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

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.

Keywords

• sar
• geomorphic surface of the alluvial fan
• quantitative staging
• backscatter coefficient
• roughness
• maximum likelihood classification