Volume 29 Issue 6
Dec.  2023
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Article Navigation >  Journal of Geomechanics  > 2023  >  29(6): 842-855
YANG Y Z，REN J J，LI D C，2023. Quantitative staging of alluvial fan geomorphic surfaces in arid areas based on SAR imagery: A case study of the Shule River alluvial fan in the western desert region of the Hexi Corridor[J]. Journal of Geomechanics，29（6）：842−855 doi: 10.12090/j.issn.1006-6616.2023080
Citation: YANG Y Z，REN J J，LI D C，2023. Quantitative staging of alluvial fan geomorphic surfaces in arid areas based on SAR imagery: A case study of the Shule River alluvial fan in the western desert region of the Hexi Corridor[J]. Journal of Geomechanics，29（6）：842−855 doi: 10.12090/j.issn.1006-6616.2023080
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Quantitative staging of alluvial fan geomorphic surfaces in arid areas based on SAR imagery: A case study of the Shule River alluvial fan in the western desert region of the Hexi Corridor

doi: 10.12090/j.issn.1006-6616.2023080
  • 1.

    School of Emergency Management Science and Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

  • 2.

    National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China

Funds:  This research is financially supported by the National Natural Science Foundation of China (Grants No. U2139201, 41941016, and U1839204), the Key Program of the Chinese Academy of Sciences (Grant No. KFZD-SW-422), and the Research Fund of the National Institute of Natural Hazards, Ministry of Emergency Management of China (Grant No. ZDJ2017-24).
More Information
  • Received: 2023-05-21
  • Revised: 2023-09-26
  • Accepted: 2023-10-20
    • Available Online: 2024-01-10
    Abstract

  • The alluvial fans and river terraces formed by river processes effectively record past tectonic activities, climate changes, and geomorphic evolution processes. Accurately dividing the alluvial fan into stages is the basis for the subsequent research. Previous researchers used L-band SAR backscatter coefficient values as a substitute parameter for geomorphic roughness to achieve quantitative zoning of geomorphic surfaces. However, these studies did not consider the impact of different time data sources on the geomorphic surface results. This study selects the Shule River alluvial fan as the research object. It determines the optimal data source by analyzing the posterior statistical indicators of multi-temporal L-band SAR data and evaluating atmospheric conditions. The maximum likelihood classification method is used to complete the classification of backscatter intensity values and achieve quantitative staging of the geomorphic surface. The results indicate that the posterior statistical indicators of staging can be used as the standard for selecting the best temporal image data to obtain better staging results. L-band HH monopolarization data provides better staging results, demonstrating advantages in distinguishing landforms of different ages compared to C-band data. Moreover, L-band data is more accessible and holds potential for automated staging. SAR image quality and staging results are closely related to imaging atmospheric conditions but show minimal seasonal dependence. Therefore, the study recommends prioritizing images with low surface water content during imaging, such as in high-evaporation intensity summer seasons. The proposed method for analyzing remote sensing data quality and staging landforms can be applied to rapidly and quantitatively stage large-scale alluvial fans in arid regions, providing valuable information for studies on tectonics and climate.

     

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