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Abstract <p>Lunar swirls are one of the most enigmatic features on the Moon, the spectral characteristics of which have been extensively studied. However, the quantitative statistical validation of the difference between the swirl interiors and the surrounding areas remains limited. In the present work, reflectance data from Moon Mineralogy Mapper on Chandrayaan-1 were used to examine four swirl areas, viz. one mare and three highland swirls. The Principal Component Analysis (PCA) was applied to hyperspectral reflectance data to isolate the albedo variation and optical maturity. We combined three PCA axes corresponding to the albedo, high Optical Maturity (OMAT) and low OMAT to generate RGB composite images that allow identification of swirl patterns. Several hundreds to thousands of pixels were selected from each ON-swirl and OFF-swirl region to characterize their spectral features. Pixel-wise reflectance and continuum-removed spectra were extracted for all four lunar swirl regions examined in this study, and absorption band depths at 1 and 2 µm were quantified. Following the continuum removal, a stability-based Monte-Carlo resampling approach was used to assess the statistical significance of ON and OFF-swirl changes. Welch’s two-sample <i>t</i>-test was used to evaluate statistical significance, and Cohen’s <i>d</i> affected size was computed to measure the magnitude of ON-OFF swirl difference in the absorption band depth. In addition to explicitly accounting for spatial heterogeneity and swirl-to-swirl variations, our combined spectral–statistical approach offers a reliable and repeatable framework for evaluating spectral variability across several lunar swirl regions.</p>

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Mapping the Spectral Diversity of Lunar Swirls Using Chandrayaan-1 M3 Hyperspectral Images

  • 期刊论文

  • 发表日期：

    2026年7月22日

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  • Bhumi Jadhav,
  • Jayesh Pabari,
  • Vaishali Bhavsar

摘要

Abstract

Lunar swirls are one of the most enigmatic features on the Moon, the spectral characteristics of which have been extensively studied. However, the quantitative statistical validation of the difference between the swirl interiors and the surrounding areas remains limited. In the present work, reflectance data from Moon Mineralogy Mapper on Chandrayaan-1 were used to examine four swirl areas, viz. one mare and three highland swirls. The Principal Component Analysis (PCA) was applied to hyperspectral reflectance data to isolate the albedo variation and optical maturity. We combined three PCA axes corresponding to the albedo, high Optical Maturity (OMAT) and low OMAT to generate RGB composite images that allow identification of swirl patterns. Several hundreds to thousands of pixels were selected from each ON-swirl and OFF-swirl region to characterize their spectral features. Pixel-wise reflectance and continuum-removed spectra were extracted for all four lunar swirl regions examined in this study, and absorption band depths at 1 and 2 µm were quantified. Following the continuum removal, a stability-based Monte-Carlo resampling approach was used to assess the statistical significance of ON and OFF-swirl changes. Welch’s two-sample t-test was used to evaluate statistical significance, and Cohen’s d affected size was computed to measure the magnitude of ON-OFF swirl difference in the absorption band depth. In addition to explicitly accounting for spatial heterogeneity and swirl-to-swirl variations, our combined spectral–statistical approach offers a reliable and repeatable framework for evaluating spectral variability across several lunar swirl regions.