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<p>The suspended particulate matter (SPM) is a key parameter influencing the quality of aquatic habitats. SPM directly impacts the habitat of the “soft gold” (Artemia) in Ebinur Lake and is a major contributor to saline dust within its watershed. However, significant variations among inversion models present a challenge for SPM monitoring via remote sensing. Using Ebinur Lake as a case study, this study identify an optimal strategy for SPM monitoring. The findings are as follows: (1) Ebinur Lake water shows complete absorption at 695&#xa0;nm. (2) ESTARFM achieved a Red-band spatiotemporal fusion R<sup>2</sup> ≥0.79, leading to an SPM inversion R<sup>2</sup> of 0.75. (3) Compared to the empirical model (R<sup>2</sup> ≥ 0.72, RMSE ≤ 78.95&#xa0;mg/L), the QAA (Quasi-Analytical Algorithm) demonstrated superior adaptability (R<sup>2</sup> ≥ 0.74, RMSE ≤ 61.12&#xa0;mg/L). (4) The red-band reflectance consistency among Landsat sensors reaches R<sup>2</sup> ≥ 0.76, with a cross-platform correlation of R<sup>2</sup>= 0.73 between Landsat 8 and Sentinel 2. (5) The QAA_655(665) model is effective for Landsat 8 and Sentinel 2, whereas the EXPM (the exponential model) is more suitable for Landsat 5/7 and fusion images. This study primarily addresses the challenge of spatiotemporal inadaptability in the long-term SPM inversion process for Ebinur Lake. It can serve as a reference for water color parameter retrieval via remote sensing in globally similar environmental contexts.</p>

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A hybrid empirical and semi analytical inversion approach for remote sensing estimation of SPM in Ebinur Lake China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月23日

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  • Changjiang Liu,
  • Xingbin Xu,
  • Yingxiu Wu,
  • Fei Zhang,
  • Wenming Zhang,
  • Mou Leong Tan,
  • Ye Yuan

摘要

The suspended particulate matter (SPM) is a key parameter influencing the quality of aquatic habitats. SPM directly impacts the habitat of the “soft gold” (Artemia) in Ebinur Lake and is a major contributor to saline dust within its watershed. However, significant variations among inversion models present a challenge for SPM monitoring via remote sensing. Using Ebinur Lake as a case study, this study identify an optimal strategy for SPM monitoring. The findings are as follows: (1) Ebinur Lake water shows complete absorption at 695 nm. (2) ESTARFM achieved a Red-band spatiotemporal fusion R2 ≥0.79, leading to an SPM inversion R2 of 0.75. (3) Compared to the empirical model (R2 ≥ 0.72, RMSE ≤ 78.95 mg/L), the QAA (Quasi-Analytical Algorithm) demonstrated superior adaptability (R2 ≥ 0.74, RMSE ≤ 61.12 mg/L). (4) The red-band reflectance consistency among Landsat sensors reaches R2 ≥ 0.76, with a cross-platform correlation of R2= 0.73 between Landsat 8 and Sentinel 2. (5) The QAA_655(665) model is effective for Landsat 8 and Sentinel 2, whereas the EXPM (the exponential model) is more suitable for Landsat 5/7 and fusion images. This study primarily addresses the challenge of spatiotemporal inadaptability in the long-term SPM inversion process for Ebinur Lake. It can serve as a reference for water color parameter retrieval via remote sensing in globally similar environmental contexts.