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Estimating Endmember Backscattering Coefficients Within the Mixed Pixels Based on the Microwave Backscattering

Yubin Song1,2, Zhitong Zhang2, Hongwei Zheng3,4,5

  • 1XinJiang Huier Agriculture Group Co., Ltd., Changji 831100, China.

Sensors (Basel, Switzerland)
|December 31, 2025
PubMed
Summary

This study introduces a new model to estimate pure radar backscatter signals from mixed pixels in Synthetic Aperture Radar (SAR) imagery. The approach improves surface parameter inversion accuracy, especially for soil and grassland endmembers.

Keywords:
endmembershyperspectral unmixingmicrowave backscatter contribution decomposition modelradar backscattering coefficient

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Area of Science:

  • Remote Sensing
  • Geophysics
  • Electromagnetics

Background:

  • Mixed-pixel contamination in Synthetic Aperture Radar (SAR) imagery is a significant challenge due to land type complexity and limited spatial resolution.
  • The combination of backscattering contributions from multiple endmembers within mixed pixels hinders accurate surface parameter inversion.
  • Few studies have addressed the decomposition and estimation of pure backscatter signals within these mixed pixels.

Purpose of the Study:

  • To propose and validate a novel approach for estimating pure backscatter coefficients of endmembers within mixed SAR pixels.
  • To improve the accuracy of surface parameter inversion by addressing signal mixture issues.
  • To assess the model's performance across different endmember abundances and types.

Main Methods:

  • Utilizing hyperspectral unmixing techniques combined with the microwave backscatter contribution decomposition (MBCD) model.
  • Estimating pure backscatter coefficients for individual endmembers within mixed pixels.
  • Evaluating model performance based on endmember abundance, vegetation coverage, and the number of endmembers.

Main Results:

  • High accuracy in estimating soil backscattering coefficients was observed with vegetation coverage below 25% (R2≈0.88).
  • Estimation accuracy for soil decreased with increased vegetation coverage.
  • The model maintained high precision for grass endmembers across a wide range of vegetation coverage (0.2-0.8), with R2=0.80.

Conclusions:

  • The proposed MBCD model effectively estimates pure backscatter coefficients from mixed SAR pixels.
  • Model performance is significantly influenced by endmember abundance and type, with varying accuracy depending on vegetation coverage.
  • The approach offers a promising method for enhancing surface parameter inversion accuracy in complex land cover scenarios.