    1. Zixuan Zhang & Beibei Niu & Xinju Li & Xingjian Kang & Zhenqi Hu, 2022. "Estimation and Dynamic Analysis of Soil Salinity Based on UAV and Sentinel-2A Multispectral Imagery in the Coastal Area, China," Land, MDPI, vol. 11(12), pages 1-21, December.
    2. Jiawen Hou & Yusufujiang Rusuli, 2022. "Assessment of Soil Salinization Risk by Remote Sensing-Based Ecological Index (RSEI) in the Bosten Lake Watershed, Xinjiang in Northwest China," Sustainability, MDPI, vol. 14(12), pages 1-16, June.

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