Dark-object subtraction atmosphere correction for water body information extraction in Zhuhai-1 hyperspectral imagery

Abstract

The atmospheric correction of hyperspectral data stands as a fundamental step in quantitative applications, crucial for the accurate analysis of hyperspectral information. Zhuhai-1 hyperspectral data, characterized by its high spatial and spectral resolution, holds substantial potential and advantages for the quantification of water body information. Nonetheless, the adoption of more precise physical models for atmospheric correction often demands extensive satellite and ground environmental parameters, which pose practical challenges in applying physical models The Dark Object Subtraction (DOS), leveraging the intrinsic spectral characteristics of the imagery, offers an efficient alternative for achieving improved atmospheric correction results tailored to the data and study area. In this context, this study presents a Dark Object Subtraction for Water body information extraction (DOSW), specifically designed to advance the quantification of water body information in Zhuhai-1 hyperspectral data. The proposed method is rigorously evaluated by comparing the correction results from the Foshan region and Feilaixia Reservoir with standard and measured spectra of typical objects. The results demonstrate the accuracy of DOSW in atmospheric correction, with correlation coefficients exceeding 0.7 when compared to standard spectra for three representative objects. Notably, DOSW achieves exceptional accuracy in water body correction, achieving a correlation coefficient of 0.95 and an RMSE of 0.002 in the Feilaixia Reservoir, and a correlation coefficient of 0.72 and an RMSE of 0.005 in the Foshan region. Overall, the results underscore the efficacy of DOSW in accurately addressing atmospheric correction challenges to Zhuhai-1 hyperspectral data, effectively meeting the requirements of hyperspectral quantification applications.

Keywords

• Dark-object subtraction
• Reflectance of water body
• Atmosphere correction assessment
• Zhuhai-1 hyperspectral images